WO2003034300A2

WO2003034300A2 - Marketing communication and transaction/distribution services platform for building and managing personalized customer relationships

Info

Publication number: WO2003034300A2
Application number: PCT/IB2002/005796
Authority: WO
Inventors: Ramon Van Der Riet
Original assignee: Ramon Van Der Riet
Priority date: 2001-09-04
Filing date: 2002-09-04
Publication date: 2003-04-24
Also published as: US20110202404A1; US20030126146A1; US7158943B2; WO2003034300A9; US20070260521A1; WO2003034300A8; US7917388B2

Abstract

An interactive marketing communication and transaction services platform for managing personalized customer relationships. The platform facilitates communication and transactions between consumers, retailers and manufacturers, by helping suppliers customize product/service offerings, presentations and advertising messages to reflect individual consumers' needs, while providing portals with premium advertising messages for personal interactive info/news/entertainment services. The core of the platform consists of i) a central database system with 'product/retail information' and 'holistic purchase behaviour specific consumer profiles', generated by registering on-line product/retail information retrieved by consumers, as well as purchases made both on-line and in-store, using a loyalty card; ii) software applications, that create 'market intelligence' on manufacturer/retailer offers, consumer purchase needs, market performance of products/retailers and impact of brand/retailer presentations and ads on consumer purchase behavior; and iii) standard performance indicators, that make it possible to benchmark individual consumer communication programs against each other.

Description

MARKETING COMMUNICATION AND TRANSACTION/DISTRIBUTION SERVICES PLATFORM FOR BUILDING AND MANAGING PERSONALIZED CUSTOMER RELATIONSHIPS.

Field of the invention An interactive marketing communication and transaction/distribution services platform for building and managing personalized customer relationships. The invention provides consumers with privacy, product/retailer (re)search, shopping and ad based personalized info, news and entertainment services, its manufacturing and retailing clients with interactive marketing communication, IT, research support and effectiveness benchmarking services and interactive media and telecom companies with premium advertising, needed to develop profitable ad-based personalized interactive info, news and entertainment services.

Background of the invention

In recent years, the internet has been recognized as a powerful new medium that potentially can make consumer communication processes more effective. The internet presents an opportunity to build online personalized relationships with consumers. Advertisers have recognized the potential of online advertising, but early experiences with banner ad formats have been disappointing.

Advertisers, however, continue to recognize the internet's potential to streamline their advertising communication processes. It is a medium, that allows to track individual consumer's purchase and shopping behavior and to tailor advertising messages to the individual purchase and shopping needs of consumers, something that is not possible with traditional mass media, where advertising messages are generic, cannot be customized and where purchase behavior cannot be tracked. Further, the internet allows to measure the effect of advertising on consumer purchase behavior. Advertisers, finally, recognize the potential of realizing improved advertising delivery efficiencies that result from moving away from unfocused mass advertising to a more personalized and automated electronic delivery approach, where advertising exposure is confined to sending personalized messages only to those consumers who are potentially interested in the advertiser's product.

However, for a personalized advertising approach to be successful, advertisers need a standardized consumer profiling system that is portal and retailer independent. It is also necessary to develop a standardized consumer feedback measurement system which measures the effectiveness of the advertising portal and retailer independent. Without it, advertisers have to deal with the complexity of a multitude of different profiling and consumer feedback systems. This has proven to be a barrier to achieving the above described vision of 'personalized advertising'. In general, consumers prefer to browse aggregated retailer or portal websites over individual manufacturer websites when looking for product specific information. Therefore, it would be desirable for manufacturers if via a central system they could directly control their product related information displayed on retailer or portal. Specifically, it would be beneficial if manufacturers could control all the brand product presentations at the different retailer and portal websites, where the product is listed, from one desktop which is located, for example, at the manufacturer's head office. It would also be desirable for manufacturers if via a central system they were to be able to personalize the brand product presentations depending on the language and needs of an individual consumer. Because manufacturers desire to avoid channel conflicts with their distribution partners, they cannot create distribution channels that compete with them or develop initiatives that risk taking over the retailer's consumer relationships. However, both manufacturers and retailers realize that they have in common that they have the same consumer client. They are gradually recognizing that a collaborative retail/manufacturing selling approach would be financially beneficial to both the retailers and the manufacturers. They are creating joint category management initiatives, collaborative IT platforms that automate 'Planning, Forecasting and Replenishment' processes and electronic data exchange systems between retailers and manufacturers. Both parties are also more frequently exchanging their consumer data. In addition to the above, retailers are increasingly recognizing the potential of the internet as a new distribution channel that can improve the efficiency of their store operations and provide consumers with the convenience of home shopping and delivery. Thus, many such retailers have begun acquiring e-commerce competencies by either purchasing upstarts or building up expensive e-commerce organizations and systems themselves. The necessary information technology (IT) and marketing resources are a great financial burden for those retailers, who are traditionally accustomed to small margins and relatively low IT and marketing expenses. Due to the lack of standard communication protocols between retailers and manufacturers, the process of building a retailer website is still very inefficient. Each retailer must independently build up category presentations. Further, each retailer must also build product presentations relating to the manufacturer's products which are listed in the retailer's on-line store. Traditionally, each retailer has been responsible for their in-store category presentations. However, the actual product brand presentation was a function, that was traditionally handled by the manufacturer via packaging and mass advertising. It is apparent that taking over this product brand presentation function from the manufacturer is very labour intensive for retailers. It is also evident that manufacturers are hesitant to relinquish control of the online presentation of their brands to the retailers. Thus, retailers need to assess whether their internet business will be able to absorb these additional in-house overhead costs or whether it is more practical to organize collaborative selling processes to outsource these non-core functions to manufacturers and or to IT (information technology) and marketing services specialists, that will be able to perform these tasks better and at lower costs.

There are currently software packages which are less expensive and perform better then the in-house developed store front and website systems described above. However, the marketing knowledge needed to use the personalization features of these software packages is still missing in these retailing companies. Thus, the communication potential of these systems is not being fully exploited. Adapting manufacturer brand presentations and retailer category presentations to individual consumer needs is a complex task. One way of simplifying the retailer task would be for the retailer to assume the retailer category presentation personalization function and to leave the product brand personalization function to the manufacturer. Such a collaborative approach would allow retailers to construct their categories from product brand presentations stored in a central database. This would make the process of creating retailer presentations more efficient. Further, this approach would ensure that the retailer category presentations would contain the latest product brand descriptions as well as product brand descriptions, that are automatically adapted to the needs of individual consumers.

For retailers, it would be ideal if, from one desktop at a head office for example, they could build the retail category presentations from the product brand descriptions stored in a central database and have the system personalize these product brand presentations depending on the language and needs of the consumer. A collaborative approach on a central platform would lower IT investments as it would avoid the need for each individual retailer to establish separate IT systems that link with its various manufacturers. A collaborative system with a central product presentation database and a standardized consumer profiling and purchase behavior tracking system would further avoid the need to define separate consumer profiles and feedback information protocols required for the exchange of consumer data between retailers and manufacturers, as well as make it possible to measure and to benchmark the effectiveness of brand and retailing presentations against each other. Absent a central product presentation database and a standardized profiling and consumer feedback system, separate consumer profile and feedback information protocols would have to be defined for each manufacturer-retailer relation, greatly reducing the benefit impact of the collaborative approach as well as its chances of success.

Traditionally, web portal designers have been successful in creating convenient and interesting content and information services, but most of them have failed to turn their efforts into a profit. As a result, most portals operate at a loss. Many portals have attempted to rework their business model, which has largely been dependent on banner advertising revenues. One solution which was proposed included using consumer-paid subscription models for interactive personal information, news, music and entertainment services. However, it is difficult to convince consumers that they should start paying for a service, which until now has been free. Other efforts by portals included requesting that manufacturers and/or retailers pay the portals for displaying their product brand and/or retail category presentations. Some have incorporated comparison shopping services that compare products based on price. These services do not have the support of manufacturers and/or retailers, who refuse to pay the portals for these services.

For interactive personal information, news, music and entertainment services to become profitable and to be able to compete against the classical mass media, like tv, radio, and print, it would be desirable to exploit the internet's personalized advertising delivery capabilities, which traditional mass media and its advertising cannot offer. To justify premium rates advertisement messages must be personalized. However, without a standard profiling and segmentation system for profiling consumers and measuring advertising impact on consumer purchase behavior, these new interactive media will not gain the acceptance of advertisers. Telephone and cable companies have invested heavily in broadband and in third generation (3G) wireless infrastructure development. The telephone and cable companies hope to recuperate their investments through broadband information, news, music and entertainment services. Subscription-based models are one possible way for these companies to recuperate their investments. However, the consumer cost for these services is extremely high. Ad-based models, which are based on premium personalized ad messages, are another option for telephone and cable companies. This option reduces the cost to the consumer. For interactive information, news, music and entertainment services to be able to compete against the classical mass media, like tv, radio, and print, for example, it will would be desirable to develop and exploit personalized ad delivery capabilities, which is something that mass media cannot offer. To exploit these capabilities, advertisement messages must be personalized. However, again, without a standard profiling and segmentation system for profiling consumers, these new interactive services will not gain the acceptance of advertisers. Premium ad-based models are only possible with a standard portal and retailer independent system for profiling the consumers that use these services as well as a standard portal and retailer independent system for measuring the impact of its advertising on consumer purchase behavior. Without it, individual personal information, news, and entertainment service would have incongruous segmentation, profiling, and measurement systems. As a result it is unlikely advertisers will be able to efficiently target their messages nor track the effectiveness of their advertising investments.

In addition to a need for standardized consumer, manufacturers, retailers, and portals need to consider the consumer's concern about their privacy. Consumers are aware that their behavior on the internet is registered and this is generally seen as unpleasant. In addition, consumers are also bothered by consumer address companies which send irrelevant messages commonly known as "spam" messages. These consumer address companies collect consumer profiles but do not reward consumers for providing this information. If consumers shopped at an aggregated shopping service that protects and respects their privacy, the above-mentioned privacy concerns would be greatly eliminated. Consumers could store their shopping needs and preferences on one central location and could maintain control over this information. Because this service could ensure that it would not sell and/or relay individual consumer profiles to third parties, the consumer could avoid receiving unwanted advertisements or messages. In\exchange for this privacy guarantee, as well as other possible benefits, the consumer would permit their shopping habits and preferences data to be processed into valuable information which allows retailers and/or manufacturers to improve their product and/or category offers and to personalize their advertisements so that they are more relevant to the consumer. Further, it is very inconvenient for consumers to repeatedly enter their shopping needs at different websites. An aggregated holistic profiling system, that creates a single consumer profile that captures a consumer's complete purchase and shopping behavior is preferable over a multiple of individual retailer systems that each capture only a part of the consumer's purchase behavior. This single profile would benefit the consumer and advertisers, as it would enhance consumer's shopping convenience as well as advertising impact by making advertising messages more relevant to consumers.

Summary of the Invention

The system of the invention addresses the above' described problems by providing a collaborative interactive system. According to an embodiment of the invention, a multilingual collaborative interactive marketing communication and transaction/distribution services platform is provided for building and managing personalized customer relationships. The platform of the invention preferably provides consumers with privacy as well as product and retailer related research and shopping services. In addition, the platform provides consumers with ad-based personalized info, news and entertainment services, provides manufacturers and/or retailers with interactive marketing communication and research support and interactive media and telecom companies with premium advertising, needed to make their personalized services profitable.

The platform of the invention includes a central database of product and retail information and holistic consumer profiles, generated by a consumer profile generator based on the historical purchasing preferences and habits of each consumer. The holistic consumer profiles are preferably constructed by registering or recording the information consumers retrieve from the central product and retail information database, as determined by parsing log files of the consumer's online behavior as well as by capturing purchases made both on-line and in-store, using a loyalty card. The central product and retail information database is preferably independently fed and managed by each participating manufacturer and retailer. The central product and retail information databases may be accessed by consumers independent of the portal site that they are using for their shopping activities. The information retrieved from these databases is sent to the consumer in a portal specific presentation format with special slots for including customized advertising messages as well as the brand name of the portal that is providing the service to the consumer.

The holistic consumer profiles are created by capturing consumer purchase behavior and preferences for the largest possible range of product brands, categories, and retailers. The holistic purchase-behavior specific consumer profiles allow manufacturers and/or retailers to customize their product and category presentations to reflect an individual consumer's needs, independent of the portal that the consumer is using and independent of the retailer where the consumer is purchasing. The consumer profiles also allow manufacturers and/or retailers to reach their consumers, by placing consumer customized purchase-behavior specific advertising messages on the consumer's personalized interactive shopping and ad sponsored info, news and entertainment services. Advertisers may customize their advertising messages on these services to reflect individual consumer's purchase and shopping needs, independent of the portal that the consumer has been using and independent of the retailers where the consumer has been making purchases.

By sponsoring content delivery with premium, customized advertising messages, it is possible to decrease the consumer's price for such services. Consumer's receive such services in return for consumers accepting the advertising exposure as well as agreeing to the registration of their shopping and purchase behavior, in a way that provides consumers with full control over their profile data and that permits this data to be processed into aggregated retailer and portal independent consumer feedback information, that can be automatically processed and channelled back to manufacturers and/or retailers. The processing of data allows manufacturers and/or retailers to receive portal and retailer independent information about consumer's needs as well as information that permits manufacturers and/or retailers to benchmark their different product and/or category presentations and customized ad messages against each other, thus enabling them to evaluate the effectiveness of their communication programs, assortments and products.

The system of the invention allows portals to be compensated for their personalized content services and their customer databases. Portals may receive premium advertising revenues based on the amount of personalized ads that are being displayed on the portal's personalized information, news and entertainment services and in the advertising slots on the portal's personal shopping pages, that display the product and/or category presentations that the portal's consumers retrieve. In a preferred embodiment, the system of the present invention includes a central database system in electronic communication with a manufacturer, a retailer, and a portal. The central database system may include a product presentation database, a consumer profile database, a category presentation database, a product and category presentation server, an ad message database, an ad rate calculator, an ad server, a consumer profile processor, an order processor, and an effectiveness assessor processor. The ad server is preferably configured to transmit personalized purchase-behavior specific and/or context- sensitive advertisements in response to a request from the portal, consumer, or user of the system.

The product presentation database is populated with product information transmitted from the manufacturer, or retailer, to the central database system. Also, the category presentation database is populated with product information transmitted from the manufacturer or retailer to the central database system.

When determining when and what type of ad to serve, the ad server generates a personalized purchase-behavior specific or context-sensitive advertisement based on information stored in the consumer profile in the consumer profile database. Most often, the user or consumer using this system will be connected via a user terminal in electronic communication with the portal, or a distributed network such as the internet, enabling the personalized purchase-behavior specific or context-sensitive advertisement to be transmitted to the consumer. The process by which the present invention is useful for increasing the effectiveness of advertising effectiveness includes 1) collecting data for a consumer indicating online shopping information retrieval and online and offline purchasing history and preferences; 2) generating a consumer profile from the above data; 3) storing a plurality of advertisements in an ad database; 4) selecting an advertisement from the ad database based on the consumer profile; 5) serving the advertisement to the consumer via a distributed network; 6) monitoring the shopping and purchase behavior of the consumer after exposure to the advertisement; and 7) calculating the effectiveness of the advertisement based on consumer purchase behavior. Preferably, the process also includes updating the consumer profile after the consumer has been exposed to the advertisement.

In an alternative embodiment, the process by which the present system is useful for increasing the effectiveness of product and category presentations includes 1) uploading a product presentation or category presentation to a product/category presentation database; 2) storing a plurality of advertisements in an ad database; 3) selecting a product or category presentation from the product/category presentation database based on the consumer profile; 4) serving a product presentation or category presentation in a portal specific format to a plurality of online consumers; 5) selecting an advertisement from the ad database based on the consumer profile; 6) serving the advertisement to the consumer via a distributed network; 7) monitoring the shopping and purchase behavior of the consumer after exposure to the product presentation, category presentation and advertisement; and 8) calculating the effectiveness of the product presentation, category presentation and advertisement based on consumer purchase behavior. It is also desirable to update the consumer profile after the consumer has been exposed to the product presentation or category presentation.

In another embodiment of the system of this invention, there is a central standardized database, comprising product brand presentations and retail category presentations, wherein the product brand presentations and retail category presentations are uploaded and updated by a participating manufacturer or retailer, and a log file database including requests by consumers to access the product brand presentations and retail category presentations and the advertisement contacts to which the consumer has been exposed. The database may further comprise a holistic consumer profile, wherein the holistic consumer profile includes the consumer's historical shopping and purchase behavior and preferences.

The present invention is also useful as a system for serving consumer purchase- behavior specific online product and retailer content. The process by which this system is carried out is as follows: 1) creating a holistic user purchase behavior specific profile for a consumer; 2) determining, based on the holistic purchase behavior specific consumer profile, product and retailer content which most closely matches the preferences or needs of the consumer; and 3) serving the product and retailer content to the consumer in portal specific presentation format. Preferably, the product and retailer content is selected from advertisements, product presentations, and category presentations.

While in operation, the process by which the present system is carried out may also include any of the following, or combinations thereof: logging the consumer's shopping and purchase behavior response to the product and retailer content, updating the consumer's holistic purchase behavior profile, based on the consumer's response to the content, assessing the effectiveness of the content, based on the shopping and purchase behavior response of a plurality of consumers to the product and retailer content, transparently calculating advertising rates, based on the effectiveness of the product and retailer content to influence consumer purchasing behavior, and generating in-store traffic by providing the consumer with advertising and or promotional incentives to purchase a product via an online advertisement, product presentation, or category presentation; accepting online payment for the product; and delivering the product to the consumer at an offline retail store; forwarding advertising and or promotional incentives to consumers based on their holistic consumer profile, when the holistic consumer profile indicates that the consumer is more likely to purchase a product having a discounted price.

Brief Description of the Drawings

Figure 1 illustrates the central web services system of the present invention.

Figure 2 illustrates the interaction between manufacturers and the central system. Figures 3(a)-3(b) illustrate the retailer's interaction with the central system.

Figure 4 shows the portal configuration of the central system.

Figure 5 illustrates the consumer marketing of the portals personal interactive shopping and info/news/entertainment services.

Figures 6(a)-(c) illustrate various the subscription management process interaction between a consumer, a portal and the central system.

Figures 7 (a) - (e) illustrate the consumer shopping processes of the central web services system

Figures 8 (a) - (d) illustrate processing purchase orders that are delivered home to the consumer Figure 9 illustrates the processing of in-store purchases using the loyalty/benefit card

Figure 10 (a) - (e) illustrate processing purchase orders that are picked-up in-store by the consumer

Figure 11 (a) - (c) illustrate the systems functionality to serve advertisements on the interactive personal info, news and entertainment services of consumers. Figure 12 (a) - (c) illustrate the systems consumer 'target audience categorization and effectiveness evaluation run' as well as the consumer attitude collection and processing and the feedback information reporting to advertisers and retailers.

Detailed Description of the Invention

The present invention provides consumers, manufacturers, retailers and interactive media/telecom companies with interactive marketing communication/IT infrastructure services, and market intelligence, permitting the creation of personal consumer- customized shopping information and personalized purchase-behavior specific or context- sensitive advertising (see appendix I), resulting in effective, personalized interactive consumer communication and advertising campaigns, effective and cost efficient interactive retailer categories and electronic storefronts, and profitable, convenient interactive shopping and media services.

The present system relates to a web services system for consumer marketing communication, and shopping processes between consumers, manufacturers, retailers and media companies. The system provides tools for the integrated interaction of manufacturers, retailers, media companies and consumers, creating powerful efficiencies and network effects that streamline personalized interactive communication and transaction processes between consumers and retailers/manufacturers, while creating sustainable advertising revenue for media and telecom companies that enable them to offer free ad-based interactive entertainment and convenient shopping services to consumers. The present invention includes, but is not limited to, the following system modules:

The Personal Customization and Privacy Control Module This aspect of the invention personalizes the user's/consumer shopping, media, and advertising experience by means of a tool that captures individual consumer needs while providing privacy protection. The personal customization and privacy control module performs the following functions:

• Tracking personal shopping behavior/preferences and ad exposure with consumer consent. • Making the interactive user experience more convenient and relevant for consumers.

• Provides the consumer user with access to a personal portal branded shopping services.

• Providing portal branded personalized ad, news, and entertainment services. • Protecting user privacy by providing consumers with direct control over their personal profile data.

• Provides the consumer user with a benefit card, giving them access to special benefits and promotions, such as earning 'bonus points' on all their online and offline purchases at retailing members, and preferential access to special promotions of leading retailers and manufacturers.

Product Information & Ad Control Module

This aspect of the invention provides indirect sellers, such as manufacturers, with a tool for managing interactive consumer communications, allowing for the distribution of interactive product information and, also, for measuring its effectiveness. The product information and ad control module provides:

• Portal/retailer independent direct control and customization of product information. • Customization of Product Information to the shopping needs of special target audiences.

• Portal/retailer independent product information effectiveness measurement.

• A tool for delivering interactive personalized advertising and measuring its effectiveness. • Access to consumer profiles, to identify consumers shopping/purchase habits and needs.

• Ad targeting and delivery to narrow audiences, defined by consumer shopping behavior and needs.

• Serving advertisements ("Ads") while consumers are shopping or browsing news, entertainment, etc.

• A tool for measuring consumer feedback/purchases to assess advertising effectiveness. Category Information & Ad Control' Module

This aspect of the invention permits direct sellers of goods or services, such as retailers, to manage interactive storefronts, categories and consumer communication. Features provided by the category information and ad control module include: • Providing an infrastructure for managing fully interactive retailer storefronts, categories and consumer communication and payment, that may be integrated with retailer back-offices systems.

• Managing and customizing online retailer product categories. • Communicating and presenting retailer categories and advertisements to consumers.

• Directing online consumer traffic to offline stores, retail establishments, etc.

• Promoting online sales through offering consumers home delivery from a central warehouse, and dispatching from a central warehouse to a conveniently located store for pick-up by a purchaser.

• Measuring and benchmarking the effectiveness of online category presentation and advertising.

Product/Retail Category Information/Ad Server Module This aspect of the invention provides interactive portal operators with infrastructure for providing consumers with a differentiated portal specific interactive shopping services experience and advertisers with a portal independent ad planning, delivery and effectiveness measurement instrument. The product/retail category information/ad server module includes means for: • Providing the infrastructure that portals need to offer consumers a differentiated portal specific personal shopping experience and advertisers a portal independent ad planning, delivery and effectiveness measurement instrument. • Providing portal branded personal shopping service for consumers.

• Providing personal shopping service with a portal-specific user experience.

• Portal independent ad planning, delivery and effectiveness measurement, to generate ad revenue for deploying interactive services, e.g., portal-specific personal consumer shopping services and ad-sponsored interactive information and entertainment. In one embodiment of the invention, ad revenue is linked to the number of product/category presentations downloaded by consumers and the # of ads served with interactive shopping and info, news and entertainment services of each portal.

Market Intelligence

Besides information about manufacturer and retailer offers and sales promotions, the invention provides means for creating market intelligence from ad, product, and category database log files:

Portal/Retailer Independent Consumer Shopping/Purchase Habits and Preference

Intelligence

The system creates centrally stored portal/retail independent consumer shopping/purchase needs and preference information. Consumer profile data may, for example, characterize consumers as:

Heavy - Medium - Light Spenders

Necessity driven buyers vs. Joy/pleasure seeking shoppers

Frequent vs. occasional Shoppers

Prospects, buyers, etc., based on their propensity to effect a transaction.

Users - Non Users

Loyals - Switchers - Occasionals

Strongly Aware- Not Aware Shoppers

Highly Interested-Not interested Shoppers

Premium Quality vs. Basic Quality Shoppers

Wide vs. Narrow Brand Scope Shoppers

Wide vs. Narrow Retailer Scope Shoppers

Promotion vs. No-Promotion Shoppers

Bulk vs. Small Quantity Shoppers • Early Adopters vs. Laggards

The above characterization may be done on a category, product brand and retailer basis.

The consumer profile is the result of measuring the value of the shopping habits and need parameters for each consumer retailer/portal independent and then benchmarking these consumers against each other and categorizing them into groups with similar shopping habits/needs. The system allows to identify and target consumers based on their overall shopping habits and purchase needs. In this manner, the present invention is able to create a holistic, 360-degree perspective of the consumer's shopping and purchase habits, to aid in directing the most effective advertising, product and category presentations, and other consumer-specific services.

The system's market intelligence gathering and reporting features allow advertisers to customize on-line communication/ads and to more effectively target advertising, thereby increasing communication effectiveness and improving the financial return on their advertising investment, due to the increased likelihood of a consumer receiving advertisements that they find interesting, timely, or commensurate with their previous purchasing patterns.

Standard Overall Product Brand / Retailer Category Effectiveness Market Intelligence The system provides advertisers with standard effectiveness information on product brands/retailer categories that allows benchmarking of their performance against each other on the following market indicators:

Share

Penetration

Frequency

Loyalty

(Re)Purchase/Churn

Interest

Buyer/Shopper Profile

Communication Effectiveness

Advertising Impact and Exposure

Product Brand Distribution • Retailer Category Assortment

• Pricing

• Display Productivity

• Promotion Impact and Exposure

The effectiveness measurement is the result of registering the product/category retrieval, ad exposure and purchase history of each consumer, and processing this data into standard performance indicators, that allow performance benchmarking that is retailer/portal independent:

• Product Brand Performance is benchmarked vs. competitive brands.

• Retailer Performance is benchmarked vs. the average 'retailing format' peer performance.

(i.e. hypermarkets, department stores, catalog, supermarkets, drug stores, electronics, clothing, sports, toys, Book/CD/Nideo, DIY, Furniture,

Office).

The system's 'Market Intelligence' empowers manufacturers and retailers to continuously improve the market effectiveness of their on-line products and categories by measuring key performance indicators and benchmarking their Offers' against each other.

Standard Product/Category Presentation/ Ad/Promotion Effectiveness Market Intelligence

The system provides advertisers with standard consumer feedback information about the effect of brand/retailer category presentations, ads and promotions, on brand/retailer purchases and on the brand/retailer market performance indicators listed below:

Share

Consumer Purchases/Sales • Penetration

Frequency Loyalty

(Re)Purchase/Churn Interest • Buyer/Shopper Profile

• Communication Effectiveness

The effectiveness measurement is the result of registering the product/category retrieval, ad exposure and purchase history of each consumer and processing this data into standard impact indicators that allow for performance benchmarking that is retailer and portal independent. In one embodiment of the invention, the effectiveness of each brand/retailer category presentation is determined by measuring the impact of each presentation among those who have been exposed to it, measuring the impact of a presentation reference among a sample of (for example 100) reference consumers of the same audience, calculating the impact delta versus the reference (Score Pres.X / Score Pres.Ref * 100), and comparing the impact delta of the presentation vs. that of reference presentation.

Further, the effectiveness of each brand/retailer ad/promotion may, for example, be determined by measuring the impact of each ad/promo among those who have been exposed to it, measuring the impact of no ad/promo among a sample of (for example 100) reference consumers of the same audience, calculating the impact delta versus the Reference (Score Ad/Promo.X/Score.Ref.O * 100), and comparing the impact delta of the ad/promo vs. that of other/reference ads/promo's. The overall effectiveness of a presentation, advertisement or promotion is determined by calculating the average (avg.) and standard deviation (s) of the impact delta (d) of all presentations, advertisements and promotions and categorizing them into an impact delta (d) distribution range: (>75% range) (50%-75% range) (25%-50% range) «25% range) Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.- 25%*s)

The system's market intelligence enables advertisers to measure and benchmark the effectiveness of individual on-line communication/ad/promotion campaigns on consumer purchase behavior thereby making it possible to continuously increase their effectiveness and to focus investments behind the campaigns that generate the highest yield.

Specific definitions of consumer profiles, target audiences, performance indicators and algorithms are attached in Appendix π. By way of example, these definitions and algorithms demonstrate the type of market intelligence information that the system generates, as well as the manner in which it may be generated.

The heart of the operation of the present central manufacturer/retailer/portal independent system, is a central database system for product presentations, category presentations, advertisements and consumer profiles as well as central processing functionality that transforms on-line consumer shopping and purchase data, as well as offline purchase data, into: i) consumer profiles used for targeting and personalizing advertising information and customizing product and category presentations to the needs of individual consumers; ii) performance indicators used to measure the overall on-line market impact of product and category offers, allowing advertisers, manufacturers, or retailers to benchmark market performance, and iii) performance indicators that measure the effect of category and product presentations, ads and promotions on consumer sales and that allow to benchmark their effectiveness against each other.

The input data for the above transformation process that creates the earlier described market intelligence may include: i) the ad, brand presentation, or retailer category presentation database log files of the system; ii) the purchase log files from the system's order processor; and iii) purchase log files from the cashier system(s) of a retailer(s).

The present invention is generally carried out, based on the above described transformation process, on a central platform with 'standardized' manufacturer, retailer and portal independent definitions of consumer profiles, target audiences and performance indicators as well as standardized automated processes for measuring the effect of individual on-line marketing initiatives on consumer purchase behavior and for benchmarking them against each other. The positive impact of effectiveness measurement on advertising ROI is illustrated in example 1.

The central platform system, as shown in Figure 1, includes individual databases that store product presentation information, ad messages, category presentations, and consumer profiles. Further, the central database system includes means for processing data, i.e., software applications. Among the software applications present on the central database system will be an ad server, an ad rate calculator, a product and category content server, a consumer profiler, an order processor, and an effectiveness assessor.

The present system is applicable to the consumer receiving and displaying the data using a conventional web-browser via an internet connected PC or any type of electronic device (mobile phone, Mira displays, cable TV set-up box) connected to any type of mobile, distributed or local network using any type of transmission protocol.

The ad server

The aspect of the invention is included to deliver ads to target audiences, defined by shopping behavior/needs of individual consumers, i.e., the consumer profile. Ads are served as consumers are shopping/researching, browsing stores/products, or retrieving and reviewing news, information, consuming music, video, games or other type of entertainment services provided via a portal.

The ad message database

This feature of the present invention is used by each participating advertiser to upload advertising campaign data, such as ad message, campaign timings, target audience, frequency and reach objectives, or other information necessary to convey the purpose and effect of the advertisers goals. Further, the ad message database may be used by each participating advertiser to get effectiveness measurement data that may include performance indicators measuring the ad's impact on consumer's shopping behavior, benchmarking data for comparing the ads performance against that of other ads, and/or measurement standards for assessing advertising effectiveness. Performance benchmarking is, therefore, possible in a portal independent manner.

Product & Category Presentation Server

This server searches the central product and retail information databases for shopping information requested by a consumer and serves it in a customized and a portal specific presentation format.

Product Presentation Database

Used by each participating manufacturer to control/customize its presentations. Features which may be customized include, without limitation, specification of product presentation, target audience, and exposure timings. The product presentation database may be used by participating retailers to access and provide up-to-date product presentations, by participating portals to obtain the product presentation for consumers, by participating consumers to get up-to-date product presentations, and/or by each participating manufacturer to get effectiveness measurement data, such as indicators on the presentation's impact on consumer's shopping behavior, benchmarking data for comparing the performance of presentations against each other, or measurement standards for assessing presentations portal and retailer independent.

Retailer Category Presentation Database

This database is used by participating retailers to create/manage retailer category presentations. A retailer category presentation may include a specification of retailer category item composition and presentation format. The retailer category presentation database permits the retailer to access and provide up-to-date product presentations and to regularly update of pricing data and inventory data. This feature may be used by each participating retailer to control/customize its presentations, upload category presentations, preferred target audience, and exposure timings. Moreover, this database may be used by each participating portal to obtain retailer information for consumers, by consumers to get up-to-date retailer information, by participating retailers to get effectiveness measurement data, such as indicators of a category's impact on consumer's shopping behavior, benchmarking data for comparing the performance of categories against each other, and/or measurement standards for assessing category performance in a portal and retailer independent manner.

Consumer Profiler

The consumer profile creates comprehensive, i.e., "holistic purchase-behavior specific", profiles of consumers by tracking individual consumer advertising exposure history and shopping, purchase behavior and preferences across multiple retailer categories, product brands and portals. In a preferred embodiment of the invention, explicit consumer consent is required for such detailed monitoring of the consumer's browsing, purchasing, and other online behavior.

Consumer Profile Database

This database contains consumer ad exposure, product/category retrieval and purchase history, usually in the form of a consumer profile, used to customize product/category presentations and target/serve ads. The database can be accessed by the consumer to change/delete a profile.

Order Processor A processor for consumer orders, loyalty points, confirmations, payments and delivery messages.

Effectiveness Assessor

The effectiveness assessor provides advertisers with a significant advantage over prior art systems for serving online advertising, by providing a means for gauging the effectiveness of certain ad campaigns, product presentations, etc. The effectiveness assessor registers historical consumer product/category retrieval, purchase and ad exposure data and processes it into standard product/category presentation/advertising effectiveness measurement data, making it possible to assess the impact of advertising, product/retailer presentations, promotions and other factors on the shopping behavior of consumers. Further, the effectiveness assessor permits benchmarking of the effectiveness of product/category presentations and ads against each other.

Ad Rate Calculator The ad rate calculator dynamically and transparently (from both the advertisers and the media company perspective) calculates ad rates based on the target audience of the campaign and the advertising's impact on the purchase behavior of consumers. To objectively reflect any factual performance differences fairly in its ad rate pricing, the system measures the effectiveness of each contact, benchmarks it against the effectiveness of a reference or mass advertising contact and automatically incorporates the performance difference in the ad pricing.

The product presentation database is filled with product presentation data that is uploaded by manufacturers of goods, providers of services and retailers in the case of retailer branded private-label products. Manufacturers, for example, may submit presentation information for each of its products to the product presentation database and may update that information over time, as their product line, product availability, or specific product specifications may change. Further, the manufacturer will populate the ad messages database with advertisements to be delivered to a specific consumer target audience, based on purchase-based profile criteria and/or consumer audience that the advertiser wants to reach with his advertising message. This process is illustrated in more detail in Figure 2 which shows that the manufacturer will define target audiences and will develop product presentations and ad messages specifically designed to appeal to members of the target audience. The return on investment ("ROI") benefits of customizing advertising messages to the shopping needs of different consumers is illustrated in example 2. The ad messages are forwarded to the central database system and stored in the ad message database. The product presentations are forwarded to the central database system and stored in the product presentation database. The system allows advertisers to reach consumers with different types of advertising contacts. Consumers can be contacted substantially anywhere or at anytime, i.e., in the consumer's home via a PC or cable TN/Mira system, in the office via a PC, or when traveling with a mobile device. Consumers can be reached as they are shopping/researching stores/products via their portal personal shopping services and as they are consuming the personal interactive info/news/entertainment of their portal. An overview of the contextual advertising contact possibilities can be found in Appendix I. For each advertising campaign the Ad Rate Calculator of the present system dynamically and transparently calculates ad rates ( a price per 1000 advertisement contacts that is completely transparent to both buyers and sellers of advertisements), based on the target audience of the campaign and the advertising contact's impact on the purchase behavior of consumers. To objectively reflect any 'factual' performance differences 'fairly' in its ad rate pricing, the system measures the effectiveness of each ad contact, benchmarks it against the effectiveness of a reference or mass advertising, and automatically reflects the performance difference in its pricing. The process is based on algorithms described in detail in Appendix III.

Further, this process transforms ad serving and purchasing history (stored in log files) into standard performance indicators and benchmarks them against the mass advertising performance references that are measured following the same measurement methodology. The ad rate calculation algorithm starts with the cost of reaching the target audience via mass advertising, discounts this price with a 'Target Bonus' of x %, corrects it with any advertising effectiveness performance difference between the system's advertising and mass advertising and finally with a 'Pricing Differentiation Index' that allows each interactive personal service provide to keep independent control over their pricing policy. With the proper parameter settings, the system will improve ROI for advertisers while creating premium advertising revenues required to develop profitable media services. This is shown by the illustrations in Appendix III.

Once the advertiser has received the ad rate pricing information, the advertiser will finalize the campaign booking by providing campaign specific timing and frequency information, and by confirming the advertising order that specifies the advertising space purchased, as well as its price. Similar to the process that occurs with manufacturers, retailers can create definitions of target audiences and create ad messages and category presentations custom- tailored to individual consumers, as shown in figure 3a. The retailer's ad messages and category presentations, that are determined by their product item assortment, presentation format and pricing definitions, are stored in their respective databases in the central database system. Moreover, the category presentations stored in the category presentation database may reference information in other databases, such as the product presentation database, permitting the retailer to define categories that include certain types of products and allowing the central database system to filter the records stored in the product presentation database for products meeting the criteria for the retailer's category definition. Retailers may manually define the products to be shown in accordance with their defined category definitions, or preferably the central database system will automatically create categories for the retailer based upon category definition and product presentation data uploaded to the central database system by manufacturers. The systems capability to send different ad messages to different target audiences is also the basis for the system's in-store traffic generator feature that streamlines current offline retailer store traffic generation programs that advertise weekly price features equally strong to price sensitive switchers as to loyal consumers that buy at the retailer independent of the weekly price features. The present system can aggressively drive online awareness of weekly specials among price sensitive occasional consumers and to also improve profit margins by keeping the communication of the weekly specials low among loyal consumers that buy products independently of whether they are offered at a discounted price. The system may allow price sensitive occasional shoppers to buy these weekly specials on-line at special discounted prices and to pick them up in-store while pricing all in-store items at their normal shelf prices. The ROI benefits for the retailer are illustrated in examples 3(a) and 3(b) on page x.

As shown in Figure 3b, another feature of the retailer aspect of the present system are its distribution center assignment and product stock monitoring functions. These functions permit the retailer to assign the closest distribution center to the consumer, in order to minimize shipping costs and delivery times. The present system also permits retailers to select the closest distribution center to the consumer with the selected product in-stock. The present system may further permit the retailer to send out-of-stock messages from its inventory management systems to the present system and to make sure that the out-of-stock information is automatically reflected in the retailers category presentations that the consumer consults when buying products.

Although only a single manufacturer/retailer is shown in the drawing figures 2 and 3(a) and 3(b), it should be understood that the central database system of the present invention may accept data from a multiple manufacturers/retailers in the same way as here described.

The present invention enhances the functionality of portals by providing shopping/ad services for deploying profitable interactive services. It provides the infrastructure that portals need to offer consumers a differentiated portal-specific personal shopping experience and advertisers with a portal-independent ad planning, delivery, and effectiveness measurement instrument.

Portals employing the present invention get a portal-branded personal shopping tool, with access to the latest up-to-date manufacturer and retailer product/category information stored in the central database, that can provide a distinctive, portal-specific user experience which differentiates one portal from that of competitive portals. To configure the portal-specific experience, portals may create templates that define a portal- specific format in which all product/category information will be sent to the consumer. This personal shopping tool allows the portal's consumers to quickly find product/retailer and consumer feedback information as well as to conveniently (re)order on one platform without having to (re)type in their needs on a multitude of retail, portal and manufacturing websites. It also provides the portal's consumers with a system to control their shopping profiles as well as a loyalty/benefit card that may be portal branded.

Further, the portal may adopt the system's consumer profiling, ad serving, and effectiveness measurement tool that is portal and retailer independent, eliminating an important usage barrier for advertisers. The system makes the management of personalized ads less complex and more manageable. For advertisers, it avoids the need to manage a multitude of different, non-standard portal consumer profiling and effectiveness measurement systems, which make prior art methods of personalized ad management and measurement processes very complicated and inefficient. The system's personalized ad-planning tool further allows to plan personal ad campaigns based on GRP (Gross Rating Points - an industry accepted measure for the # of ad contacts), reach, frequency objectives and Cost/ 1000 rates that are completely transparent to buyers and sellers of advertisements. In contrast to prior art systems in which portal pay 'mass' ad prices for their advertising space, the present system's unique portal/retailer independent profiling/effectiveness measurement capabilities permits portals to charge advertisers premium ad rates that are justified by the system's unique capabilities to deliver a higher ROI for advertisers, i.e. capabilities that make it more cost-efficient to reach specific narrow target audiences, to adapt advertisements to the needs/behavior of individual target audiences, and to measure the effect of ads on sales, allowing advertisers to focus investments on high yield ads. The consumer profiling, ad serving and effectiveness measurement tool that is portal and retailer independent thus permits portals to deploy profitable personal interactive news/entertainment services and telco/cable companies to recoup their investments in broadband and 3G infrastructure with ad sponsored info/news/entertainment services.

As shown in figure 4, at least one, and preferably many, web portals may be in communication with the central web services system. Portals will have to configure the portal specific formats in which product/category data and ads from the central web services system will be sent to consumers. The portals may include their own news and content generation and delivery functions, or may obtain these services from other content-generation and delivery services (not shown). The portal may obtain product and category data from the central database system's product and category content server, customize the data with the portal's own brand (or co-brand the data to include the brand of a manufacturer or retailer) and provide a user with an integrated, convenient shopping experience without requiring the user to leave the portal website. Further, based on the profile of the consumer stored in the central database system, personal preferences input by the user, the portal site may adapt the personalized news and entertainment content for the consumer.

Figure 5, shows the marketing communication between a portal site and a consumer for the purpose of initiating a consumer subscription to the services offered by the portal site. The present invention requires interaction with a consumer, so that a profile for the consumer can be established. The profile for the consumer is then used for the purpose of generating personalized services for the consumer. Figures 6(a), 6(b) show the processes that may occur for a typical consumer, e.g., the creation of a subscription to use a particular portal (upon which consumers are provided with a benefit card), and the entering and changing of information concerning the user's preferences, i.e., subscriber settings. Once the user has activated their services with a portal, the central database system may create a unique profile file for that consumer, to track the consumer's shopping behavior and preferences across multiple retailer categories, multiple product brands, and/or multiple portals. The user may now begin receiving portal-branded personal shopping and info/news/entertainment services. Fig 6 (c) shows how the consumer profile file that tracks the consumer behavior in the central database system is deleted once the consumer decides to terminate his subscription.

The standardized holistic purchase-behavior specific profiling system, that tracks a consumer purchase behavior and preferences across multiple retailers categories and manufacturers product brands as well as multiple portals is updated to provide each consumer with the most relevant, personalized advertisements. The system also makes consumer's shopping sessions more productive and relevant, thereby increasing the likelihood that they will purchase a product, and improving the convenience of placing repurchase and replenishment orders. The portal-branded personal shopping tool may also allow consumers to consult peer consumer rating and opinions on products and retailers. Additionally, the present invention provides consumers with a convenient portal-branded privacy shopping tool that permits them to have control over their profiles, i.e., giving the consumer the possibility of deleting or changing their personal profiles, asking consumers for permission to collect profiles and consumer feedback, and rewarding them financially for this data with free personalized ad-sponsored info, news, music and entertainment services. The extensiveness and value of the personalized ad- sponsored info, news, music and entertainment services may dependent on the consumer usage of the portal-branded shopping tool. The operation of the reward system can be compared with that of an activity based loyalty point system. To be able to capture consumers in-store purchases each consumer is provided with a benefit card that provides members with access to special benefits and promotions. The card allows consumers to earn bonus points for free portal-branded personalized digital info, news and entertainment, on all their on-line and offline purchases at retailing members, and provides card holders with unique preferential access to special promotions of participating retailers and manufacturers.

In a typical on-line shopping session shown in figures 7 (a)-(e), the consumer logs into the interactive personal shopping service of his portal upon which the central system is activated. The consumer then makes a request for manufacturer product and or retailer category information. This information can either be a complete retailer store front, or advertising information stored in the portal's 'retailer specials' and/or product registry. As indicated in appendix I, the portal's 'retailer specials' and/or 'product registry' works like a directory, allowing manufacturers to describe their products to consumers and retailers to describe their weekly special offers. The consumer requested information is fetched in the databases of the central system together with advertisements that fit the specific profile criteria of the consumer. The system then activates a template that defines the portal specific format in which the information will be forwarded to the consumer. The system creates an empty delivery page that is branded with the name of the portal. The product & category server of the present system fills the 'empty info section' on the page with the requested information and the ad server fills the 'empty ad slot' on the page with the earlier fetched consumer specific advertisement upon which the 'delivery page' is forwarded to the consumer. The process ends with the consumer profiler, effectiveness assessor and the systems ad, product presentation and category presentation databases receiving log file messages specifying the advertisements, the product and retailer specials registry information, the product presentations, the category presentations as well as the consumer ID and the exposure date of the information transmitted.

The consumer generally will be in communication with the present system via a user terminal connected to the internet or other distributed network. Each time a user makes a selection during the shopping process, the consumer profile processor is notified, so that it may update the consumer profile database. Further, the effectiveness assessor processor receives notification of the product and category information retrieved by the consumer and updates the product and category presentation databases. The effectiveness assessor processor also receives notification of the advertisements to which the consumer has been exposed and updates the ad message database.

When a consumer places an on-line order, the present system may provide the ability to process the customer's order, including processing payment, providing order confirmation to the buyer, and notifying the retailer's order fulfilment processing means, as shown in figures 8(a), 8(b), 8(d). Further, as shown in figure 8(c), the consumer profile processor may be notified of the purchase and pertinent information is processed by the consumer profile process to update the consumer's profile database, the advertising and the product and category presentation databases. Such pertinent information may include the item selected for purchase, the retailer, the category, quantity, price, the consumer's identity, date of purchase, price, etc. This data may also be transmitted to the effectiveness assessor processor. The effectiveness assessor process may use it to update the product and category presentation database and to generate statistics that are helpful to the manufacturer, retailer, and portal operator. The present system may also process offline consumer purchase data of in-store purchases that were effectuated scanning the system's benefit card at the retailer's cashier system, as shown in figure 9. In this case, the system's consumer profiler processes an in-store purchase log file (specifying the retailer, the consumer ID, the purchased items, the quantity purchased, the price and the date of purchase, etc.), received electronically from the retailer, and updates the consumer's profile database, the advertising and the product and category presentation databases as previously described. When a consumer places an on-line order, that the consumer will pick-up in-store, the present system may again provide the ability to process the customer's order, including processing payment, providing order confirmation to the user, and notifying the retailer's order fulfilment processing means. The system may also notify the retailer cashier system of the pre-paid order placed. This is shown in figures 10(a), 10(b). Further, the consumer profile processor may be notified of the purchase and pertinent information is processed by the consumer profile process to update the consumer's profile database, the advertising and the product and category presentation databases as previously described . When the consumer goes to the store to pick up the pre-paid merchandise as well as any other items that he might decide to buy, he identifies himself with his benefit card at the cashier, as shown in figure 10(c). The merchandise and the benefit card are scanned and cashier system accesses the pre-paid order file of the card holder and deducts the pre-paid amount from the bill, upon which the balance is paid, as shown in figure 10(d). Further, as shown in figure 10(e), the consumer profile processor may be notified electronically by the retailer of the purchase and pertinent information is processed by the consumer profile process to update the consumer's profile database, the advertising and the product and category presentation databases as previously described. The present system is applicable to the consumer receiving and displaying shopping data using a conventional web-browser via an internet connected PC or any type of electronic device (mobile phone, Mira displays, cable TV set-up box) connected to any type of mobile, distributed or local network using any type of transmission protocol.

In a typical online info/news/entertainment consumption session, shown in figures 11 (a)-(c), the consumer logs into the interactive info/news/entertainment service of his portal upon which the consumer id number is forwarded to the central system. The system is activated, retrieves the ads that are relevant for this consumer and this info/news/entertainment session and sends the consumer specific ads to the portal content server, that inserts the ads in the appropriate portal branded personal info/news/entertainment services ad slots. Alternatively, the system may also send the ads directly to terminal of the consumer where they are inserted into the info/news page as a 'print ad', into a media player that is used for playing audio or video clip tracks as a 'radio' or 'TV ad' or any software application that the consumer is using for playing interactive games. The process ends with the system's consumer profiler, effectiveness assessor, and ad database receiving a log file message specifying the advertisement, as well as the consumer ID and the exposure date of the advertisement transmitted.

The present system is applicable to the consumer receiving and displaying advertisements using a conventional web-browser via an internet connected PC or any type of electronic device (mobile phone, Mira displays, cable TV set-up box) connected to any type of mobile, distributed or local network using any type of transmission protocol.

In a daily consumer 'Target Audience Categorization and Effectiveness Evaluation Benchmarking Run' (a 'batch' operation), that is illustrated in figure 12(a), the central system measures the value of each consumer profile parameter and benchmarks each consumer against each other, categorizing them into groups with similar shopping habits/needs. The system reviews the daily product/category retrieval, ad exposure and purchase history of each consumer with the objective of assigning consumers to specific target audiences with common identical shopping/purchase habits/needs in a way that is retailer and portal independent ( e.g. prospects, users/non-users, loyal users/shoppers, etc.) so that these daily updated target audiences can be used as the basis for targeting and customizing advertising messages and product/category information. In the same operation, the central system may process the database log data files, to generate updated consumer feedback on manufacturer and retailer product/category presentations and personalized ad campaigns retailers that allows to benchmark the different product/category presentations and personalized ad messages against each other, allowing the evaluation of the effectiveness of marketing programs, assortments and products.

Specific details and algorithms which, by way of example, demonstrate how the effectiveness assessor processor may operate are included in attached Appendix II, which is hereby incoφorated by reference.

The system may also periodically create consumer attitude assessment data on manufacturer brands, and retailers' portals' interactive services, as shown in figure 12b. The system may send electronic evaluation questionnaires to an attitude panel of representative consumers. The consumers of this panel fill in the questionnaires and return them electronically. The attitudes on the products, retailers and interactive services are processed. As illustrated by figure 12(c), all the market intelligence about products, retailers and advertisements can be accessed on-line on via a web services extranet, to which marketing and category managers of the member companies have access with their password.

Example 1

The positive impact of the effectiveness measurement capability on ROI Previously, manufacturers and retailers who spent money on advertisements could only gauge the effectiveness of their advertising expenses by comparing their gross sales to periods before, during, and/or after the advertising campaign was initiated. Using the present system, the effectiveness assessor process can provide retailers and manufacturers with real-time analysis of the value of the advertising expenses. In today's 'mass' media world it is extremely difficult and expensive to measure the impact of advertising on actual consumer sales. The most accurate measuring method, is through a consumer panel test, where consumers' TV programs are interrupted by special 'split cable' test advertising blocks and where consumers' purchases are monitored through the scanners of the consumer's supermarkets. The technique requires months of preparation and is very expensive. The method is, therefore, used in a minority of cases (less then 1% of all ads aired). More frequently, less sophisticated and expensive research techniques are used. These testing methods are less reliable, as they cannot measure the impact of advertising on actual consumer sales. In practice, many advertisers will base their 'airing' decision on the 'qualitative' input of a couple of focus group consumers. Without a proper testing method that measures the impact of the advertisement on consumer sales, it is extremely difficult to distinguish the 'ads that sell' from the 'ads that do not sell'. The present system can help improve advertising ROI in a major way: advertising impact on sales can be measured almost instantly and for free. This has major consequences for advertisers, because they can easily distinguish the 'ads that sell' from the 'ads that do not sell' and can make sure that they put their money into the ads that have a proven pedigree, thereby significantly boosting the return on their invested advertising dollar. The invention is further illustrated, but not limited, by way of the following examples.

Advertiser A develops three spot alternatives (al,a2,a3), each with a random effectiveness (5%, 15% and 1%) that is difficult to predict and unknown before testing. To find out which spot is the best the advertiser uses Iawai.net and selects the spot with the highest impact on sales. He finds out that this is spot a2 with a 15% share growth impact on sales. Without the present invention, the advertiser would not have been able to identify the 'best selling' spot. He would have selected spot (a), believing that it would deliver a 'random' 10% share growth impact. The measurement capabilities of the present system show 5 ppts. additional share growth, which can be translated into a 50% additional ROI.

Advertiser B develops three spot alternatives (M,b2,b3,b4,b5), each with a random effectiveness (5%, 10%,20%, 15% and 15%) that is difficult to predict and unknown before testing. To find out which spot is the best the advertiser uses data generated by the effectiveness assessor feature of the present system and selects the spot with the highest impact on sales. He finds out that this is spot b3 with a 20% share growth impact on sales. Without the effectiveness assessor processor, the advertiser would not have been able to identify the 'best selling' spot. He would have selected spot (b), that would have delivered a 'random' 11% share growth impact. The measurement capabilities of effectiveness assessor generator, in this case, deliver 9 ppts. additional share growth, which can be translated into a 82% additional ROI.

The share increases of the different campaigns A and B are weighted with the media weight, that is put behind the campaigns and then added. The result is the

Performance Index for both the advertising made in accordance with the present invention and the 'mass' advertising and an ROI effectiveness factor of 1.70, i.e. advertising according to the present invention that is providing a 70% higher ROI than 'mass' advertising. The effectiveness assessor processor makes it possible for advertisers to filter out ineffective ads and to focus advertising investments exclusively on 'high yield' ads, as illustrated in the following table:

Table 1

Example 2

The positive advertising ROI impact of customization of advertising messages to narrow consumer groups defined bv their shopping behavior/needs

In the below example it is illustrated how Iawai.net 'Personalized' advertising consisting of 4 more relevant 'personalized' ads ('easy usage!', 'try us ! ', 'brand x is ..', we're new !') targeted at 4 different target groups ('brand users', 'interested non-users', 'non-aware', 'un-impressed') could improve the advertising ROI for advertisers versus 'mass' advertising, consisting of one 'generic' ad (we're it!), that is a less relevant compromise 'message', that treats all consumers as being equal.

Brand Interested Non- Un- Brand Interested Non- unusers Non-users aware impressed users Non-users aware impressed Example 3

The positive impact of the shopper specific differentiated in-store traffic generation capability on ROI for retailers The system's capability to sent different ad messages to different target audiences 5 is also the basis for the system's 'in-store traffic generator' application software functionality that drives the inefficiency out of current offline store traffic generation programs that advertise weekly 'price features' equally strong to 'price sensitive switchers' as to 'loyal consumers that buy at the retailer independent of the weekly 'price features". The 'in-store traffic generator' allows to aggressively drive the on-line 10 awareness of 'weekly specials' among 'price sensitive occasional' consumers and to simultaneously improve profit margins by keeping the communication of the 'weekly specials' low among loyal consumers that buy products independently of whether they are 'on feature'. The in-store traffic generator allows 'price sensitive occasional shoppers' to buy these 'weekly specials' on-line at special discounted prices and to pick them up in- 15 store while pricing all in-store items at their normal shelf prices. With the in-store traffic generator' the retailer benefits by discounting only to those consumers that are sensitive to discounting instead of discounting to everybody. The overall 'in-store traffic generator' process works as follows: 1) The retailers places the 'Weekly Specials' in the 'Retailer Specials' Registry. 20 2) The retailer places special 'weekly specials' announcement advertising on the interactive personal shopping and news/entertainment services of 'price sensitive occasional' shoppers only.

3) The 'price sensitive occasional' shoppers goes to the 'Retailer Specials' Registry, buys 25 the

'Specials' at a discounted price and pre-pays by credit card.

4) The pre-paid order of the 'Specials' is forwarded to the Retailer Order Information System and a copy of the pre-paid order file is forwarded to the cashier system of the retailer. 30 5) The consumer goes to the store to pick up the pre-paid merchandise as well as any other items that he might decide to buy now that he is in-store anyway. 6) The consumer goes to the cashier and identifies himself with his iawai.net benefit/ID- card, the cashier scans the merchandise and the benefit/id-card and cashier system accesses the pre-paid order file of the iawai.net card holder and deducts the pre-paid amount from the bill, upon which the consumer pays the balance and takes his merchandise home.

The below tables illustrate the 'Store Traffic Generation/Featuring' Cost/ROI gains, that retailers can realize through Iawai.net's 'personalized store traffic generation'

10 process.

In the below example Iawai.net increases the return for a 'electronics retailer' 2.5 times

Appendix I

Overview of different Contextual Advertising Messages

Iawai.net Advertising Messages:

- Consumer Consultation of Manufacturer 'Product Info' in Portal Shopping Registry

- Consumer Consultation of Retailer 'Weekly Specials' in Portal Shopping Registry

- Consumer Ad Exposure in a Personal Digital News/Music/Video on Demand Service

- Consumer Ad Exposure in a Personal Shopping Service

Overview of different type ofIawai.net Advertising Messages

Iawai.net provides four different advertising contacts: i) A Consumer Consultation of Manufacturer 'Product Info' in Portal Shopping Registry

This is a 'pull' (i.e. consumer initiated) contact, initiated by 'interested' consumers, that are new to a category, are unhappy with a brand or interested in the latest 'product' developments. Because the contact is initiated by the consumer one can assume that its effect on sales is higher than that of a classical mass 'push' ad message (i.e. initiated by the advertiser). ii) A Consumer Consultation of 'Retailer Specials' in Portal Shopping Registry This is a 'pull' (i.e. consumer initiated) contact, initiated by consumers that are 'interested' in the weekly or monthly 'Retailer Specials' and that like to research where they can get the best 'value- for-money'. It is a contact that is important because it can potentially drive store traffic and retail sales in a very cost efficient way. Because the contact is initiated by the consumer it can be assumed that its effect on sales is higher than that of a classical mass 'push' ad message. iii) A Consumer Ad Exposure in a Personal Digital News/Music/Nideo-on-Demand Service

This is a 'push' (i.e. advertiser initiated) contact. The ads are served while consumers are consuming their personal digital news articles or their digital music, video-on-demand or interactive games. The advertising format depends on the type of Personal Digital News/Entertainment Service:

- Personal Digital News Services: 'Print Ad' Format incorporated in the news articles

- Personal Digital Music Services: 'Audio Ad' Format incorporated as 'radio-like ad block'

- Personal Digital VOD Services: 'Video Ad' Format before each Video/Clip as a 'TV-like ad'

- (Personal Digital Game Services: 'Sponsor Banner' Format as is common in sport sponsoring Personal Digital Info Services (weather, route, stock market info): 'Print/Banner Ad' Format)

Because Iawai.net ads can be personalized and targeted to consumers based on holistic purchase based shopping profiles and because its effect on sales can be measured continuously and instantaneously, it can be assumed that the effect on sales of a Iawai.net 'push' ad message is higher than that of a classical generic mass 'push' ad message, that is addressed to 'random' consumers. iv) A Consumer Ad Exposure in a Personal Shopping Service

This is a 'push' (i.e. advertiser initiated) contact. The ads are served while consumers are shopping or researching stores/products via their personal digital portal 'shopping services'

The advertising that is served to consumers as they are shopping in their personal digital portal 'shopping service' will be mostly in the 'Print Ad' and 'Banner' Ad Formats. Because Iawai.net ads can be personalized and targeted to consumers based on holistic purchase based shopping profiles, because these ad can be served as consumers are busy shopping/researching stores/products via their personal digital portal 'shopping services' and finally because its effect on sales can be measured continuously and instantaneously, it can be assumed that the effect on sales of this type ofIawai.net 'push' ad message is higher than that of a classical generic mass 'push' ad message, which is addressed to consumers at a moment when they are not involved with shopping. Appendix II

Consumer Profiles,

Target Audiences and Performance Indicators

Section I:

Consumer Profile Data & Segments & Target Audiences

Section II: Performance Indicators for Manufacturers

Section III: Performance Indicators for Retailers

Section I: Consumer Profile Data & Segments & Target Audiences

1. General;

- Definition of Consumer Shopping Act Log - Definition of Consumer Ad/Promo Exposure Log

2. Category Specific Consumer Shopping Information:

- General Category Specific Information

- Definition of Consumer Profile Parameters

- Definition of Consumer Segments & Target Audiences

3. Brand Specific Consumer Shopping Information:

- Definition of Consumer Profile Parameters

- Definition of Consumer Segments & Target Audiences

4. Category Specific Consumer Shopping Information:

- Definition of Consumer Profile Parameters

- Definition of Consumer Segments & Target Audiences

1. General:

Definition of Consumer Shopping Act Log:

Shopping Event: Event when consumer purchases and/or researches product/retailer A Shopping Event consists of multiple product/retailer shopping acts.

Shopping Act Types: Research Act (no purchase) or Purchase Act (purchase) Research Act: Category, Presentation, SKU, Retailer, Consumer, Duration, Date Purchase Act: Category, Presentation, SKU, Qty, Price, Retailer, Consumer, Duration, Date

The above Consumer Shopping Logs will be processed into Consumer Purchase Profile & Brand/Retailer Performance Data according to the parameter definitions outlined in this document.

The profile & performance data is processed the same way for all product categories.

Definition of Consumer Ad/Promo Exposure Log:

Ad Exposure Event: Event when consumer is exposed to an ad/promo

Ad Types: Shopping Ad/Promo (served when busy shopping)

Entertainment/News Ad/Promo (served when exposed to music/news) Shopping Ad/Promo Exposure: Ad, Category, Brand/Retailer, Consumer, Date

Entertainment/News Ad Exposure: Ad, Category, Brand/Retailer, Consumer, Date

The above Consumer Ad/Promo Exposure Logs will be processed into Consumer Purchase Profile & Brand/Retailer Performance Data according to the parameter definitions outlined in this document. The profile & performance data is processed the same way for all product categories. 2. Category Specific Consumer Shopping Information:

Overall Category Data:

Category Purchase Volumes (% distribution by SKU product item - Pareto analysis) Category Interest Index (% of consumers that have researched the category in PxM) Category Penetration Index (% of consumers who purchased the category in PxM) Category Purchase Frequency (# category purchase events per year)

Category Shopping Frequency (# of category shopping events per year) Average basket sales (basket sales per purchase event)

Category Needs:

a) Service Oriented Needs

- Purchase Impulse (Shopping Duration/Shopping Events/Brand Scope/ Retailer Scope/purch. incl.)

- Sales Productivity (Category Spending/Shopping Duration)

- Purchase Inclination (# of shopping events with purchase/total # of shopping events made) b) Assortment Oriented Needs Category Brand Scope (avg. # of different brand/sku presentations accessed per shopping event) c) Price Oriented

Promotion Sensitiveness/Responsiveness (category volume with promotional price/category volume) d) Innovation Oriented Needs

Innovation Sensitiveness/Responsiveness (avg. time since product launch of product presentations accessed by the consumer) Algorithm Remarks:

■ PxM (= Past x Months, e.g. Past 3 Months - x can be either 1,3,6 or 12 Months)

■ avg. spending = average spending

• s = standard deviation of an average x that is assumed to have a 'standard deviation')

• 75% chance spending interval = average consumer spending +/- 25%*s

75% of the consumers have an average spending that lies in the 75% chance spending interval heavy spender = a consumer that has an average spending that lies above the 75% interval medium spender = a consumer that has an average spending that lies in the 75% spending interval light spender = a consumer that has an average spending that lies below the 75% spending interval

smal + 25%*s Then:

er

2. Category Specific Consumer Shopping Information:

Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Category Volume in PxM/c: ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Category Spending in PxM/c: heavy spender (> avg.spending+25%*s)

((x = (c+0.25*s) avg. purch. freq.) medium spender (avg.spending+/-25%*s) with c= # of purchase cycles) light spender (< avg.spending-25%*s) non-user (0%)

Last Category Research Date in PxM: prospect (x = 1.25*s* avg. purch. freq.) Last Category Purchase Date in PxM: user (x = 1.25*s* avg. purch. freq.) Time since last category purchase: suspect ( > -0.25*s* avg. purch. freq.) attritor ( > 1.25 *s* avg. purch. freq.)

Shopping Frequency in PxM/c: frequent shopper (>avg.purch.freq.+25%*s) ((x = (c+0.25*s) avg. purch. freq.) regular shopper (avg. purch.freq. +/-25%*s) with c= # of purchase cycles) infrequent shopper (avg.purch.freq -25%*s)

Purchase Impulse in PxM/c: high: long (re)search time needed to buy (Shopping Duration / Shopping Events / (>avg. purchase impulse +25%*s) Brand Scope / Retailer Scope / purch. incl.) medium: avg. (re) search time to buy ((x = (c+0.25*s) avg. purch. freq.) (avg. purchase impulse +/-25%*s) with c= # of purchase cycles) low: short (re)search time needed to buy ["Purchase Rush - Research Intensity"] (<avg. purchase impulse -25%*s) NA: no purchase act

Purchase/Sales Productivity in PxM/c: high purchase $'s / shopping second Category Spending/Shopping Duration (>avg. purchase productivity +25%*s) ((x = (c+0.25*s) avg. purch. freq.) moderate purchase $'s / shopping second with c= # of purchase cycles) (avg. purchase productivity +/-25%*s) low purchases $'s / shopping second (<avg. purchase productivity -25%*s)

Purchase Inclination in PxM/c: high: 'necessity' driven (likely to buy) (# of shopping events with purchase/ (> avg. purchase inclination +25%*s) total # of shopping events made) medium: unclear motivation (maybe to buy) ((x = (c+0.25*s) avg. purch. freq.) (avg. purchase inclination +/- 25%*s) with c= # of purchase cycles) low: 'joy/pleasure' driven (unlikely to buy) (< avg. purchase inclination -25%*s) Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Category Brand Scope in PxM/c: high interest in alternative products (avg. # of different brand presentations (> avg. category brand scope +25%*s) accessed per shopping event) moderate interest in alternative products ((x = (c+0.25*s) avg. purch. freq.) (avg. category brand scope +/- 25%*s) with c= # of purchase cycles) limited interest in alternative products [Importance of "assortment"]: Choice (< avg. category brand scope -25%*s) Category Retailer Scope in PxM/c : high interest in alternative retailers (avg. # of different retail presentations (> avg. category retailer scope +25%*s) accessed per shopping event) moderate interest in alternative retailers ((x = (c+0.25*s) avg. purch. freq.) (avg. category retailer scope +/- 25%*s) with c= # of purchase cycles) limited interest in alternative retailers [Importance of "value- for-money"] : Price (< avg. category retailer scope -25%*s)

Avg. Category Basket Size in PxM/c: 'bulk quantity' buyer: (% of total buyers) (category purchase volume/purchase event) (>avg. purchase volume +100%) ((x = (c+0.25*s) avg. purch. freq.) 'regular quantity' buyer: (% of total buyers) with c= # of purchase cycles) (avg. purchase volume +/-100%)

[Importance of "small/large packs"]: Sizing 'small quantity' buyer: (% of total buyers) (<avg. purchase volume -100%)

Premium Quality Inclination in PxM/c: high: 'premium quality' inclined buyer (category spending/category volume / avg. (>avg. premium quality inclination +25%*s) category spending/ avg .category volume) medium: 'regular quality' inclined buyer

((x = (c+0.25*s) avg. purch. freq.) (avg. premium quality inclination +/-25%*s) with c= # of purchase cycles) low: 'basic quality' inclined buyer

[Importance of "image"]: Quality (<avg. premium quality inclination -25%*s)

Promotion Responsiveness in PxM/c: high promo sensitive buyer

(category volume with promotional price or (>avg. promotion responsiveness +25%*s) with promotional pack /category volume) moderate promo sensitive buyer

((x = (c+0.25*s) avg. purch. freq.) (avg. promotion responsiveness +/-25%*s) with c= # of purchase cycles) low promo sensitive buyer

[Importance of "deals"]: Promotion (<avg. promotion responsiveness -25%*s)

Innovation Responsiveness in PxM/c: 'early adopter' (avg. time since product launch of product (>avg. innovation responsiveness +25%*s) presentations accessed by the consumer) 'mass follower' ((x = (c+0.25*s) avg. purch. freq.) (>avg.innovation responsiveness +/-25%*s) with c= # of purchase cycles) 'laggard' [Importance of "news"]: Innovation (>avg. innovation responsiveness +25%*s) Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Brand Performance Sensitiveness in PxM/c: high performance sensitivity (# of brand consumer reports accessed) (>avg. consumer reports accessed +25%*s) moderate performance sensitivity

((x = (c+0.25*s) avg. purch. freq.) (avg. consumer reports accessed +/-25%*s) with c= # of purchase cycles) low performance sensitivity [Importance of "Product Performance"]: (<avg. consumer reports accessed -25%*s) Retailer Performance Sensitiveness in PxM/c: high performance sensitivity

(# of retailer consumer reports accessed) (>avg. consumer reports accessed +25%*s) moderate performance sensitivity

((x = (c+0.25*s) avg. purch. freq.) (avg. consumer reports accessed +/-25%*s) with c= # of purchase cycles) low performance sensitivity [importance of "Retailer Performance"] (<avg. consumer reports accessed -25%*s)

Demographics:

- Age - Gender

- Address

- Profession

Category Specific Consumer Need Profile Data: For example: Clothing Sizes:

- Shirts Small, Medium, Large, Extra Large

- Trousers/Suits

- Underwear/Bathing Cloth

- Dress/Blouses - Shoes

information and Ad Exposure in PxM:

- Product Consumer Opinion Access in PxM: Brand 1,2,2,3,...

- Product Brands Researched in PxM: Brand 1,2,2,2,3,...

- Product Brands Purchased in PxM: Brand 1,2,3,3,3,3..

Product Ad Exposure in PxM: Ad 1,1,2,3,...

Retailer Consumer Opinion Access in PxM: Brand 1,2,3,3,4,5,. Retailers Researched in PxM: Brand 1,1,2,3,... Retailers Purchased in PxM: Brand 1,2,2,3,...

Retailer Ad Exposure in PxM Ad 1,2,3,3,3,... 3. Brand Specific Consumer Shopping Information:

Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Brand Volume in PxM/c: Brand share of category volume (PxM)/c: loyal user (brand share > 75%) ((x = (c+0.25*s) avg. purch. freq.) switcher (brand share 75% - 25% ) with c= # of purchase cycles) occasional user (brand share< 25% > 0%) non-user (brand share= 0%)

Last Brand Research Date in PxM: prospect (x = 1.25*s* avg. purch. freq.) Last Brand Purchase Date in PxM: user (x = 1.25*s* avg. purch. freq.) Time since last Brand purchase: suspect ( > -0.25*s* avg. purch. freq.) attritor ( > 1.25 *s* avg. purch. freq.)

Brand Spending in PxM/c: heavy spender (> avg.spending+25%*s) ((x = (c+0.25*s) avg. purch. freq.) medium spender (avg.spending+/-25%*s) with c= # of purchase cycles) light spender (< avg.spending-25%*s) non-user (0%)

Brand Purchase Inclination in PxM/c: high: likely to buy brand when shopping (# brand purchase acts/ (> avg. purchase inclination +25%*s) total # of category shopping events) medium: moderately likely to buy brand ((x = (c+0.25*s) avg. purch. freq.) (avg. purchase inclination +/- 25%*s) with c= # of purchase cycles) low: unlikely to buy brand when shopping ["Brand Purchase Likelihood"] (< avg. purchase inclination -25%*s) 0: no brand purchase inclination

(brand purchase inclination=0)

Brand Impact in PxM/c: high: likely to buy after research act

(# brand purchase acts/ (> avg. brand impact +25%*s) total # of category brand shopping acts) medium: moderately likely of buying ((x = (c+0.25*s) avg. purch. freq.) (avg. brand impact +/- 25%*s) with c= # of purchase cycles) low: unlikely to buy after research act

["Brand Purchase Intent"] (< avg. brand impact -25%*s) 0: no brand impact

(brand impact=0) Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Brand Conversion in PxM/c: high: needs few brand research acts (# of brand purchase acts/ (> avg. brand conversion +25%*s) # of brand shopping acts) medium: needs avg. brand research acts ((x = (c+0.25*s) avg. purch. freq.) (avg. brand conversion +/- 25%*s) with c= # of purchase cycles) low: needs many brand research acts ["Brand Proposition Appeal/Clarity"] (<avg. brand conversion -25%*s) 0: 'not convinced' brand shopper (brand conversion=0)

Brand Purchase Impulse in PxM/c: high: long (re)search time needed to buy (Brand Shopping Duration / Brand (>avg. brand purchase impulse +25%*s) Shopping Acts / brand purch. incl.) medium: avg. (re) search time to buy ((x = (c+0.25*s) avg. purch. freq.) (avg. brand purchase impulse +/-25%*s) with c= # of purchase cycles) low: short (re)search time needed to buy ["Brand Purchase Rush"] (<avg. brand purchase impulse -25%*s) NA: no purchase act

Brand Share of Mind in PxM: strongly aware (share of mind > 75%) (% of category shopping events regularly aware (share of mind 75%-25%) with brand shopping act) little aware (share of mind < 25%> 0%) no interest/not aware (share of mind=0%)

Brand User's Competitive Scope in PxM/c: wide range of product alternatives (avg. # of different brand presentations (> avg. alternative brand scope +25%*s) accessed per shopping event) moderate range of product alternatives ((x = (c+0.25*s) avg. purch. freq.) (avg. alternative brand scope +/- 25%*s) with c= # of purchase cycles) limited range of product alternatives ["Competitive Brand Scope"] (< avg. alternative brand scope -25%*s)

Brand "Interest" in PxM/c : high: limited interest in alternative brands

( # of brand research acts / (> avg. brand interest +25%*s) total # of category brand research acts) moderate interest in alternative brands ((x = (c+0.25*s) avg. purch. freq.) (avg. brand interest +/- 25%*s) with c= # of purchase cycles) low: high interest in alternative brands ["Brand Interest vs. Competition"] (< avg. brand interest -25%*s)

0: no brand interest (Brand lnterest=0)

Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Brand User Needs Profile:

Category Brand Scope in PxM/c: high interest in alternative products (avg. # of different brand presentations (> avg. category brand scope +25%*s) accessed per shopping event) moderate interest in alternative products ((x = (c+0.25*s) avg. purch. freq.) (avg. category brand scope +/- 25%*s) with c= # of purchase cycles) limited interest in alternative products [Importance of "assortment"]: Choice (< avg. category brand scope -25%*s)

Category Retailer Scope in PxM/c: high interest in alternative retailers (avg. # of different retail presentations (> avg. category retailer scope +25%*s) accessed per shopping event) moderate interest in alternative retailers ((x = (c+0.25*s) avg. purch. freq.) (avg. category retailer scope +/- 25%*s) with c= # of purchase cycles) limited interest in alternative retailers [Importance of "value- for-money"]: Price (< avg. category retailer scope -25%*s)

Avg. Category Basket Size in PxM/c: 'bulk quantity' buyer: (% of total buyers) (category purchase volume/purchase event) (>avg. purchase volume +100%) ((x = (c+0.25*s) avg. purch. freq.) 'regular quantity' buyer: (% of total buyers) with c= # of purchase cycles) (avg. purchase volume +/-100%) [Importance of "small large packs"]: Sizing 'small quantity' buyer: (% of total buyers) (<avg. purchase volume -100%)

Premium Quality Inclination in PxM/c: high: 'premium quality' inclined buyer (category spending/category volume / avg. (>avg. premium quality inclination +25%*s) category spending/ avg .category volume) , medium: 'regular quality' inclined buyer ((x = (c+0.25*s) avg. purch. freq.) (avg. premium quality inclination +/-25%*s) with c= # of purchase cycles) low: 'basic quality' inclined buyer [Importance of "image"]: Quality (<avg. premium quality inclination -25%*s)

Promotion Responsiveness in PxM/c: high promo sensitive buyer (category volume with promotional price or (>avg. promotion responsiveness +25%*s) with promotional pack /category volume) moderate promo sensitive buyer ((x = (c+0.25*s) avg. purch. freq.) (avg. promotion responsiveness +/-25%*s) with c= # of purchase cycles) low promo sensitive buyer [Importance of "deals"]: Promotion (<avg. promotion responsiveness -25%*s)

Innovation Responsiveness in PxM/c: 'early adopter' (avg. time since product launch of product (>avg. innovation responsiveness +25%*s) presentations accessed by the consumer) 'mass follower' ((x = (c+0.25*s) avg. purch. freq.) (>avg.innovation responsiveness +/-25%*s) with c= # of purchase cycles) 'laggard' [Importance of "news"]: Innovation (>avg. innovation responsiveness +25%*s)

Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

((x = (c+0.25*s) avg. purch. freq.) (avg. consumer reports accessed +/-25%*s) with c= # of purchase cycles) low performance sensitivity [Importance of "Product Performance"]: (<avg. consumer reports accessed -25%*s)

Retailer Performance Sensitiveness in PxM/c: high performance sensitivity (# of retailer consumer reports accessed) (>avg. consumer reports accessed +25%*s) moderate performance sensitivity

Demographics:

- Age

- Gender

- Address

- Profession

Category Specific Consumer Need Profile Data: For Example: Clothing Sizes:

- Shirts Small, Medium, Large, Extra Large - Trousers/Suits

- Underwear/Bathing Cloth

- Dress/Blouses

- Shoes

Information and Ad Exposure in PxM:

- Product Consumer Opinion Access in PxM: Brand 1,2,2,3,...

- Product Brands Researched in PxM: Brand 1,2,2,2,3,..

- Product Brands Purchased in PxM: Brand 1,2,3,3,3,3.

- Product Ad Exposure in PxM: Ad 1,1,2,3,...

4. Retailer Specific Consumer Shopping Information:

Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Retailer Volume in PxM/c: Retailer Share of category volume (PxM)/c: loyal shopper (share > 75%) ((x = (c+0.25*s) avg. purch. freq.) switcher (share 75% - 25% ) with c= # of purchase cycles) occasional shopper (share< 25% > 0%) non-shopper (retailer share= 0%)

Last Retailer Research Date in PxM: prospect (x = 1.25*s* avg. purch. freq.) Last Retailer Purchase Date in PxM: shopper (x = 1.25*s* avg. purch. freq.) Time since last Retailer purchase: suspect ( > -0.25*s* avg. purch. freq.) attritor ( > 1.25 *s* avg. purch. freq.)

Retailer Spending in PxM/c: heavy spender (> avg.spending+25%*s) ((x = (c+0.25*s) avg. purch. freq.) medium spender (avg.spending+/-25%*s) with c= # of purchase cycles) light spender (< avg. spending-25%*s) non-user (0%)

Shopping Frequency in PxM/c: frequent shopper (>avg.purch.freq.+25%*s) ((x = (c+0.25*s) avg. purch. freq.) regular shopper (avg. purch.freq. +/-25%*s) with c= # of purchase cycles) infrequent shopper (avg. purch.freq-25%*s)

Retailer Purchase Inclination in PxM/c: high: likely to buy retailer when shopping (# retailer purchase acts/ (> avg. purchase inclination +25%*s) total # of category shopping events) medium: moderately likely to buy retailer ((x = (c+0.25*s) avg. purch. freq.) (avg. purchase inclination +/- 25%*s) with c= # of purchase cycles) low:unlikely to buy retailer when shopping ["Retailer Purchase Likelihood"] (< avg. purchase inclination -25%*s) 0: no retailer purchase inclination

(retailer purchase inclination^)

Retailer Impact in PxM/c: high: likely to buy after research act

(# retailer purchase acts/ (> avg. retailer impact +25%*s) total # of category shopping acts) medium: moderately likely of buying ((x = (c+0.25*s) avg. purch. freq.) (avg. retailer impact +/- 25%*s) with c= # of purchase cycles) low: unlikely to buy after research act

["Retailer Purchase Intent"] (< avg. retailer impact -25%*s) 0: no retailer impact

(retailer impact=0) Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Retailer Conversion in PxM/c: high: needs few retailer research acts (# of retailer purchase acts/ (> avg. retailer conversion +25%*s) # of retailer shopping acts) medium: needs avg. retailer research acts ((x = (c+0.25*s) avg. purch. freq.) (avg. retailer conversion +/- 25%*s) with c= # of purchase cycles) low: needs many retailer research acts ["Proposition Appeal/Clarity"] (<avg. retailer conversion -25%*s)

0: 'not convinced' retailer shopper

(retailer conversion=0)

Retailer Purchase impulse in PxM/c: high: long (re)search time needed to buy (Retailer Shopping Duration / Retailer (>avg. retailer purchase impulse +25%*s) Shopping Acts / brand purch. incl.) medium: avg. (re) search time to buy ((x = (c+0.25*s) avg. purch. freq.) (avg. retailer purchase impulse+/-25%*s) with c= # of purchase cycles) low: short (re)search time needed to buy ["Brand Purchase Rush"] (<avg. retailer purchase impulse -25%*s) NA: no purchase act

Purchase/Sales Productivity in PxM/c: high purchase $'s / shopping second Category Spending/Retailer Shopping Duration (>avg. purchase productivity +25%*s) ((x = (c+0.25*s) avg. purch. freq.) moderate purchase $'s / shopping second with c= # of purchase cycles) (avg. purchase productivity +/-25%*s) low purchases $'s / shopping second (<avg. purchase productivity -25%*s)

Retailer Share of Mind in PxM: strongly aware (share of mind > 75%) (% of category shopping events regularly aware (share of mind 75-25%) with retailer shopping act) little aware (share of mind < 25%> 0%) no interest/not aware (share of mind=0%)

Retailer Shopper's Competitive Scope in PxM/c: wide range of retailer alternatives (avg. # of different retailer presentations (> avg. alternative retailer scope +25%*s) accessed per shopping event) moderate range of retailer alternatives ((x = (c+0.25*s) avg. purch. freq.) (avg. alternative retailer scope+/- 25%*s) with c= # of purchase cycles) limited range of retailer alternatives ["Competitive Retailer Scope"] (< avg. alternative retailer scope -25%*s)

Retailer "Interest" in PxM/c: high: limited interest in alternative retailers ( # of brand research acts / (> avg. retailer interest +25%*s) total # of category brand research acts) moderate interest in alternative retailers ((x = (c+0.25*s) avg. purch. freq.) (avg. retailer interest +/- 25%*s) with c= # of purchase cycles) low: high interest in alternative retailers ["Retailer Interest vs. Competition"] (< avg. retailer interest -25%*s) 0: no retailer interest (Retailer lnterest=0) Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Retailer Shopper Needs Profile: Category Brand Scope in PxM/c: high interest in alternative products

(avg. # of different brand presentations (> avg. category brand scope +25%*s) accessed per shopping event) moderate interest in alternative products ((x = (c+0.25*s) avg. purch. freq.) (avg. category brand scope +/- 25%*s) with c= # of purchase cycles) limited interest in alternative products [Importance of "assortment"]: Choice (< avg. category brand scope -25%*s)

Avg. Category Basket Size in PxM/c: 'bulk quantity' buyer: (% of total buyers) (category purchase volume/purchase event) (>avg. purchase volume +100%) ((x = (c+0.25*s) avg. purch. freq.) 'regular quantity' buyer: (% of total buyers) with c= # of purchase cycles) (avg. purchase volume +/-100%) [Importance of "small/large packs"]: Sizing 'small quantity' buyer: (% of total buyers) (<avg. purchase volume -100%)

Premium Quality Inclination in PxM/c: high: 'premium quality' inclined buyer (category spending/category volume / avg. (>avg. premium quality inclination +25%*s) category spending/ avg .category volume) medium: 'regular quality' inclined buyer ((x = (c+0.25*s) avg. purch. freq.) (avg. premium quality inclination +/-25%*s) with c= # of purchase cycles) low: 'basic quality' inclined buyer [Importance of "image"]: Quality (<avg. premium quality inclination -25%*s)

Promotion Responsiveness in PxM/c: high promo sensitive buyer (category volume with promotional price or (>avg. promotion responsiveness +25%*s) with promotional pack /category volume) moderate promo sensitive buyer ((x = (c+0.25*s) avg. purch. freq.) (avg. promotion responsiveness +/-25%*s) with c= # of purchase cycles) low promo sensitive buyer [Importance of "deals"]: Promotion (<avg. promotion responsiveness -25%*s) Innovation Responsiveness in PxM/c: 'early adopter'

(avg. time since product launch of product (>avg. innovation responsiveness +25%*s) presentations accessed by the consumer) 'mass follower' ((x = (c+0.25*s) avg. purch. freq.) (>avg. innovation responsiveness +/-25%*s) with c= # of purchase cycles) 'laggard' [Importance of "news"]: Innovation (>avg. innovation responsiveness +25%*s) Consumer Shopping Profile Parameters: Consumer Segments & Target Audiences

Demographics:

- Age - Gender

- Address

- Profession

Category Specific Consumer Need Profile Data: For Example: Clothing Sizes: - Shirts Small, Medium, Large, Extra Large

Trousers/Suits Underwear/Bathing Cloth - Dress/Blouses

Shoes

Information and Ad Exposure in PxM:

- Retailer Consumer Opinion Access in PxM: Brand 1,2,3,3,4,5,.

- Retailers Researched in PxM: Brand 1,1,2,3,...

- Retailers Purchased in PxM: Brand 1,2,2,3,...

- Retailer Ad Exposure in PxM Ad 1,2,3,3,3,... Section II: Performance Indicators for Manufacturers

1. Brand Product Indicators: 0 - Brand Performance Indicators : *

- Brand Profile Indicators:**

- Brand Advertising Performance Indicators:* 5

- Brand Price/Distribution/Promotion Indicators:*

2. Brand Product Presentation Effectiveness Indicators: 0

- Calculation of Effectiveness Data for each Brand Product Presentation

- Definition of Brand Product Presentation Effectiveness Parameters 5

3. Brand Product Ad Effectiveness Indicators:

- Calculation of Effectiveness Data for each Brand Product Ad 0 - Definition of Effectiveness Parameters for each Brand Product Ad

4. Brand Product Promotion Effectiveness Indicators: 5 - Calculation of Effectiveness Data for each Brand Product Promotion

- Definition of Effectiveness Parameters for each Brand Product Promotion

0

* Performance will be benchmarked vs. competitive brands Data break-outs by retailer chain are not available - Indicators can be broken-out by demographics, purchase behavior, ad/presentation exposure

** The user profile of a particular brand become apparent only once you compare the brand's category shopping habits/needs with that other brands or against that of the category average. 1. Brand Product Indicators:

- Brand Performance Indicators:*

- Brand Profile Indicators:**

10

Brand Advertising Performance Indicators:

15

Brand Price/Distribution/Promotion Indicators:*

20

25

* Performance will be benchmarked vs. competitive brands Data break-outs by retailer chain are not available -_n indicators can be broken-out by demographics, purchase behavior, ad/presentation exposure

** The user profile of a particular brand become apparent only once you compare the brand's 35 category shopping habits/needs with that other brands or against that of the category average.

Brand Performance Indicators:*

Base: Category Shoppers (those who have made a category research/puchase act in the PxM)

Brand Share:

- Brand Volume Share: % (Brand Volume in PxM / Category Volume in PxM)

- Brand Purchase Share: % (Brand Spending in PxM / Category Spending in PxM)

Brand Penetration (or User Base): %

(those who have made brand purchase in PyM with y = ((c+0.25*s) avg. purch. freq.)) / (those who have made category purchase in PyM with y =((c+0.25*s* avg. purch. freq.))

(with c= # of purchase cycles)

User Base Loyalty:

Brand Loyalty Index: PyM brand purchase share/brand penetration % loyal users (brand share > 75%)

% switchers (brand share 75% - 25% )

% occasional users (brand share< 25% > 0%)

% non-users (brand share= 0%) (y = ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Brand Shopping Frequency:

Brand Shopping Frequency in PyM/c: ((y = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

(Re)Purchase Potential (or (Re)Trial Potential):

- Brand Share of Category Prospects: ["Share of those likely to buy a category item"] (those with brand research act in PxM/those with category research act in PxM)

Brand Purchase Inclination: ["Brand Purchase Likelihood"]

(# brand purchase acts/ total # of category shopping events) - Brand Churn: ["% of existing customers who have ceased buying the brand"]

(# of attritors in PyM / # of users in PyM with y = ((c+0.25*s) avg. purch. freq))

Brand Interest: - Brand Share of Mind in PxM (% of category shopping events with brand shopping act)

- Brand "Interest" in PxM/c: ( # of brand research acts / # of category brand research acts)

- Brand User's Competitive Scope in PxM/c:

(avg. # of different brand presentations accessed per shopping event) Brand Profile Indicators:**

Base: Brand Shoppers (those who have made a brand research/puchase act in the PxM)

Brand User Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [Importance of "assortment"]: Choice (avg. # of different brand presentations accessed per shopping event)

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Category Retailer Scope in PxM/c: [Importance of "value-for-money"] : Price

(avg. # of different retail presentations accessed per shopping event) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Avg. Category Basket Size in PxM/c: [Importance of "small/large packs"]: Sizing

(category purchase volume/purchase event) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Premium Quality Inclination in PxM/c: [Importance of "image"]: Quality

(category spending/category volume / avg. category spending/ avg .category volume) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

(category volume with promotional price or with promotional pack /category volume) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Innovation Responsiveness in PxM/c: [Importance of "news"]: Innovation (avg. time since product launch of product presentations accessed by the consumer)

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Brand Communication Performance Indicators:* Base: Category Shoppers (those who have made a category research puchase act in the PxM)

Brand Communication Effectiveness:

10

- Brand Impact in PxM/c: ["Brand Purchase Intent"]

(# brand purchase acts / total # of category brand shopping acts) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

15 Measures likelihood that consumer buys after a single brand presentation research exposure.

- Brand Conversion in PxM/c: ["Brand Proposition Appeal/Clarity"]

(# of brand purchase acts / # of brand shopping acts) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

20

Measures the brand presentation exposure required for a single purchase act.

- Brand Purchase Impulse in PxM/c: ["Brand Purchase Rush"]

(Brand Shopping Duration / Brand Shopping Acts / brand purch. incl.) 25 ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Measures the brand shopping time needed to complete a single purchase act among buyers.

-_n - Brand Presentation Customization Index (# customized presentations used / brand vs. avg.) Measures the brand presentation personalization sophistication degree.

- Brand Presentation Impact/Exposure:

Pres.l Pres.2 Pres.3 Pres.4...Total Brand 35 Target Audience:

- Presentation Impact(*) in PxM:

Pres.Purchase Delta (d) Pres.Purchase Delta vs. Category Avg.

40

Presentation Exposure in PxM: Share of Total Brand Contacts

45

-_n (*) Impact is only measured among those that have been exposed to the presentation in PxM

Pres.Purchase Delta: - Brand Vol. Share of Pres.x / Brand Vol. Share of Ctrl (Pres.Ref).*100 - Total Brand Pres.Delta: Sum of (pres.delta's*contact share) of all Pres.

_<- _<. Share of Total Brand Contacts: # Pres.x Shopping Acts / # Total Brand Shopping Acts* 100

Brand Presentation Performance (d) vs. Avg. Category Presentation Performance: r>75% range) (50%-75% range) (25%-50% range) «25% range)

Strong Above Average Below Average Weak

60 (d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Brand Advertising Performance Indicators:*

5 Base: Category Shoppers (those who have made a category research/puchase act in the PxM)

10

Brand Advertising Impact Exposure:

Adl Ad2 Ad3 Ad4... Total Brand 15 Target Audience :

- Advertising Impact(*) in PxM:

Ad Purchase Delta (d) -_n Ad Purchase Delta vs. Category Avg.

- Brand Advertising Exposure in PxM:

Share of Voice 25 GRP's

Reach Frequency

,_π - Brand Ad Customization Index (# customized ads used / brand vs. avg.)

Measures the brand ad personalization sophistication degree.

35

(*) Impact is only measured among those that have been exposed to the ad in PxM

Ad Purchase Delta: - Brand Vol. Share of Ad.x / Brand Vol. Share of Ctrl (no Ad) * 100 40 - Total Brand Ad Delta: Sum of (ad delta' s*share of voice) of all ads

Brand Ad Performance (d) vs. Avg. Category Ad Performance:

(>75%range) (50%-75% range) (25%-50% range) (<25% range) 5 Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s)

Share of Voice: (# ad contacts of brand / # of ad contacts of category) 0 GRP's: ( # of contacts in PxM)

Reach: (# of consumers reached in PxM / category shoppers in PxM):

Frequency: (# of times that the ads were seen on average)

5 Brand Price/Distribution Promotion Indicators:*

5

Distribution (in PxM):

- Numerical: % of retailers carrying the sku/brand

- Weighted: % of retailers carrying the sku/brand weighted by retailer volume

10 Brand Pricing (in PxM) :

- Avg. Purchase Price (avg. price at which the sku or brand was purchased)

- Avg. Regular Price (avg. regular price at which the sku or brand was purchased)

- Avg. Promotional Price (avg. promotional price at which the sku or brand was purchased)

15 Forward Placement (or Display) (in PxM):

- Brand Display Interest (*): ( # of brand research acts / # of category brand research acts )

- Brand Display Impact (*):(# brand purchase acts / total # of category brand shopping acts)

20 - Display Share: % of retailer category overview page views where a brand sku is displayed

Brand Promotion:

- Promotional Pressure (% of brand volume sold in promotion)

25 - price promotion (% of brand volume sold at promotional price)

- 'special pack' promotion (% of brand volume sold in a 'special promotion pack')

- Brand Promotion Impact/Exposure:

Proml Prom2 Prom3 Prom4...Total Brand 30 Target Audience:

- Promotion Impact(**) in PxM:

Promo Purchase Delta (d) _ _ Promo Purchase Delta vs. Category Avg.

- Promotion Exposure in PxM:

Reach

- Brand Promotion Customization Index (# customized promotions used / brand vs. avg.)

40 Measures the brand promotion personalization sophistication degree.

45

(*) Brand "Interest" and Impact is only measured on the retailer category overview pages (**) Impact is only measured among those that have been exposed to the promotion

Promo Purchase Delta: - Brand Vol.Share of Prom.x/Brand Vol.Share of Ctrl (no Promo)* 100 50 - Total Brand Delta: Sum of all (promo delta' s*reach) of all promo's.

Brand Promo Performance (d) vs. Avg. Category Promo Performance: f>75%range) (50%-75% range) (25%-50% range) (<25% range)

55 Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s)

Reach: (# of consumers reached in PxM / category shoppers in PxM) 0 2. Brand Product Presentation Effectiveness Indicators:

Calculation of Effectiveness Data for each Brand Product Presentation

- Definition of Brand Product Presentation Effectiveness Parameters

Effectiveness Data for each Brand Product Presentation

The effectiveness of each Brand Product Presentation is determined as follows:

1) measure the impact among those exposed x-times to the Brand Product Presentation

2) measure the impact of Brand Product Presentation Reference among 100 of the same target

3) calculate the impact delta versus the reference (Score Pres.X/Score Pres.Ref * 100)

4) compare the impact delta of the Brand Product Presentation vs. that of other presentations

Presentation Impact^*) in PxM:

10 Pres.X Pres.Ref Delta (=Pres.X/Pres.Ref.*100)

Target Audience:

Share of Total Brand Contacts:

Base Size:

15

Brand Purchase Volume: Performance vs. Category Avg.**

Purchase Share: 20 Performance vs. Category Avg.

Penetration:

Performance vs. Category Avg.

25 Loyalty:

Performance vs. Category Avg.

Shopping Frequency: -„ Performance vs. Category Avg.

(Re)Purchase Potential:

- Share of Category Prospects Performance vs. Category Avg.

35 - Brand Purchase inclination

Performance vs. Category Avg.

- Brand Churn

-_n Performance vs. Category Avg.

Brand interest:

- Brand Share of Mind Performance vs. Category Avg.

45 - Brand "Interest"

Performance vs. Category Avg.

- Brand User's Competitive Scope _<.„ Performance vs. Category Avg.

(*) Impact is only measured among those that have been exposed to the presentation in PxM

(**) Brand Presentation Performance (Delta) vs. Avg. Category Presentation Performance:

55

(>75% range) C50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s)

60 Effectiveness Data for each Brand Product Presentation

The effectiveness of each Brand Product Presentation is determined as follows:

Presentation Impact(*) in PxM: Pres.X Pres.Ref Delta (=Pres.X Pres.Ref.*100)

Target Audience:

Share of Total Brand Contacts:

Base Size:

Brand User Profile: Category Needs:

Category Brand Scope: Choice Performance vs. Category Avg.**

Category Retailer Scope: Price Performance vs. Category Avg.

Avg. Category Basket Size: Sizing Performance vs. Category Avg.

Premium Quality Inclination: Quality Performance vs. Category Avg.

Promotion Responsiveness: Promotion Performance vs. Category Avg.

Innovation Responsiveness: Innovation Performance vs. Category Avg.

Brand Communication Effectiveness:

- Brand Impact Performance vs. Category Avg.

- Brand Conversion Performance vs. Category Avg.

- Brand Purchase Impulse Performance vs. Category Avg.

(>75% range) f 50%-75% range) (25%-50% range) «25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Definition of Effectiveness Parameters for each Brand Product Presentation

Base Test Leg: Category Shoppers exposed x-times to Brand Product Presentation X in PxM Base Ctrl Leg: Category Shoppers exposed to Brand Product Presentation Reference in PxM

Brand Share:

- Brand Volume Share: % (Brand Volume in PxM / Category Volume in PxM) - Brand Purchase Share: % (Brand Spending in PxM / Category Spending in PxM)

Brand Penetration (or User Base): %

(with c= # of purchase cycles)

User Base Loyalty:

Brand Loyalty Index: PyM brand purchase share/brand penetration

% loyal users (brand share > 75%) % switchers (brand share 75% - 25% ) % occasional users (brand share< 25% > 0%)

% non-users (brand share= 0%)

(y = ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Brand Shopping Frequency:

Brand Shopping Frequency in PyM/c:

((y ⁼ (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) (Re)Purchase Potential (or (Re)Trial Potential):

- Brand Share of Category Prospects: ["Share of those likely to buy a category item"] (those with brand research act in PxM/those with category research act in PxM) - Brand Purchase Inclination: ["Brand Purchase Likelihood"]

(# brand purchase acts/ total # of category shopping events)

- Brand Churn: ["% of existing customers who have ceased buying the brand"]

Brand Interest:

- Brand Share of Mind in PxM (% of category shopping events with brand shopping act)

- Brand "Interest" in PxM/c: ( # of brand research acts / # of category brand research acts) - Brand User's Competitive Scope in PxM/c:

(avg. # of different brand presentations accessed per shopping event) Definition of Effectiveness Parameters for each Brand Product Presentation

Brand User Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [importance of "assortment"]: Choice

(avg. # of different brand presentations accessed per shopping event) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Category Retailer Scope in PxM/c: [importance of "value-for-money"]: Price

Avg. Category Basket Size in PxM/c: [Importance of "small/large packs"]: Sizing

Premium Quality Inclination in PxM/c: [Importance of "image"]: Quality (category spending/category volume / avg. category spending/ avg .category volume)

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

Innovation Responsiveness in PxM/c: [Importance of "news"]: Innovation

(avg. time since product launch of product presentations accessed by the consumer) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Definition of Effectiveness Parameters for each Brand Product Presentation

Brand Communication Effectiveness: - Brand impact in PxM/c: ["Brand Purchase Intent"]

Measures likelihood that consumer buys after a single brand presentation research exposure.

- Brand Conversion in PxM/c: ["Brand Proposition Appeal/Clarity"]

(# of brand purchase acts / # of brand shopping acts) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Measures the brand presentation exposure required for a single purchase act.

- Brand Purchase Impulse in PxM/c: ["Brand Purchase Rush"]

(Brand Shopping Duration / Brand Shopping Acts / brand purch. incl.) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

3. Brand Product Ad Effectiveness Indicators:

- Calculation of Effectiveness Data for each Brand Product Ad

- Definition of Effectiveness Parameters for each Brand Product Ad

Effectiveness Data for each Brand Product Ad

The effectiveness of each Brand Product Ad is determined as follows: 1) measure the impact among those who have been exposed x-times to the Brand Product Ad 5 2) measure the impact of no Brand Product Ad among 100 consumers of the same target

3) calculate the impact delta versus the reference (Score Ad.X/Score Ad.Ref.O * 100)

4) compare the impact delta of the Brand Product Ad vs. that of other ads.

Ad ImpactC*) in PxM: 10 Ad.X Ad.Ref.0 Delta (=Ad.X/Ad.Ref.0*100)

Target Audience: Share of Voice:

Base Size:

15

Brand Purchase Volume Performance vs. Category Avg.**

Purchase Share: 20 Performance vs. Category Avg.

Penetration:

Performance vs. Category Avg.

25 Loyalty:

Performance vs. Category Avg.

Shopping Frequency: __n Performance vs. Category Avg.

(Re)Purchase Potential:

- Share of Category Prospects Performance vs. Category Avg.

35 - Brand Purchase Inclination

Performance vs. Category Avg.

- Chum

_4n Performance vs. Category Avg.

Brand Interest:

- Brand Share of Mind Performance vs. Category Avg.

45 - Brand "Interest"

Performance vs. Category Avg.

- Brand User's Competitive Scope Performance vs. Category Avg.

50

(*) Impact is only measured among those that have been exposed to the Brand Ad in PxM

(**) Brand Ad Performance (Delta) vs. Avg. Category Brand Ad Performance:

(>75% range) (50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) 0 Effectiveness Data for each Brand Product Ad

The effectiveness of each Brand Product Ad is determined as follows: 1) measure the impact among those exposed x-times to the Brand Product Ad 5 2) measure the impact of no Brand Product Ad among 100 consumers of the same target

4) compare the impact delta of the Brand Product Ad vs. that of other ads.

Ad ImpactC*) in PxM: 10 Ad.X Ad.Ref.O Delta (=Ad.X/Ad.Ref.0*100)

Target Audience: Share of Voice: Base Size:

15 Brand User Profile: Category Needs:

Category Brand Scope: Choice Performance vs. Category Avg.**

20 Category Retailer Scope: Price Performance vs. Category Avg.

Avg. Category Basket Size: Sizing -- Performance vs. Category Avg.

Premium Quality Inclination: Quality Performance vs. Category Avg.

Promotion Responsiveness: Promotion 30 Performance vs. Category Avg.

Innovation Responsiveness: Innovation Performance vs. Category Avg.

35 Brand Communication Effectiveness:

- Brand Impact Performance vs. Category Avg.

- Brand Conversion

40 Performance vs. Category Avg.

- Brand Purchase Impulse Performance vs. Category Avg.

45

-_Λ (**) Brand Ad Performance (Delta) vs. Avg. Category Brand Ad Performance:

(>75% range) (50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Definition of Effectiveness Parameters for each Brand Product Ad

Base Test Leg: Category Shoppers exposed x-times to Brand Product Ad X in PxM Base Ctrl Leg: 100 Category Shoppers of the same target group not exposed to any Brand Ad

Brand Share:

Brand Penetration (or User Base): %

(with c= # of purchase cycles)

User Base Loyalty:

Brand Loyalty Index: PyM brand purchase share/brand penetration

% non-users (brand share= 0%)

Brand Shopping Frequency in PyM/c:

((y = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) (Re)Purchase Potential (or (Re)Trial Potential) :

(# brand purchase acts/ total # of category shopping events)

- Brand Churn: ["% of existing customers who have ceased buying the brand"]

Brand Interest:

(avg. # of different brand presentations accessed per shopping event) Definition of Effectiveness Parameters for each Brand Product Ad

Brand User Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [Importance of "assortment"]: Choice

Category Retailer Scope in PxM/c: [Importance of "value-for-money"]: Price

Avg. Category Basket Size in PxM/c: [Importance of "small/large packs"]: Sizing

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

Innovation Responsiveness in PxM/c: [Importance of "news"]: Innovation

(avg. time since product launch of product presentations accessed by the consumer) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Definition of Effectiveness Parameters for each Brand Product Ad Base Test Leg: Category Shoppers exposed x-times to Brand Product Ad X in PxM Base Ctrl Leg: 100 Category Shoppers of the same target group not exposed to any Brand Ad

Brand Communication Effectiveness:

- Brand Impact in PxM/c: ["Brand Purchase Intent"]

- Brand Conversion in PxM/c: ["Brand Proposition Appeal/Clarity"]

Measures the brand presentation exposure required for a single purchase act.

- Brand Purchase impulse in PxM/c: ["Brand Purchase Rush"] (Brand Shopping Duration / Brand Shopping Acts / brand purch. incl.)

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

4. Brand Product Promotion Effectiveness Indicators:

- Calculation of Effectiveness Data for each Brand Product Promotion

- Definition of Effectiveness Parameters for each Brand Product Promotion

Effectiveness Data for each Brand Product Promotion

The effectiveness of each Brand Product Promotion is determined as follows: 1 ) measure the impact among those exposed x-times to the Brand Product Promotion 5 2) measure the impact of no Brand Product Promotion among 100 of the same target group

3) calculate the impact delta versus the reference (Score Prom.X/Score Prom.Ref.O * 100)

4) compare the impact delta of the Brand Product Promotion vs. that of other promotions.

Promotional Impact(*) in PxM: 10 Prom.X Prom.Ref.O Delta (=Prom.X/Prom.Ref.0*100)

Target Audience: Reach:

Base Size:

15

Brand Purchase Volume: Performance vs. Category Avg.**

Purchase Share: 20 Performance vs. Category Avg.**

Penetration:

Performance vs. Category Avg.

25 Loyalty:

Performance vs. Category Avg.

Shopping Frequency: _„ Performance vs. Category Avg.

(Re)Purchase Potential:

- Share of Category Prospects Performance vs. Category Avg.

35 - Brand Purchase Inclination

Performance vs. Category Avg.

- Brand Churn

.„ Performance vs. Category Avg.

Brand Interest:

- Brand Share of Mind Performance vs. Category Avg.

45 - Brand "Interest"

Performance vs. Category Avg.

- Brand User's Competitive Scope -_n Performance vs. Category Avg.

(*) Impact is only measured among those that have been exposed to the Brand Promo in PxM

(**) Brand Promo Performance (Delta) vs. Avg. Category Brand Promo Performance:

55 f>75% range) (50%-75% range) (25%-50% range) «25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) 0 Effectiveness Data for each Brand Product Promotion The effectiveness of each Brand Product Promotion is determined as follows:

1) measure the impact among those exposed x-times to the Brand Product Promotion

2) measure the impact of no Brand Product Promotion among 100 of the same target group

3) calculate the impact delta versus the reference (Score Prom.X/Score Prom.Ref.O * 100) 5 4) compare the impact delta of the Brand Product Promotion vs. that of other promotions.

Promotional Impactf*) in PxM: Prom.X Prom.Ref.O Delta (=Prom.X/Prom.Ref.0*100) Target Audience: 0 Reach: Base Size:

Brand User Profile: Category Needs: 5 Category Brand Scope: Choice Performance vs. Category Avg.**

Category Retailer Scope: Price _π Performance vs. Category Avg.

Avg. Category Basket Size: Sizing Performance vs. Category Avg.

Premium Quality Inclination: Quality 5 Performance vs. Category Avg.

Promotion Responsiveness: Promotion Performance vs. Category Avg. 0 Innovation Responsiveness: Innovation Performance vs. Category Avg.

Brand Communication Effectiveness:

- Brand Impact 5 Performance vs. Category Avg.

- Brand Conversion Performance vs. Category Avg. 0 - Brand Purchase Impulse

Performance vs. Category Avg. 5 (*) Impact is only measured among those that have been exposed to the Brand Promo in PxM

(**) Brand Promo Performance (Delta) vs. Avg. Category Brand Promo Performance:

(>75% range) (50%-75% range) (25%-50% range) «25% range) 0 Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Definition of Effectiveness Parameters for each Brand Product Promotion

Base Test Leg: Category Shoppers exposed x-times to Brand Product Promo X in PxM Base Ctrl Leg: 100 Category Shoppers of same target group not exposed to any Brand Promo

Brand Share:

Brand Penetration (or User Base): %

(with c= # of purchase cycles) User Base Loyalty:

Brand Loyalty Index: PyM brand purchase share/brand penetration

% non-users (brand share= 0%)

(y - ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Brand Shopping Frequency:

Brand Shopping Frequency in PyM/c:

((y = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) (Re)Purchase Potential (or (Re)Trial Potential):

(# brand purchase acts/ total # of category shopping events)

- Brand Churn: ["% of existing customers who have ceased buying the brand"] (# of attritors in PyM / # of users in PyM with y = ((c+0.25*s) avg. purch. freq))

Brand Interest:

(avg. # of different brand presentations accessed per shopping event) Definition of Effectiveness Parameters for each Brand Product Promotion

Brand User Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [Importance of "assortment"]: Choice

Category Retailer Scope in PxM/c: [Importance of "value-for-money"]: Price

Avg. Category Basket Size in PxM/c: [Importance of "small/large packs"]: Sizing (category purchase volume/purchase event)

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Premium Quality inclination in PxM/c: [Importance of "image"] : Quality

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

innovation Responsiveness in PxM/c: [Importance of "news"]: Innovation

(avg. time since product launch of product presentations accessed by the consumer) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Definition of Effectiveness Parameters for each Brand Product Promotion

- Brand Conversion in PxM/c: ["Brand Proposition Appeal/Clarity"]

- Brand Purchase Impulse in PxM/c: ["Brand Purchase Rush"]

Section III: Performance Indicators for Retailers

1. Retailer Category Indicators:

- Retailer Category Performance Indicators:*

10

- Retailer Category Profile Indicators:**

- Retailer Category Advertising Performance Indicators:*

15 - Retailer Category Price/Distribution/Promotion Indicators:*

2. Retailer Category Presentation Effectiveness Indicators:

20 - Calculation of Effectiveness Data for each Retailer Category Presentation

- Definition of Retailer Category Presentation Effectiveness Parameters

25 3. Retailer Category Ad Effectiveness Indicators:

- Calculation of Effectiveness Data for each Retailer Category Ad

- Definition of Effectiveness Parameters for each Retailer Category Ad

30

4. Retailer Category Promotion Effectiveness Indicators:

- Calculation of Effectiveness Data for each Retailer Category Promotion

35

- Definition of Effectiveness Parameters for each Retailer Category Promotion

40 * Whilst it is technically feasible to benchmark performance vs. competitive retailers, the retailers will probably prefer to benchmark against their average peer performance.

Performance will be benchmarked vs. the average 'retailing format' peer performance (i.e. hypermarkets, department stores, catalog, supermarkets, drug stores, electronics, clothing, 45 sports, toys, Book/CD/Nideo, DIY, Furniture, Office)

Data break-outs by retailer chain are not available

-₀ Indicators can be broken-out by demographics, purchase behavior, ad/presentation exposure

** The user profile of a particular retailer category will become apparent only once you compare 55 the retailer's category shopping habits/needs with that other retailers or against that of the category 'retailing format' peer average.

0 1. Retailer Category Indicators:

Retailer Category Performance Indicators:

- Retailer Category Profile Indicators: **

- Retailer Category Advertising Performance Indicators:*

Retailer Category Price/Distribution/Promotion Indicators:¹¹

* Whilst it is technically feasible to benchmark performance vs. competitive retailers, the retailers will probably prefer to benchmark against their average peer performance. Performance will be benchmarked vs. the average 'retailing format' peer performance

(i.e. hypermarkets, department stores, catalog, supermarkets, drug stores, electronics, clothing, sports, toys, Book/CD/Nideo, DIY, Furniture, Office)

Data break-outs by retailer chain are not available indicators can be broken-out by demographics, purchase behavior, ad/presentation exposure

** The user profile of a particular retailer category will become apparent only once you compare the retailer's category shopping habits/needs with that other retailers or against that of the category 'retailing format' peer average.

Retailer Category Performance Indicators:* Base: Category Shoppers (those who have made a category research/puchase act in the PxM)

Retailer Share:

- Retailer Volume Share: % (Retailer Volume in PxM / Category Volume in PxM) - Retailer Purchase Share: % (Retailer Spending in PxM / Category Spending in PxM)

Category Development Index (CDI):

( Retailer Category Purchase Share / Retailer 'All Commodity' Purchase Share * 100 ) Category Sales/Purchase Productivity (Consumer Purchase Spending/Time Spend Shopping): (Category Spending/Retailer Consumer Categoiy Shopping Duration)

Retailer Penetration (or User Base): %

(those who have made retailer purchase in PyM with y = ((c+0.25*s) avg. purch. freq.)) / (those who have'made retailer purchase in PyM with y =((c+0.25*s* avg. purch. freq.))

(with c= # of purchase cycles)

Shopper Base Loyalty: Retailer Loyalty Index: PyM retailer purchase share/retailer penetration

% loyal buyers (retailer share > 75%) % switchers (retailer share 75% - 25% ) % occasional buyers (retailer share< 25% > 0%) % non-buyers (retailer share= 0%)

(y ⁼ ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Retailer Shopping Frequency: Shopping Frequency in PyM/c :

((y = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

(Re)Purchase Potential (or (Re)Trial Potential):

- Retailer Share of Category Prospects: ["Share of those likely to buy a category item"] (those with retailer research act in PxM/those with category research act in PxM)

- Retailer Purchase inclination: ["Retailer Purchase Likelihood"]

(# retailer purchase acts/ total # of category shopping events) - Retailer Churn: ["% of existing customers who have ceased buying at the retailer"]

Retailer Interest:

- Retailer Share of Mind in PxM (% of category shopping events with retailer shopping act) - Retailer "Interest" in PxM/c:(# of retailer research acts/# of category retailer research acts)

- Retailer Shopper's Competitive Scope in PxM/c:

(avg. # of different retailer presentations accessed per shopping event) Retailer Profile Indicators:**

Base: Retailer Shoppers (those who have made a brand research puchase act in the PxM)

Retailer Category Shopper Profile: Category Shopping Habits/Needs

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Category Retailer Scope in PxM/c: [Importance of "value-for-money"]: Price

Avg. Category Basket Size in PxM/c: [Importance of "small/large packs"]: Sizing

Premium Quality Inclination in PxM/c: [Importance of "image"]: Quality

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Retailer Communication Performance Indicators:* Base: Category Shoppers (those who have made a category research puchase act in the PxM)

Retailer Communication Effectiveness:

10

- Retailer Impact in PxM/c: ["Retailer Purchase Intent"]

(# retailer purchase acts / total # of category retailer shopping acts) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

15 Measures likelihood that consumer buys after a single retailer presentation research exposure.

- Retailer Conversion in PxM/c: ["Retailer Proposition Appeal/Clarity"]

20

Measures the retailer presentation exposure required for a single purchase act.

- Retailer Purchase Impulse in PxM/c: ["Retailer Purchase Rush"]

(Retailer Shopping Duration / Retailer Shopping Acts / retailer purch. incl.) 25 ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Measures the retailer shopping time needed to complete a single purchase act among buyers.

Retailer Presentation Customization Index (# customized presentations used / brand vs. avg.)

30 Measures the retailer presentation personalization sophistication degree.

- Retailer Presentation Impact/Exposure:

Pres.l Pres.2 Pres.3 Pres.4...Total Retailer 35 Target Audience:

- Presentation Impact(*) in PxM:

Pres.Purchase Delta (d) Pres.Purchase Delta vs. Category Avg.

40

- Presentation Exposure in PxM: Share of Total Retailer Contacts

45

_<-_Λ (*) Impact is only measured among those that have been exposed to the presentation in PxM

Pres.Purchase Delta:-Retailer Vol.Share of Pres.x /Retailer Vol.Share of Ctrl (Pres.Ref).* 100 -Total Retailer Pres.Delta: Sum of (pres.delta's*contact share) of all Pres.

„ Share of Total Retailer Contacts: # Pres.x Shopping Acts/# Total Retailer Shopping Acts*100

Retailer Presentation Performance (d) vs. Avg. Category Presentation Performance: f>75% range) (50%-75% range) (25%-50% range) «25% range)

Strong Above Average Below Average Weak

60 (d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Retailer Advertising Performance Indicators:*

Retailer Advertising Impact/Exposure:

Adl Ad2 Ad3 Ad4... Total Retailer Target Audience:

- Advertising Impact(*) in PxM: Ad Purchase Delta (d) Ad Purchase Delta vs. Category Avg.

- Retailer Advertising Exposure in PxM:

Share of Voice GRP's Reach

Frequency

- Retailer Ad Customization Index (# customized ads used / retailer vs. avg.) Measures the retailer ad personalization sophistication degree.

(*) Impact is only measured among those that have been exposed to the ad in PxM

Ad Purchase Delta: -Retailer Vol. Share of Ad.x / Retailer Vol. Share of Ctrl (no Ad) * 100 - Total Retailer Ad Delta: Sum of (ad delta' s*share of voice) of all ads

Retailer Ad Performance (d) vs. Avg. Category Ad Performance:

(>75%range) (50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak (d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s)

Share of Voice: (# ad contacts of retailer / # of ad contacts of category)

GRP's: ( # of contacts in PxM) Reach: (# of consumers reached in PxM / category shoppers in PxM):

Frequency: (# of times that the ads were seen on average) Retailer Assortment/Price/Promotion Indicators:*

Retailer Assortment (in PxM):

- Brand Assortment: % segment share - sku's - sku item volume-pareto analysis

- Private Label Assortment: % segment share - sku's - sku item volume-pareto analysis

- Category Breath (Choice): # of different product brands - Category Depth (Sizes): avg. size sku's per category brand

Retailer Brand/Sku Pricing (of all sku's in assortment in PxM):

- Avg. Purchase Price (avg. price at which the sku or brand was purchased)

- Avg. Regular Price (avg. regular price at which the sku or brand was purchased) - Avg. Promo Price (avg. promo price at which the sku or brand was purchased)

Retailer Forward Placement/Display Brand/Sku Performance (of all sku's on display in PxM): -Retailer Display Productivity (***):(# of category purchase acts/# of category shopping acts) -Brand Display Interest (***): ( # of brand research acts / # of category brand research acts ) -Brand Display Impact (***):(# brand purchase acts / total # of category brand shopping acts)

Retailer Promotion:

- Promotional Pressure (% of retailer volume sold in promotion)

- price promotion (% of retailer volume sold at promotional price) - 'special pack' promotion (% of retailer volume sold in a 'special promotion pack')

- Brand Promotion Impact/Exposure:

Proml Prom2 Prom3 Prom4...Total Brand Target Audience: - Promotion Impact(**) in PxM: Promo Purchase Delta (d) Promo Purchase Delta vs. Category Avg.

- Promotion Exposure in PxM:

Reach - Retailer Promotion Customization Index (# customized promotions used / retailer vs. avg.)

Measures the retailer promotion personalization sophistication degree.

(**) Impact is only measured among those that have been exposed to the promotion

(***) Brand "Interest" and Impact is only measured on the retailer category overview pages

Promo Purchase Delta: - Brand Vol.Share of Prom.x/Brand Vol.Share of Ctrl (no Promo)*100

- Total Brand Delta: Sum of all (promo delta' s*reach) of all promo's.

Brand Promo Performance (d) vs. Avg. Category Promo Performance:

(>75%range) (50%-75% range) f25%-50% range) «25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Reach: (# of consumers reached in PxM / category shoppers in PxM) 2. Retailer Category Presentation Effectiveness Indicators:

- Retailer Category Presentation Specification

Calculation of Effectiveness Data for each Retailer Category Presentation

Definition of Retailer Category Presentation Effectiveness Parameters

Retailer Category Presentation Specification

Presentation Specification Difference vs.

Pres.X Pres.Ref Avg.Cat. Pres.Ref Avg.Cat.

Target Audience: Share of Total Retailer Contacts: Base Size:

Retailer Assortment

- Brand Assortment Share: |

- Private Label Assortment Share: | - Category Breath (Choice): |

- Category Depth (Sizes): |

Avg. Retailer Brand/Sku Pricing

- Avg. Purchase Price: - Avg. Regular Price:

- Avg. Promo Price:

Retailer Display Performance

- Retailer Display Productivity: |

Retailer Promotion

- Promotional Pressure |

- price promotion |

- 'special pack' promotion |

Effectiveness Data for each Retailer Category Presentation

The effectiveness of each Retailer Category Presentation is determined as follows:

1) measure the impact among those exposed x-times to the Retailer Presentation

2) measure the impact of Retailer Presentation Reference among 100 of the same target group

4) compare the impact delta of the Retailer Presentation vs. that of other presentations

Presentation Impact(*) in PxM:

10 Pres.X Pres.Ref Delta (=Pres.X/Pres.Ref.*100)

Target Audience:

Share of Total Retailer Contacts:

Base Size:

15

Retailer Purchase Volume: Performance vs. Category Avg.**

Purchase Share: 20 Performance vs. Category Avg.

Penetration:

Performance vs. Category Avg.

25 Loyalty:

Performance vs. Category Avg.

Shopping Frequency: __π Performance vs. Category Avg.

(Re)Purchase Potential:

- Retailer Share of Category Prospects Performance vs. Category Avg.

35 - Retailer Purchase Inclination Performance vs. Category Avg.

- Retailer Churn

.„ Performance vs. Category Avg.

Retailer Interest: - Retailer Share of Mind Performance vs. Category Avg.

45 - Retailer "Interest"

Performance vs. Category Avg.

- Retailer Shopper's Competitive Scope ,_π Performance vs. Category Avg.

(**) Retailer Presentation Performance (Delta) vs. Avg. Category Presentation Performance:

55

T>75% range) f50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) 0 Effectiveness Data for each Retailer Category Presentation

1) measure the impact among those exposed x-times to the Retailer Presentation

Presentation ImpactC*) in PxM: Pres.X Pres.Ref Delta (=Pres.X/Pres.Ref.*100)

Target Audience:

Share of Total Retailer Contacts:

Base Size:

Retailer User Profile: Category Needs:

Category Brand Scope: Choice Performance vs. Category Avg.**

Category Retailer Scope: Price Performance vs. Category Avg.

Avg. Category Basket Size: Sizing Performance vs. Category Avg.

Premium Quality inclination: Quality Performance vs. Category Avg.

Promotion Responsiveness: Promotion Performance vs. Category Avg.

Innovation Responsiveness: Innovation Performance vs. Category Avg.

Retailer Communication Effectiveness:

- Retailer Impact Performance vs. Category Avg.

- Retailer Conversion Performance vs. Category Avg.

- Retailer Purchase Impulse Performance vs. Category Avg.

(**) Retailer Presentation Performance (Delta) vs. Avg. Category Presentation Performance: f>75% range) (50%-75% range) f25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Definition of Effectiveness Parameters for each Retailer Category Presentation

Base Test Leg: Category Shoppers exposed x-times to Retailer Presentation X in PxM Base Ctrl Leg: Category Shoppers exposed to Retailer Presentation Reference in PxM

Retailer Share:

Retailer Penetration (or Shopper Base): %

(those who have made retailer purchase in PyM with y = ((c+0.25*s) avg. purch. freq.)) / (those who have made category purchase in PyM with y =((c+0.25*s* avg. purch. freq.))

(with c= # of purchase cycles)

Shopper Base Loyalty:

Brand Loyalty Index: PyM retailer purchase share/retailer penetration

% loyal buyers (retailer share > 75%) % switchers (retailer share 75% - 25% ) % occasional buyers (retailer share< 25% > 0%)

% non-buyers (retailer share= 0%)

(y ⁼ ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Retailer Shopping Frequency:

Retailer Shopping Frequency in PyM/c:

- Retailer Share of Category Prospects: ["Share of those likely to buy a category item"] (those with brand research act in PxM/those with category research act in PxM) - Retailer Purchase Inclination: ["Retailer Purchase Likelihood"]

(# brand purchase acts/ total # of category shopping events)

- Retailer Churn: ["% of existing customers who have ceased buying the retailer"] (# of attritors in PyM / # of users in PyM with y = ((c+0.25*s) avg. purch. freq))

Retailer Interest:

- Retailer Share of Mind in PxM (% of category shopping events with retailer shopping act)

- Retailer "Interest" in PxM/c: (# of retailer research acts/# of category retailer research acts) - Retailer Shopper's Competitive Scope in PxM/c:

(avg. # of different retailer presentations accessed per shopping event) Definition of Effectiveness Parameters for each Retailer Category Presentation

Retailer Category Shopper Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [Importance of "assortment"]: Choice

Category Retailer Scope in PxM/c: [Importance of "value-for-money"]: Price

Avg. Category Basket Size in PxM/c: [Importance of "small/large packs"]: Sizing

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Promotion Responsiveness in PxM/c: [Importance of "deals"] : Promotion

Innovation Responsiveness in PxM/c: [Importance of "news"]: innovation

(avg. time since product launch of product presentations accessed by the consumer) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Definition of Effectiveness Parameters for each Retailer Category Presentation

Retailer Communication Effectiveness: - Retailer Impact in PxM/c: ["Retailer Purchase Intent"]

Measures likelihood that consumer buys after a single retailer presentation research exposure.

- Retailer Conversion in PxM/c: ["Retailer Proposition Appeal/Clarity"]

(# of brand purchase acts / # of brand shopping acts) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Measures the retailer presentation exposure required for a single purchase act.

- Retailer Purchase Impulse in PxM/c: ["Retailer Purchase Rush"]

(Retailer Shopping Duration / Retailer Shopping Acts / retailer purch. incl.) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

3. Retailer Category Ad Effectiveness Indicators:

- Calculation of Effectiveness Data for each Retailer Category Ad

- Definition of Effectiveness Parameters for each Retailer Category Ad

Effectiveness Data for each Retailer Category Ad

The effectiveness of each Retailer Category Ad is determined as follows: 1) measure the impact among those exposed x-times to the Retailer Category Ad 5 2) measure the impact of no Retailer Category Ad among 100 consumers of the same target

4) compare the impact delta of the Retailer Category Ad vs. that of other ads.

Ad ImpactC*) in PxM: 10 Ad.X Ad.Ref.0 Delta (=Ad.X/Ad.Ref.0*100)

Target Audience: Share of Voice:

Base Size:

15

Retailer Purchase Volume Performance vs. Category Avg.**

Purchase Share: 20 Performance vs. Category Avg.

Penetration:

Performance vs. Category Avg.

25 Loyalty:

Performance vs. Category Avg.

Shopping Frequency: __n Performance vs. Category Avg.

(Re)Purchase Potential:

- Retailer Share of Category Prospects Performance vs. Category Avg.

35 - Retailer Purchase Inclination Performance vs. Category Avg.

- Retailer Churn

₄₀ Performance vs. Category Avg.

Retailer Interest:

- Retailer Share of Mind Performance vs. Category Avg.

45 - Retailer "Interest"

Performance vs. Category Avg.

- Retailer Shopper's Competitive Scope _<-„ Performance vs. Category Avg.

(*) Impact is only measured among those that have been exposed to the Retailer Ad in PxM

(**) Retailer Ad Performance (Delta) vs. Avg. Category Brand Ad Performance:

(>75% range) f50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s)

60 Effectiveness Data for each Retailer Category Ad

4) compare the impact delta of the Retailer Category Ad vs. that of other ads.

Ad ImpactC*) in PxM: 10 Ad.X Ad.Ref.0 Delta (=Ad.X/Ad.Ref.0*100)

Target Audience: Share of Voice: Base Size:

15 Retailer Shopper Profile: Category Needs:

Category Brand Scope: Choice Performance vs. Category Avg.**

20 Category Retailer Scope: Price Performance vs. Category Avg.

Avg. Category Basket Size: Sizing _c. Performance vs. Category Avg.

Premium Quality inclination: Quality Performance vs. Category Avg.

Promotion Responsiveness: Promotion 30 Performance vs. Category Avg.

Innovation Responsiveness: Innovation Performance vs. Category Avg.

35 Retailer Communication Effectiveness:

- Retailer Impact Performance vs. Category Avg.

- Retailer Conversion

40 Performance vs. Category Avg.

- Retailer Purchase Impulse Performance vs. Category Avg.

45 .

(*) Impact is only measured among those that have been exposed to the Retailer Ad in PxM „ (**) Retailer Ad Performance (Delta) vs. Avg. Category Retailer Ad Performance: r>75% range) f50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Definition of Effectiveness Parameters for each Retailer Category Ad

Base Test Leg: Category Shoppers exposed x-times to Retailer Category Ad X in PxM Base Ctrl Leg: 100 Category Shoppers of the same target not exposed to any Retailer Cat. Ad

Retailer Share: - Retailer Volume Share: % (Retailer Volume in PxM / Category Volume in PxM)

- Retailer Purchase Share: % (Retailer Spending in PxM / Category Spending in PxM)

Retailer Penetration (or Shopper Base): % (those who have made retailer purchase in PyM with y = ((c+0.25*s) avg. purch. freq.)) /

(those who have made category purchase in PyM with y =((c+0.25*s* avg. purch. freq.))

(with c= # of purchase cycles) Shopper Base Loyalty:

Brand Loyalty Index: PyM retailer purchase share/retailer penetration

% loyal buyers (retailer share > 75%) % switchers (retailer share 75% - 25% )

% occasional buyers (retailer share< 25% > 0%) % non-buyers (retailer share= 0%)

(y = ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Retailer Shopping Frequency:

Retailer Shopping Frequency in PyM/c:

((y = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

(Re)Purchase Potential (or (Re)Trial Potential):

- Retailer Share of Category Prospects: ["Share of those likely to buy a category item"] (those with brand research act in PxM/those with category research act in PxM)

- Retailer Purchase Inclination: ["Retailer Purchase Likelihood"]

(# brand purchase acts/ total # of category shopping events)

Retailer Interest:

- Retailer Share of Mind in PxM (% of category shopping events with retailer shopping act) - Retailer "Interest" in PxM/c: (# of retailer research acts/# of category retailer research acts)

- Retailer Shopper's Competitive Scope in PxM/c:

(avg. # of different retailer presentations accessed per shopping event) Definition of Effectiveness Parameters for each Retailer Category Ad

Retailer Category Shopper Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [importance of "assortment"]: Choice

Category Retailer Scope in PxM/c: [Importance of "value-for-money"]: Price

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Premium Quality Inclination in PxM/c: [Importance of "image"]: Quality

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

Innovation Responsiveness in PxM/c: [Importance of "news"]: Innovation

(avg. time since product launch of product presentations accessed by the consumer) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Definition of Effectiveness Parameters for each Retailer Category Ad

- Retailer Conversion in PxM/c: ["Retailer Proposition Appeal/Clarity"]

- Retailer Purchase Impulse in PxM/c: ["Retailer Purchase Rush"]

4. Retailer Category Promotion Effectiveness Indicators:

- Calculation of Effectiveness Data for each Retailer Category Promotion

- Definition of Effectiveness Parameters for each Retailer Category Promotion

Effectiveness Data for each Retailer Category Promotion

The effectiveness of each Retailer Category Promotion is determined as follows: 1) measure the impact among those exposed x-times to the Retailer Category Promotion 5 2) measure the impact of no Retailer Category Promotion among 100 of the same target group

4) compare the impact delta of the Retailer Category Promotion vs. that of other promotions.

Promotional Impactf*) in PxM: 10 Prom.X Prom.Ref.O Delta f=Prom.X/Prom.Ref.0*100)

Target Audience: Reach:

Base Size:

15

Retailer Purchase Volume Performance vs. Category Avg.**

Purchase Share: 20 Performance vs. Category Avg.

Penetration:

Performance vs. Category Avg.

25 Loyalty:

Performance vs. Category Avg.

Shopping Frequency: »_n Performance vs. Category Avg.

(Re)Purchase Potential:

- Retailer Share of Category Prospects Performance vs. Category Avg.

35 - Retailer Purchase Inclination Performance vs. Category Avg.

- Retailer Churn

.„ Performance vs. Category Avg.

Retailer interest:

- Retailer Share of Mind Performance vs. Category Avg.

45 - Retailer "Interest"

Performance vs. Category Avg.

- Retailer User's Competitive Scope _sn Performance vs. Category Avg.

(*) Impact is only measured among those exposed to the Retailer Category Promo in PxM

(**) Retailer Promo Performance (Delta) vs. Avg. Category Retailer Promo Performance:

55 r>75% range) (50%-75% range) (25%-50% range) (<25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s)

60 Effectiveness Data for each Category Retailer Promotion

The effectiveness of each Retailer Category Promotion is determined as follows: 1) measure the impact among those exposed x-times to Retailer Category Promotion 5 2) measure the impact of no Retailer Category Promotion among 100 of the same target group

Target Audience: Reach: Base Size:

15 Retailer Shopper Profile: Category Needs:

Category Brand Scope: Choice Performance vs. Category Avg.**

20 Category Retailer Scope: Price Performance vs. Category Avg.

Avg. Category Basket Size: Sizing » - Performance vs. Category Avg.

Premium Quality Inclination: Quality Performance vs. Category Avg.

Promotion Responsiveness: Promotion 30 Performance vs. Category Avg.

Innovation Responsiveness: Innovation Performance vs. Category Avg.

35 Retailer Communication Effectiveness:

- Retailer impact Performance vs. Category Avg.

- Retailer Conversion

40 Performance vs. Category Avg.

- Retailer Purchase Impulse

Performance vs. Category Avg.

45 . .

^ (**) Retailer Promo Performance (Delta) vs. Avg. Category Retailer Promo Performance:

(>75% range) (50%-75% range) (25%-50% range) «25% range)

Strong Above Average Below Average Weak

(d >avg.+25%*s) (avg.<d>avg.+25%*s) (avg.-25%*s<d>avg.) (d<avg.-25%*s) Definition of Effectiveness Parameters for each Retailer Category Promotion

Base Test Leg: Category Shoppers exposed x-times to Retailer Category Promo X in PxM Base Ctrl Leg: 100 Category Shoppers of same target not exposed to any Retailer Cat. Promo

(with c= # of purchase cycles) Shopper Base Loyalty:

Brand Loyalty Index: PyM retailer purchase share/retailer penetration

% loyal buyers (retailer share > 75%) % switchers (retailer share 75% - 25% )

(y ⁼ ((c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Retailer Shopping Frequency:

Retailer Shopping Frequency in PyM/c:

((y = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

(Re)Purchase Potential (or (Re)Trial Potential):

- Retailer Purchase Inclination: ["Retailer Purchase Likelihood"]

(# brand purchase acts/ total # of category shopping events)

Retailer interest:

- Retailer Shopper's Competitive Scope in PxM/c:

(avg. # of different retailer presentations accessed per shopping event) Definition of Effectiveness Parameters for each Retailer Category

Retailer Category Shopper Profile: Category Shopping Habits/Needs

Category Brand Scope in PxM/c: [Importance of "assortment"]: Choice

Category Retailer Scope in PxM/c: [Importance of "value-for-money"]: Price

((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles)

Premium Quality Inclination in PxM/c: [Importance of "image"]: Quality

Promotion Responsiveness in PxM/c: [Importance of "deals"]: Promotion

innovation Responsiveness in PxM/c: [Importance of "news"]: Innovation

(avg. time since product launch of product presentations accessed by the consumer) ((x = (c+0.25*s) avg. purch. freq.) with c= # of purchase cycles) Definition of Effectiveness Parameters for each Retailer Category Promotion

Base Test Leg: Category Shoppers x-times exposed to Retailer Category Promo X in PxM Base Ctrl Leg: 100 Category Shoppers of same target not exposed to any Retailer Cat. Promo

- Retailer Conversion in PxM/c: ["Retailer Proposition Appeal/Clarity"]

- Retailer Purchase Impulse in PxM/c: ["Retailer Purchase Rush"]

Appendix III

Iawai.net 'measures' the effectiveness of each Iawai.net ad contact, benchmarks it against the effectiveness of a 'mass' advertising contact and automatically reflects the performance difference in its ad pricing.

I) Iawai.net Advertising Rate Pricing Principles

II) Iawai.net's 'Advertising Rates' are beneficial for both advertisers and the portal/media companies

III) Iawai.net Effectiveness Measurement Methodology

IV) Iawai.net Advertising Rate Calculation Method

I) Iawai.net Advertising Rate Pricing Principles

- New Digital Media should deliver a better ROI for advertisers than traditional 'mass' advertising.

- The calculation of the Ad Rates of the new Digital Media should be transparent and adapt dynamically according to the advertiser's target audiences and 'measurable' advertising performance benchmarks versus 'mass media' to provide advertisers with a better ROI under all circumstances.

- The effectiveness of each of the different types of advertising contacts in the new Digital Media should be automatically benchmarked vs. the effectiveness 'mass' media in order to 'objectively' reflect any 'factual' performance difference 'fairly' in the ad rate pricing of the new Digital Media.

- The Ad Rates of the new Digital Media should be based on the media planning and measurement principles, that are commonly accepted throughout the world of 'mass' advertising and media.

- The Ad Rates should also reflect that the new Digital Media allow to target ads to consumers based on 'holistic purchase based' profiles as well as to measure the impact of advertising on sales.

- The Ad Rates of the new Digital Media should be sufficiently high to offset an expected ad volume decrease by higher pricing, avoiding the cannibalization of the advertising market in the long term.

- The Ad Rates of the new Digital Media should be sufficiently attractive for telecom and media companies to develop profitable personal digital media services and the required infrastructure.

- To justify charging 'premium' ad rates, the new digital media should leverage its unique technical capabilities to deliver a higher ROI for advertisers: i.e. leveraging capabilities

- to make it more cost efficient to reach 'specific particularly interesting narrow target audiences',

- to adapt advertising messages according to the needs/behavior of individual target audiences,

- to measure the 'effect of ads on sales', allowing to focus investments on 'high yield' ads only.

- The Ad Rates of the new Digital Media should be set by the service providers of personal services. II) Iawai.net's 'Advertising Rates'are beneficial for both advertisers and portal/media companies

1) The Iawai.net Ad Rates are transparent and adapt dynamically according to the advertiser's target audiences and 'measurable' advertising performance benchmarks versus 'mass media' to provide advertisers with a better ROI under all circumstances.

Examples:

Iawai.net (1): High effectiveness of Iawai.net advertising 3 'proven' ads for 2 target groups Iawai.net (2): High effectiveness of Iawai.net advertising • 4 'proven' ads for 3 target groups Iawai.net (3): High effectiveness ofIawai.net advertising • 1 'proven' ad for all category buyers Iawai.net (4): Low effectiveness ofIawai.net advertising 3 'proven' ads for 2 target groups

** effectiveness premium: 50% ofiawai.net effectiveness factor 2) The effectiveness of each of the different types of Iawai.net advertising contacts is automatically benchmarked vs. the effectiveness 'mass' media in order to 'objectively' reflect any 'factual' performance difference 'fairly' in the ad rate pricing of Iawai.net advertising.

a) A Consumer Consultation of Manufacturer 'Product Info' in Portal Shopping Registry

b) A Consumer Consultation of 'Retailer Specials' in Portal Shopping Registry

c) A Consumer Ad Exposure in a Personal Digital News/Music/Video-on-Demand Service

The advertising rates depend on the type of Personal Digital News/Entertainment Service:

Personal Digital News Services: 'Print Ad' Format incoφorated in the news articles

Personal Digital Music Services: 'Audio Ad' Format incoφorated as 'radio-like ad block'

Personal Digital VOD Services: 'Video Ad' Format as a 'TV-like ad'

Personal Digital Game Services: 'Sponsor Banner' Format as is common in sponsoring

Personal Digital Info Services (weather, route, stock market info): 'Print/Banner Ad' Format

d) A Consumer Ad Exposure in a Personal Shopping Service

3) The Iawai.net Ad Rates are sufficiently high to offset an expected ad volume decrease by higher pricing, avoiding the cannibalization of the advertising market in the long term.

The below example, that illustrates a situation where digital media has replaced the 'mass media', shows that Iawai.net can eventually compensate an ad volume decrease of 50% by premium priced ads that deliver a higher ROI for advertisers. If the Iawai.net ad effectiveness is stronger than assumed in the example and if this causes the ad volume to decline beyond the 50%, Iawai.net C/M ad rates are automatically increased to offset the volume loss and to reflect the higher ROI. This means that the Iawai.net pricing mechanism ensures that the market will grow beyond the current level in $ turnover, while simultaneously driving ROI for advertisers terms independent of ad volume and effectiveness.

The conversion to digital media/advertising will obviously only happen gradually as advertisers commit more dollars and as ads on VOD/ Music Services become feasible with more 'broadband' connections.

Advertising Market: Overview of Ad Spending on Traditional Media

Sources: Ad Age; Zenith Media; The Economist

4) The Iawai.net Ad Rates are sufficiently attractive for telecom and media companies to develop profitable personal digital media services and to build the required infrastructure.

Conclusions: 1 ) In an narrowband environment Iawai.net is capable of generating a maximum of $ 19 per Iawai.net subscriber on a monthly basis. This assumes that the advertising spending on offline newspapers/ magazines is transfeπed to digital newspaper/magazines and that Iawai.net's Shopping Services with its 'Product Info' and its 'Retailer Specials' generate another additional $1.75 per subscriber on a monthly basis. This assumes that consumers will do all their news reading and product and retailer research online; an assumption that is unrealistic. Change of consumer habits will only happen partially and gradually. Ad revenues are, however, sufficiently high to cover the news/magazine content cost and will increase as online consumption of news and online research grows.

2) In a broadband environment Iawai.net is capable of serving ads on digital VOD/Music Services. This means that revenues can be increased to a maximum of $44 per Iawai.net subscriber on a monthly basis. This assumes that the advertising of offline radio and TV is transferred to digital VOD/Music Services and Iawai.net's Shopping Services with its 'Product Info' and its 'Retailer Specials' adding another incremental $1.75 per subscriber on a monthly basis. This assumes that consumers will do all their news/music consumption and product and retailer research online; an assumption that is unrealistic. Change of consumer habits will only happen partially and gradually. Ad revenues are, however, sufficiently high to cover the news/magazine/VOD/music content cost and will increase as online consumption of news and online research grows. 4) The Iawai.net Ad Rates are sufficiently attractive for telecom and media companies to develop profitable personal digital media services and to build the required infrastructure. Remarks on the below table:

1) The Iawai.net revenues assumptions come from the table on the previous page.

2) The Yahoo and AOL revenues estimates per subscriber come from press clippings

3) The monthly cost of personal digital news/entertainment content are derived from:

- a $50 monthly fee for a home pay TV service; - a $10 monthly fee for Real News/Music Streaming Service;

- a $10-15 monthly fee per subscriber for unlimited access to music;

- a $100 dollar yearly newspaper subscription fee.

4) Consumer pays a $50 monthly subscription fee for broadband access.

5) Consumer gets a reward for doing their purchases on Iawai.net in the form a free 'info' on their mobile phones. The cost will be carried by the provider of the digital news/entertainment service.

III) Iawai.net Advertising Effectiveness Measurement Methodology

Iawai.net reaches consumers via different types of advertising contacts, each with its own effectiveness level, which is measured automatically, in order to reflect it in the ad rate pricing.

a) A Consumer Consultation of Manufacturer 'Product Info* in Portal Shopping Registry

The effectiveness of a 'Product Info' Registry contact varies largely by product category. In the case of 'high involvement' home electronics consumer durables or cars for example it can be expected that consumers consult the 'Product Info' Registry to research their potential product alternatives every time before they make a purchase. In the case of 'low involvement' fast moving consumer goods it can be expected that consumers consult the 'Product Info' Registry only occasionally for example if they are unhappy with their current Brand choice or if they are new to the category or not at all in the case low priced commodities. The importance of the 'Product Info' Registry cannot be ignored for fast moving consumer goods although the general brand image constructed via off-line media is a more determining factor for the choice of the consumer. In the case of financial services products a single consultation of the 'Product Info' Registry can determine the choice of a consumer for years to come. This means that the C/M Ad Rates for a consultation of the 'product info' registry should vary per category depending on the effectiveness/ROI of the contact for the advertiser and on the 'different size/animation' formats used for the 'product presentations' (KB's). A variable C/M Ad Rate fee per consultation allows advertisers to pay for contacts that translate into sales and not to pay if there are no contacts.

For each category the ad effectiveness of the 'Product Info' contacts is calculated as follows:

1) measure the Brand sales among the consumer group, that has access to the Brand 'Product Info' Registry as well as the % of users and # of times that the 'Product Info' Registry was accessed. 2) measure the Brand sales among a 'mass advertising' effectiveness benchmark reference group, with no access to the Brand 'Product Info' Registry (see mass benchmark group description below)

3) calculate the Performance Index by dividing the brand sales to those that accessed 'Product Info' Registry in the PxM by the brand sales to those that didn't have access to the 'Product Info'

4) weigh the Performance Index of the Brand 'Product Info' Registry by multiplying the index with the # of consumer Brand contacts and dividing them by the # of consumer category brand contacts. 5) calculate the 'Overall Category Product Info Registry' Performance Index by repeating the above steps 1-4 for all brands of the category and adding up the weighted Brand Performance Index scores. b) A Consumer Consultation of 'Retailer Specials' in Portal Shopping Registry

The C/M Ad Rates for a consumer consultation of the 'product info' registry should depend on the effectiveness/ROI of the contact for the advertiser and on the 'different size/animation' formats used for the 'retailer specials presentations' (KB's). A variable C/M Ad Rate fee per consultation allows advertisers to pay for contacts that translate into sales and not to pay if there are no contacts.

The ad effectiveness of the 'Retailer Specials' contacts is calculated as follows: 1) measure the Retailer sales among the consumer group, that has access to the Retailer 'Specials' Registry as well as the % of users and # of times that the Retailer 'Specials' Registry was accessed.

2) measure the Retailer sales among a 'mass advertising' effectiveness benchmark reference group, with no access to the Retailer 'Specials' Registry (see mass benchmark group description below)

3) calculate the Performance Index by dividing the sales to those that accessed 'Weekly Specials' Registry in the PxM by the sales to those that didn't have access to the 'Weekly Specials' 4) weigh the Performance Index of the 'Specials' Registry by multiplying the index with the # of consumer contacts with a specific retailer and dividing them by the # of retailing contacts.

5) calculate the Overall Retailer Specials Registry' Performance Index by repeating the above steps 1-4 for all retailers and adding up the weighted Retailer Performance Index scores.

Because Iawai.net ads can be personalized and targeted to consumers based on holistic purchase based shopping profiles and because its effect on sales can be measured continuously and instantaneously, it can be assumed that the effect on sales of a Iawai.net 'push' ad message is higher than that of a classical generic mass 'push' ad message, that is addressed to 'random' consumers. The effectiveness of a consumer contact for the advertiser depends on the advertising format. The C/M Ad Rates for a consumer contact should therefore vary according to advertising format.

The effectiveness of the 'ad' contacts is calculated as follows for each of the Personal Digital News Entertainment Service ad formats: 1) measure Brand/Retailer sales among consumers, exposed x times to an ad in PxM

2) measure Brand/Retailer sales among 100 consumers of same target, that received no ad in PxM

3) calculate the Ad Performance Index by dividing the Brand/Retailer sales to those exposed to an ad in the PxM by the Brand/Retailer sales of those that were not exposed to an ad in the PxM

4) weigh the Performance Index of the Personal Digital News/Entertainment ad by multiplying the index with the # of contacts of a specific ad and dividing it by the total # of ad contacts. 5) calculate the 'Overall Personal Digital News/Entertainment' Performance Index by repeating the above steps 1-4 for all Brand/Retailer ads and adding up the weighted Ad Performance Index scores.

d) A Consumer Ad Exposure in a Personal Shopping Service

Because Iawai.net ads can be personalized and targeted to consumers based on holistic purchase based shopping profiles, because these ad can be served as consumers are busy shopping/researching stores/products via their personal digital portal 'shopping services' and finally because its effect on sales can be measured continuously and instantaneously, it can be assumed that the effect on sales of this type ofIawai.net 'push' ad message is higher than that of a classical generic mass 'push' ad message, which is addressed to consumers at a moment when they are not involved with shopping. The effectiveness of the 'Personal Shopping Service' ad contacts is calculated as follows:

1) measure Brand/Retailer sales among consumers, exposed x times to an ad in PxM

3) calculate the Ad Performance Index by dividing the Brand/Retailer sales to those exposed to an ad in the PxM by the Brand/Retailer sales to those that were not exposed to an ad in the PxM

4) weigh the Performance Index of the Personal Digital Shopping Service ad by multiplying the index with the # of contacts of a specific ad and dividing it by the total # of ad contacts.

5) calculate the 'Overall Personal Digital Shopping Service' Performance Index by repeating the above steps 1-4 for all Brand/Retailer ads and adding up the weighted Ad Performance Index scores.

The effectiveness of 'mass' ads as a benchmark for assessing the effectiveness of Iawai.net ads

The effect on sales of a Iawai.net ad message is higher than that of a classical 'mass' ad message.

To determine how much more effective, we need to measure not only the effectiveness of the Iawai.net ad messages but also the effectiveness of the different 'mass' ad messages formats.

To be able to measure the effectiveness of the different 'mass' ad message formats, each Iawai.net advertiser member will be asked to 'upload' its available 'mass' TV, Radio, Print and Banner ads. In return they will get a 'free' effectiveness study of their 'mass' TV, Radio, Print and Banner ads.

The testing method of these 'mass' TV, Radio and Print ads will work as follows: a) A small representative group ofIawai.net users will be selected randomly to act as the 'mass advertising' effectiveness benchmark reference group, that will have no access to the 'product info' registry nor the 'retailer specials' registry during a test period and instead of personal Iawai.net ads will receive 'mass' TV/Radio/Print/Banner ads in their Personal Digital Video-on Demand/Music/News Services and no ads at all in their Personal Shopping Service.

b) The effectiveness each of the 'mass' TV, Radio, Print, Banner ads will be determined as follows: (The ad effectiveness calculations will follow the 'standard' Iawai.net measurement methodology)

1) measure the Brand/Retailer sales among 100 consumers, exposed x times to a 'mass' ad in PxM

3) calculate the Ad Performance Index by dividing the Brand/Retailer sales of those exposed to an ad in the PxM by the Brand/Retailer sales of those that were not exposed to an ad in the PxM

4) weigh the Performance Index of the 'mass' ad by multiplying the index with the # of ad contacts of a specific Brand/Retailer in the PxM and dividing it by the total # of ad contacts in PxM.

5) calculate the 'Overall Mass Advertising' Performance Index by repeating the above steps 1-4 for all Brand/Retailer ads and adding up the weighted Ad Performance Index scores.

As soon as the 'Overall Mass Advertising' Performance Index for the TV/Radio/Print formats is determined, we can use the Performance Index scores of these 'mass' ad formats as a reference benchmark to measure the relative performance superiority of the different Iawai.net ad formats.

The Iawai.net Effectiveness Index is obtained by benchmarking the Performance Index of the different Iawai.net ad formats against the Performance Index of the different 'mass' ad format references as follows: a) A Category 'Product Info' Registry Contact vs. Brand 'Mass Print Ad' Contact as Reference b) A 'Retailer Specials' Registry Contact vs. Retailer 'Mass Print Ad' Contact as Reference c) An Ad Exposure in a Personal Digital News/Music/Video-on-Demand Service: - 'Personal Digital News Services Iawai.net Print Ad' vs. 'Mass Print Ad' as Reference

'Personal Digital Music Services Iawai.net Audio Ad' vs. 'Mass Radio Ad' as Reference 'Personal Digital VOD Services Iawai.net Video Ad' vs. 'Mass TV Ad' as Reference - (Personal Digital Game Services Iawai.net 'Sponsor Banner' vs. 'Mass Banner' as Reference - Personal Digital Info Services Iawai.net Sponsor Banner' vs. 'Mass Banner' as Reference) d) An Ad Exposure in a Personal Shopping Service vs. 'Mass Banner Ad' as Reference IV) Iawai.net Advertising Rate Calculation Method

The Iawai.net Ad Rates are dynamic and vary according to the advertising target group and the ROI that the medium can achieve for the advertiser. The calculation is based on 4 parameters:

- 'Mass Media C/M (target group)'

- 'Iawai.net Targeting Bonus'

- 'Iawai.net Effectiveness Premium' - 'Pricing Differentiation Index'

Mass Media C/M (target group):

The starting point of the calculation is the Mass Media C/M for the consumer target audience, that the advertiser would like to reach with his campaign, which can consist of multiple ad executions.

For example if the C/M for a 'Mass Media Print' Campaign is $0.018/M. If an advertiser is interested in confining his campaign to reaching his 'potential customer base' only, and if this conesponds to an 'effective reach' of 25% of the total audience that is reached with a 'Mass Media Print' Campaign, then this advertiser is wasting 75% of his advertising expenditures. The Mass Media C/M calculated on his 'potential customer base' target group is $0.018/M *4 = $0.072/M.

Iawai.net Targeting Bonus:

The Targeting Bonus corrects the Mass Media C/M for the specific consumer target group downward and makes it more cost effective to reach this group via targeted personal iawai.net advertising than via 'mass' advertising. To encourage advertisers 'financially' to define 'narrow target audiences' for their advertising campaigns, Iawai.net provides a larger Targeting Bonus to a campaign with a 'low' effective reach than a campaign with a 'high' effective reach . The size of Targeting Bonus depends on the effective reach of the campaign and the level of the Targeting Bonus Ceiling. The Targeting Bonus is determined as follows:

Iawai.net Targeting Bonus = ( 1 - 'effective reach' of campaign ) * Targeting Bonus Ceiling

For example if the Mass Media C/M for a Mass Media Print Campaign on the above mentioned target group (with an 'effective reach' of 25%) is $0.072/M (and if lawai.net sets its Targeting

Bonus Ceiling at 30%), it's campaign Targeting Bonus is 23%, resulting in a the Iawai.net C/M of $0.055/M. For this campaign this means a Iawai.net cost advantage of 23% vs. 'mass' advertising.

Iawai.net Effectiveness Premium: The Effectiveness Premium corrects the Mass Media C/M for the consumer target group upward depending on the 'measured' difference in advertising effectiveness between iawai.net and 'mass' advertising media. The Effectiveness Premium is calculated separately for the different types of advertising and 'product info'/'weekly specials' contacts available through Iawai.net. If, for example, with Iawai.net's personalization and effectiveness measurement capabilities, advertisers can improve their advertising effectiveness and achieve a two times higher return on advertising investment with Iawai.net than with 'mass media' and iflawai.net decides that this justifies asking advertisers an C/M 'effectiveness premium' of 50%, the Iawai.net C/M would result being $0.083/M, providing advertisers with a 50% 'effectiveness bonus' allowing advertisers to achieve a 73% higher advertising ROI with Iawai.net than with 'mass' advertising. 'Pricing Differentiation Index':

Advertising Rate Pricing is set by the portal/media companies and not by Iawai.net. To obtain the final Advertising Rate Pricing the portal/media companies will use the above used calculation methodology and adjust the outcome with a 'Pricing Differentiation Index'.

The 'Price Index' of the medium reflects the premium or discount that the portal/media company thinks that it can sustain in the competitive media market place. To help guide their decision the portal/media company can access the advertising Effectiveness Performance Indexes of the different Personal Shopping & Digital Media Services Ads and 'product info'/'retailer weekly specials' contacts versus the average Effectiveness Performance Levels of their 'mass' media references.

The Final Iawai.net Advertising Rates are thus calculated as follows:

Final Advertising Rate for Personal Digital Media Service X:

= Mass Media C/M (target group) * (1 -Iawai.net Targeting Bonus) * Iawai.net Effectiveness Premium

* 'Pricing Differentiation Index' of the Personal Digital News/Music/Info/NOD Service X

Example: Assuming that the C/M for a Mass Media Print Campaign is $0.018/M and that an advertiser defines his target audience as 'potential customer base' and if this is 25% of the total audience that is normally reached with an Mass Media Print Campaign, this means that the Mass Media C/M for this target group is $0.018/M *4 = $0.072/M. Assuming a Targeting Bonus of 23% and a C/M effectiveness premium of 50%, the resulting Iawai.net C/M will be $0.083/M. If a Portal/Media Company A believes that it can sustain a 10% ad rate price premium vs. its competitors it will adjust the Iawai.net C/M upwards, resulting in a C/M of $0.091/M for each of the 500.000 consumers subscribed to the interactive services of portal/media company A. This in contrast to a C/M of $0.083/M for 300.000 consumers subscribed to Portal/Media Company B, that has decided it cannot price at a premium to competition, and to a C/M of $0.075/M for the 200.000 consumers subscribed to Portal/Media Company C, that decided to price at an discount of 10% vs. competition.

Iawai.net Ad Rates depend on the ad effectiveness and ROI for its advertisers

In order to calculate its Ad Rates, Iawai.net measures the Effectiveness Index of Iawai.net advertising and benchmarks this against the effectiveness 'mass' advertising.

As result of its personalization and effectiveness measurement capabilities, Iawai.net can achieve a higher effectiveness and return on investment for advertisers than 'mass' media. This makes it possible for media companies to charge a C/M 'effectiveness premium', whilst still allowing advertisers to achieve a higher advertising ROI with Iawai.net than with 'mass advertising.

The Iawai.net C/M Ad Rates and ROI Bonus for each Iawai.net contact is calculated as follows: a) A Consumer Consultation of Manufacturer 'Product Info' in Portal Shopping Registry 1) Multiply the 'Overall Category Product Info Registry' Performance Index by the # of consumers, that accessed the 'Product Info' Registry and divide this by the # of consultations per consumer

2) Take the 'Overall Mass Advertising' Performance Index of 'mass' brand print ads (1 exposure) 3) Calculate the 'Iawai.net Effectiveness Factor': Index on line 1) / Index on line 2) * 100

4) Determine the Iawai.net C/M 'Effectiveness Premium'/'Effectiveness Bonus' and 'ROI Bonus':

- 'Effectiveness Bonus' is set at x%

- 'Effectiveness Premium' = ('Iawai.net Effectiveness Factor' - 100) - 'Effectiveness Bonus'

- 'ROI Bonus' = 'Effectiveness Bonus'

5) Determine the Iawai.net C/M Ad Rate for a 'Product Info Registry' contact:

= 'Mass' Print Ad C/M * 'Effectiveness Premium' * Format Rate * Pricing Differentiation Index The Format Rate depends on the 'size/format' execution of the 'product presentation':

- it reflects the differences in 'size/animation' formats (# KB's) of 'product presentations'

- for the Basic/Regular formats a 'Digital Discount' applies (reflects cost savings of 'digitalization') b) A Consumer Consultation of Retailer 'Weekly Specials' in Portal Shopping Registry

1) Multiply the 'Overall Retailer Specials Registry' Performance Index by the # of consumers, that accessed the 'Retailer Specials' Registry and divide this by the # of consultations per consumer

2) Take the 'Overall Mass Advertising' Performance Index of 'mass' retailer print ads (1 exposure)

3) Calculate the 'Iawai.net Effectiveness Factor': Index on line 1) / Index on line 2) * 100

- 'Effectiveness Bonus' is set at x% - 'Effectiveness Premium' = ('Iawai.net Effectiveness Factor' - 100) - 'Effectiveness Bonus'

- 'ROI Bonus' = 'Effectiveness Bonus'

5) Determine the Iawai.net C/M Ad Rate for a Retailer 'Weekly Specials Registry' contact:

= 'Mass' Print Ad C/M * 'Effectiveness Premium' * Format Price * Pricing Differentiation Index

The Format Price depends on the 'size/format' execution of the 'retailer presentation': - it reflects the differences in 'size/animation' formats (# KB's) of 'retailer presentations' - for the Basic/Regular formats a 'Digital Discount' applies (reflects cost savings of 'digitalization') c) A Consumer Ad Exposure in a Personal Digital News/Music Video on Demand Service

1) Take the 'Overall Personal Digital News/Entertainment' Performance Index for:

- Personal Digital News Services 'Print Ad' Format

- Personal Digital Music Services: 'Audio Ad' Format

- Personal Digital VOD Services: 'Video Ad' Format - (Personal Digital Game Services: 'Sponsor Banner' Format

- Personal Digital Info Services (weather, route, stock market info): 'Print/Banner Ad' Format)

2) Take 'Overall Mass Advertising' Performance Index of 'mass' TV/Radio/Print/Banner Ads:

'Personal Digital News Services Iawai.net Print Ad' vs. 'Mass Print Ad' as Reference - 'Personal Digital Music Services Iawai.net Audio Ad' vs. 'Mass Radio Ad' as Reference

- 'Personal Digital VOD Services Iawai.net Video Ad' vs. 'Mass TV Ad' as Reference

- (Personal Digital Game Services Iawai.net 'Sponsor Banner' vs. 'Mass Banner' as Reference

- Personal Digital Info Services Iawai.net Sponsor Banner' vs. 'Mass Banner' as Reference)

3) Calculate the 'Iawai.net Effectiveness Factor': Index on line 1) / Index on line 2) * 100 4) Determine the Iawai.net C/M 'Effectiveness Premium'/'Effectiveness Bonus' and 'ROI

Bonus':

- 'Effectiveness Bonus' is set at x%

- 'Effectiveness Premium' = ('Iawai.net Effectiveness Factor' - 100) - 'Effectiveness Bonus' - 'ROI Bonus' = 'Targeting Bonus' + 'Effectiveness Premium'

5) Determine the Iawai.net C/M Ad Rate for a Digital News/Music/Video on Demand Service Ad: = 'Mass' TV Ad C/M*(l -Targeting Bonus)*Effectiveness Premium*Pricing Differentiation Index = 'Mass' Radio Ad C/M*(l-Targeting Bonus)*Effectiveness Premium*Pricing Differentiation Index = 'Mass' Print Ad C/M*(l -Targeting Bonus)* Effectiveness Premium*Pricing Differentiation Index (='Mass' Sponsoring C/M*(l -Target. Bonus)*Effectiveness Premium*Pricing Differentiation Index ='Mass' Sponsoring C/M*'(l-Target.Bonus)*Effectiveness Premium*Pricing Differentiation Index) The final C/M Ad Rate will be corrected according to the 'length/size' format of the ad execution:

- pricing will reflect the different time lengths (10, 20, 30 sec. etc) for Radio/TV - type spots

- pricing will reflect the 'different size and animation' formats of print ads and banner ads d) A Consumer Ad Exposure in a Personal Shopping Service

1) Take the 'Overall Personal Digital Shopping Service' Performance Index ofIawai.net

2) Take the 'Overall Mass Advertising' Performance Index of 'mass' banner ads (1 exposure)

- 'Effectiveness Bonus' is set at x%

- 'ROI Bonus' = 'Targeting Bonus' + 'Effectiveness Premium' 5) Determine the Iawai.net C/M Ad Rate for a Personal Shopping Service Ad:

= 'Mass' Print Ad C/M* (1 -Targeting Bonus)*Effectiveness Premium*Pricing Differentiation Index The final C/M Ad Rate will be corrected according to the 'length/size' format of the ad execution: - pricing will reflect the 'different size and animation' formats of print ads and banner ads

Illustration of the calculation of Iawai.net 'product info' C/M ad rates and ad volume

The here described calculation ofIawai.net 'product info' C/M is based on the previously described algorithms. The example illustrated in this section helps to illustrate the calculation methodology and bring alive the algorithms. It is also provides a theoretical calculation framework that gives 'rough' indicative estimates for feasible 'product info' C/M ad rates and volume levels. 1) Value of a 'product info' registry contact:

The advertising value of a contact of a consumer, who 'downloads' information from the 'product info' registry, is estimated to increase linearly with a decreasing buying penetration and purchase cycle time (the lower the penetration and the higher the purchase cycle time, the higher the advertising waste for reaching these customers through 'mass' advertising). 'Rough' estimates can be made using the following algorithms: a) value of an ad 'product info' registry contact for fast movers (e.g. groceries, clothing, toys): = 1 / penetration * product info' effectiveness factor * print C/M b) value of an ad 'product info' registry contact for durables (e.g. electronics, motors ,services):

= 1 / penetration / purchase cycle time (in yrs) * 'product info' effectiveness factor * print

C/M with the 'Mass' Print reference C/M of $0,018; with a 'product info' registry 'effectiveness factor' of 260;

( driving factors of communication effectiveness: 'ad personalization', 'effectiveness filtration', 'consumer pull' effect, 'while shopping' context, 'information/selling depth')

2) Iawai.net Targeting Bonus:

The advertising value of a reaching a consumer, who 'downloads' information from the Iawai.net 'product info' registry, needs to be discounted with the Targeting Bonus, to make it more cost efficient to reach a consumer via an Iawai.net 'product info' contact than via a 'mass' print contact. In the example described in this section we assume the Iawai.net Targeting Bonus to be 30%.

3) Effectiveness Premium of a 'product info' registry contact:

In the example we assume that the advertising efficiencies are split 50/50 between advertisers and media companies. This means an effectiveness C/M ad rate premium of 50% of the effectiveness factor: i.e. 50% of 260 = 80%.

4) Format Rates: format: Basic Regular Deluxe Super Deluxe Supreme

- features: pictures pictures anim.pictures anim.pictures + voice pictures + VOD

10 KB 100 KB 200 KB 1.5 MB 1.5 MB

- discount/premium: 1/20 (5) 10/20 (50) 20/20 (100) 22/20 (110) 24/20 (120)

5) 'Rough' Penetration, Buying, Research Frequency and Research Contact Estimates:

The penetration, buying, research frequency and research contact estimates are 'rough' and allow for a theoretical calculation framework, that gives 'rough' indicative estimates for 'product info' C/M ad rates and ad volume, assuming that consumers use Iawai.net for all research events. Remarks:

1) The buyer penetration, the # purchase acts per year, the # research events per year, the # brands researched and the # of research acts per Iawai.net subscriber are 'rough' estimates that reflect the offline habits of consumers. The revenues per Iawai.net member, that are derived from these parameter estimations, should therefore be seen as a 'rough revenue indication', that can deviate from the real value.

2) The table a assumes that consumers will do all their research of product on Iawai.net, an assumption that is not realistic. Change of consumer shopping habits will only happen partially and gradually. The revenue estimates per subscriber should therefore be seen as a maximum.

3) The Iawai.net 'Product Info' C/M contact rates in the below table were estimated using the Iawai.net 'Product Info' ad rate calculation framework as described on the previous page.

4) The Iawai.net C/M rate also depends on the assumption for the presentation format (iawai form) that was used to calculate the C/M rate with 'basic' being the cheapest and 'supreme' the most expensive presentation format.

Illustration of the calculation of Iawai.net 'retailer specials' C/M ad rates and ad volume

The here described calculation ofIawai.net 'retailer specials' C/M is based on the previously described algorithms. The example illustrated in this section helps to illustrate the calculation methodology and bring alive the algorithms. It is also provides a theoretical calculation framework that gives 'rough' indicative estimates for feasible 'retailer specials' C/M ad rates and volume levels.

1) Value of a 'retailer specials' registry contact:

The advertising value of a contact of a consumer, who 'downloads' information from the 'retailer specials' registry, is estimated to increase linearly with a decreasing buying penetration and purchase cycle time (the lower the penetration and the higher the purchase cycle time, the higher the advertising waste for reaching these customers through 'mass' advertising). 'Rough' estimates can be made using the following algorithms: a) value of an ad 'retailer specials' registry contact for fast movers (e.g. groceries, clothing, toys):

- I I penetration * product info' effectiveness factor * print C/M b) value of an ad 'retailer specials' registry contact for durables (e.g. electronics, motors, services):

C/M with the 'Mass' Print reference C/M of $0.018; with a 'product info' registry 'effectiveness factor' of 220;

( driving factors of communication effectiveness: 'ad personalization', 'effectiveness filtration', 'consumer pull' effect, 'while shopping' context, 'information/selling depth') 2) Iawai.net Targeting Bonus:

3) Effectiveness Premium of a 'retailer specials' registry contact:

In the example we assume that the advertising efficiencies are split 50/50 between advertisers and media companies. This means an effectiveness C/M ad rate premium of 50% of the effectiveness factor: i.e. 50% of 220 = 60%.

4) Format Rates: format: Basic Regular Deluxe Super Deluxe Supreme - features: pictures pictures anim.pictures anim.pictures + voice pictures + VOD

- discount/premium: 1/20 (5) 10/20 (50) 20/20 (100) 22/20 (110) 24/20 (120) 5) 'Rough' Penetration, Buying, Research Frequency and Research Contact Estimates:

The penetration, buying, research frequency and research contact estimates are 'rough' and allow for a theoretical calculation framework, that gives 'rough' indicative estimates for 'retailer specials' C/M ad rates and volume, assuming that consumers use Iawai.net for all 'specials' research events.

Remarks:

1) The buyer audience, the # purchase acts per year, the # research events per year, the # retailers researched and the # of research acts per Iawai.net subscriber are 'rough' estimates that reflect the offline habits of consumers. The audience for fast moving grocery 'retailer specials' is assumed to be 30% of households and the audience for durables and services 'specials' is assumed to be 80% of households because these items are generally 'high expense' items. For clothing it is assumed that the 'retailer specials' are interesting for 75% of all men and women. The revenues per Iawai.net member, that are derived from these parameter estimations, should be seen as a 'rough revenue indication' that can deviate from the real value.

2) The table assumes that consumers will do all their research of 'retail specials' on Iawai.net, an assumption that is not realistic. Change of consumer shopping habits will only happen partially and gradually. The revenue estimates per subscriber should be seen as a maximum. 5) The Iawai.net 'Product Info' C/M contact rates in the below table were estimated using the

Iawai.net 'Retailer Specials' ad rate calculation framework as described on the previous page. 6) The Iawai.net C/M rate also depends on the assumption for the presentation format (iawai form) that was used to calculate the C/M rate with 'basic' being the cheapest and

'supreme' the most expensive presentation format.

Claims

In the claimsI claim:

1. A tool for providing consumer-specific advertising with effectiveness assessment, comprising:

5 a central database system in electronic communication with a manufacturer, a retailer, and a portal, the central database system comprising a product presentation database, a consumer profile database, a category presentation database, a product and category presentation server, an ad message database, an ad server, a consumer profile processor, and an effectiveness assessor processor.

10

2. The system of claim 1 wherein the ad server transmits a personalized purchase- behavior specific or context-sensitive advertisements in response to a request from the portal or consumer.

15 3. The system of claim 1 wherein the product presentation database is populated with product information transmitted from the manufacturer to the central database system.

4. The system of claim 1 wherein the category presentation database is populated 20 with product information transmitted from the manufacturer to the central database system.

5. The system of claim 1 wherein the category presentation database is populated with product information transmitted from the retailer to the central database

25 system.

6. The system of claim 1 wherein the product presentation database is populated with product information transmitted from the retailer to the central database system.

7. The system of claim 2 wherein the ad server generates a personalized purchase- behavior specific or context-sensitive advertisement based on information stored in the consumer profile in the consumer profile database.

5 8. The system of claim 7 further comprising a user terminal in electronic communication with the portal, wherein the personalized purchase-behavior specific or context-sensitive advertisement is transmitted to the consumer.

9. The system of claim 8 wherein the user terminal is in electronic communication 10 with the portal via the internet.

9. A process for increasing the effectiveness of advertising effectiveness comprising: collecting data for a consumer, indicating shopping and purchase history and 15 preferences; generating a consumer profile from the data collected for the consumer; storing a plurality of advertisements in an ad database; selecting an advertisement from the ad database based on the consumer profile; serving the advertisement to the consumer via a distributed network;

20 monitoring the shopping and purchase behavior of the consumer after exposure to the ad; and calculating the effectiveness of the advertisement based on consumer purchase behavior.

25 11. The method of claim 10, further comprising updating the consumer profile after the consumer has been exposed to the advertisement.

12. A process for increasing the effectiveness of product and category presentations comprising: uploading a product or category presentation to a product category presentation database;

5 storing a plurality of product or category presentations in an product category database; selecting a product or category presentation from the product/category presentation database based on the consumer profile; serving a product or category presentation in portal specific format to a plurality of online consumers;

10 selecting an advertisement from the ad database based on the consumer profile; serving the advertisement to the consumer via a distributed network; monitoring the shopping and purchase behavior of the consumer after exposure to the product presentation, category presentation and advertisement; and calculating the effectiveness of the product presentation, category presentation and 15 advertisement based on consumer purchase behavior.

13. The method of claim 12, further comprising updating the consumer profile after the consumer has been exposed to the product presentation or category presentation.

20

14. A central standardized database, comprising product brand presentations and retail category presentations, wherein the product brand presentations and retail category presentations are uploaded and updated by a participating manufacturer or retailer, and a log file database including requests by consumers to access the

25 product brand presentations and retail category presentations and the advertisement contacts to which the consumer has been exposed.

15. The database of claim 14, further comprising a holistic consumer profile, wherein the holistic consumer profile includes the consumer's historical purchase behavior

30 and preferences.

16. A system for serving consumer-specific online product and retailer content, comprising: creating a holistic purchase-behavior specific user profile for a consumer; 5 determining, based on the holistic purchase-behavior user profile, product and retailer content which most closely matches the preferences or needs of the consumer; serving the product and retailer content to the user into a portal-specific presentation format. 10

17. The system of claim 16, wherein the product and retailer content is selected from the group consisting of advertisements, product presentations, and category presentations.

15 18. The system of claim 17 further comprising logging the consumer's shopping and purchase behavior response to the product and retailer content.

19. The system of claim 18, further comprising updating the consumer's holistic profile, based on the consumer's shopping and purchase behavior response to the

20 product and retailer content.

20. The system of claim 19 further comprising assessing the effectiveness of the product and retailer content, based on the shopping and purchase behavior response of a plurality of consumers to the product and retailer content.

25

21. The system of claim 16, further comprising transparently calculating advertising rates, based on the effectiveness of the product and retailer content to influence consumer purchasing behavior.

30 22. The system of claim 16, further comprising generating in-store traffic by providing the consumer with advertising and or promotion incentives to purchase a product via an online advertisement, product presentation, or category presentation; accepting online payment for the product; and delivering the product to the consumer at an offline retail store.

23. The system of claim 22, wherein the advertising and or promotion incentives are 5 forwarded to consumers based on their holistic consumer purchase-behavior specific profile.

24. The system of claim 22, wherein the holistic consumer profile indicates that the consumer is more likely to purchase a product having a discounted price.