WO2002006984A2

WO2002006984A2 - Target rater

Info

Publication number: WO2002006984A2
Application number: PCT/US2000/032419
Authority: WO
Inventors: David Klingle
Original assignee: Catalina Marketing International Inc.
Priority date: 2000-07-14
Filing date: 2000-12-04
Publication date: 2002-01-24
Also published as: JP2004504671A; CA2416221A1; ITMI20002429A1; AU2001218055A1; WO2002006984A8; ZA200006530B; EP1301877A2; BE1013965A6; PT102603A

Abstract

A method and a terminal for providing promotions based upon consumer input regarding previously consumed food products and/or recipes. This input, alone or in conjunction with previous input from the same consumer or input from other consumers to obtain a predictive profile of the "tastes" (or other factor(s) that influence food purchase decisions) of the consumer, us used to suggest food products and/or recipes to the consumer and provide suitable promotions. Alternatively, the consumer can provide further consumer input regarding a particular planned meal situation, and food product suggestions and/or promotions can be provided to the consumer.

Description

Target Rater

BACKGROUND OF THE INVENTION Field of the Invention:

This invention is directed to using consumer input on food products and/or recipes for purposes of issuing promotions.

As used herein, the term "consumer input" refers to score(s) or rating(s) describing a previously consumed food product and/or recipe, and/or information regarding a planned meal situation, wherein the information and/or rating(s) are generated by the consumer.

As used herein, the term "promotion" refers to any offer, advertisement, incentive, coupon, commercial, recipe, and/or communication for promoting one or more goods and/or services.

Discussion of the Background:

Predictive targeting describes a marketing technique wherein marketing efforts are directed to an individual or group of individuals that have characteristics which indicate the likelihood of a certain behavior, such as a purchase. The examined characteristics commonly include historical and/or demographic data. By targeting marketing efforts to an individual or group likely to be interested in a product according to a predictive profile, the expense of marketing can be reduced, and even small groups of individuals interested in a product can receive information regarding the product on a low cost per capita basis.

Limitations of traditional predictive targeting include a blind reliance upon this historical or demographic data without feedback from the individual or group of individuals. For example, an individual may purchase a product for any number of reasons that are simply not captured by a historical record of purchases. For example, an individual might purchase an object as a gift for another, for use by a group, or because the individual is unaware of alternate products. These activities thus represent statistical outliers that do not truly represent the "taste" of the individual or group in regard to a particular product and limit the predictive efficacy of the predictive profiles.

The problems experienced in developing predictive profiles are especially prevalent in the case of food products and/or recipes. Food purchases are often dictated by any of a variety of factors unrelated to the "taste" in food of an individual or group that are not captured by a simple historical record. For example, food purchases are often dictated by the "tastes" of other members in a household, health concerns, financial concerns, religious concerns, social concerns, ethical concerns, awareness of products, limited time, skill, and/or utensils for food preparation, and the historical momentum of previous purchases, food traditions, and/or recipes. Although an analysis of the historical record might capture these and other factors and still be effective in predicting purchases based upon these factors, the actual "taste" (and other factors that influence a decision to purchase) of the individual remains undescribed by such an analysis.

The problems with conventional predictive targeting approaches are illustrated schematically in FIG. 1, wherein the disregard by the prior art of the multiple factors that influence a motivation to purchase is illustrated. The aggregate step of deciding to purchase S10 synthesizes various factors, examples of which are depicted as lOa-lOi in FIG. 1, that influence a purchase decision. These motivation factors include, but are not limited to, whether an individual likes the taste of a food product and/or recipe, whether the individual's family and/or friends like the taste of a food product and/or recipe, whether the food product and/or recipe meets an individual's health concerns, financial concerns, religious concerns, social concerns, and ethical concerns, whether the individual is aware of other food products and/or recipes, whether the individual has adequate time, skill, and/or utensils for preparation of the food product and/or recipe, whether the individual has traditionally used a food product and/or recipe, whether a food product and/or recipe is traditional for a particular setting or event such as a holiday, and whether a recipe known to the individual calls for a certain type and/or brand of food product. In traditional predictive targeting methods, only the step of the purchase event S20 is captured and later recorded, stored, and analyzed in step S30. In other words, there is a barrier 40 that prevents a more complete understanding of the step S10, deciding to purchase, that limits the effectiveness of conventional predictive targeting of promotions.

SUMMARY OF THE INVENTION Accordingly, one object of this invention is to provide a novel method, system, and computer program for effectively issuing promotions based upon consumer input on food products and/or recipes. Another object of this invention is to provide a novel method, system, and computer program for using consumer input on food products and/or recipes for purposes of providing recipes to an individual.

It is yet another object of this invention to provide a novel method, system, and computer program for using consumer input on food products and/or recipes for purposes of describing factors that influence food purchase decisions, including the "tastes" of an individual or group in food.

A further object of this invention is to provide a novel terminal for accessing information regarding consumer input on food products and/or recipes for purposes of issuing promotions.

A still further object of this invention is to provide a novel method, system, and computer program for charging a company to provide promotions to individuals regarding food products and/or recipes based upon the "tastes" or other factors that influence food purchase decisions of the individual.

These and other objects of the invention are realized by providing a novel method, system, and computer program that request consumer input regarding previously consumed food products and/or recipes, and using this input alone or in conjunction with previous input from the same consumer or input from other consumers to obtain a predictive profile of the "tastes" (or other motivation factor(s) that influence food purchase decisions) of the consumer. This predictive profile can be used to provide promotions to the consumer. Alternatively, this predictive profile can be used to suggest food products and/or recipes to the consumer. Alternatively, the consumer can provide further consumer input regarding a particular planned meal situation, and food product suggestions and/or promotions can be provided to the consumer.

Once a product suggestion is accepted or a promotional benefit exercised, a food product and/or recipe can be automatically added to a shopping list and/or purchased for home delivery. Furthermore, after consumption, the suggested or promoted food product and/or recipe can be the subject of further consumer input, which further improves the ability to achieve the above-mentioned objects. BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the invention and many of the attendant advantages thereof will be readily obtained as the same become better understood by reference to the following detailed description when considered in connection with the accompanying drawings, wherein:

FIG. 1 is a schematic illustrating the disregard by the prior art of example multiple factors that motivate an individual to perform a purchase event according to the present invention;

FIG. 2 is a flow diagram of a process for acquiring consumer information regarding the motivation factors behind a consumer's purchase according to the present invention;

FIG. 3 is a flow diagram of a process for effectively issuing targeted promotions after a consumer request for a meal recommendation according to the present invention;

FIG. 4 is a flow diagram of a process for effectively issuing targeted promotions after a consumer request for a meal recommendation and acquiring consumer information regarding the accepted meal recommendation according to the present invention;

FIG. 5 is a flow diagram of a process for effectively issuing targeted promotions where information regarding the consumer's motivation factors is acquired prior to providing a promotion according to another embodiment of the present invention;

FIG. 6 is a flow diagram of a process for effectively issuing targeted promotions where information regarding the consumer's motivation factors is drawn from a previously populated database prior to providing a promotion according to another embodiment of the present invention;

FIG. 7 is a flow diagram of a process for effectively issuing targeted promotions initiated by a provider of promotions where information regarding the consumer's motivation factors is drawn from a previously populated database prior to providing a promotion according to another embodiment of the present invention;

FIG. 8 is a flow diagram of a process for effectively issuing targeted promotions where information regarding the consumer's motivation factors is acquired prior to providing a promotion according to another embodiment of the present invention;

FIG. 9 is a flow diagram of a process for effectively issuing targeted promotions where information regarding the consumer's taste is acquired prior to providing a promotion according to another embodiment of the present invention;

FIG. 10 is a flow diagram of a process of another example embodiment of providing a consumer with a targeted promotion;

FIG. 11 is a schematic example network structure for issuing promotions based upon consumer input;

FIG. 12A and 12B are exemplary data record structures for storing predictive criteria; and

FIG. 13 is an exemplary computer system programmed to perform one or more functions of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Referring now to the drawings, and more particularly to FIG. 2 thereof, which illustrates a process of acquiring consumer information regarding the motivation factors behind a consumer's purchase. The process begins at step S210, wherein a consumer is identified. The identification of the consumer can occur in any of a variety of different ways, for example, by recognition of a preferred customer card or login ID number at a website. The identification need not be made volitionally by the consumer. In other words, it could be automatically triggered by a specific act of the consumer such as, e.g., logging on to a web site, sampling a food product, using a credit card, using a customer card, watching a television program, participating in a survey, and/or purchasing (or registering) a product. Step S220 involves determining if a "critical mass" or threshold level of information has already been stored regarding the consumer identified in step S210. The amount of information required to reach this "critical mass" or threshold level can change depending upon several conditions, including, but not limited to, the number of times that a consumer has used the service, the typical number of suggestions that a consumer declines, or a historical purchase record significantly different from a predicted purchase record. In the embodiment illustrated in FIG. 2, the information necessary to reach the threshold is related to the "taste" of the consumer for certain food products, but the information can also relate to other motivation factors such as those previously described. If the threshold level of information related to "taste"and/or other motivation factors of the consumer has not been met, then the consumer is queried regarding "taste" motivation factors in step S230. The querying occurring in step S230 can take any of a number of different forms, including, but not limited to, having the consumer rate or score the taste (or other characteristics) of various previously consumed food products and/or recipes, or give information regarding the future needs in food products and/or recipes. Rating or scoring can be performed on a numerical or qualitative score. Rated or scored characteristics include, but are not limited to, the individual's "taste" for the food product and/or recipe, the "taste" of the individual's family and/or friends for the food product and/or recipe, the financial, religious, social, and/or ethical opinion of the individual or the individual's family members regarding the food product and/or recipe, the opinion of the individual regarding other similar food products and/or similar recipes, the individual's opinion regarding the time, skill, and/or utensils required for preparation of the food product and/or recipe, the traditional uses of a food product and/or recipe by the individual, and/or the traditional and/or religious connotations of a food product and/or recipe for an individual and/or his or her family and friends. The querying can be performed locally or remotely using, for example, a network device. Querying of other databases might also be performed by, for example, the processor 611 of FIG. 11, as discussed later. For example, a medical database might be queried to determine if an individual is, for example, allergic to certain food products, diabetic, or lactose intolerant. A religious database might be queried to eliminate certain foodstuffs from consideration. In a preferred embodiment, an individual is simply queried regarding the individual's taste in various food products and/or recipes remotely using a website.

As the extent of querying (number of questions posed and answered) increases, so does the predictive ability of the analysis to be performed later illustrated in, e.g., FIGS. 3, 5, 6, 7, and 9. In a preferred embodiment, a threshold number of queries will be made and answered to allow a certain submaximal level of predictive ability. This threshold can increase with repeated consumer use of the target rater. In one embodiment, this threshold can be based upon a predetermined consumer tolerance for responding to queries.

After the consumer has been queried regarding a particular food product and/or recipe (or group of food products and/or recipes), the consumer's information is stored in a database during step S240. In a preferred embodiment, this database is a remote, electronic database of the type described later in FIG. 11 and the consumer's information is stored in records illustrated in FIG. 12. In this preferred embodiment, data collection is cumulative through several iterations of the steps outlined in FIG. 2. In an alternate embodiment, the storage of the consumer's information is delayed until after analysis of the consumer's information, alone or in conjunction with other information, as illustrated in, e.g, FIGS. 3, 5, 6, 7, and 9.

FIG. 3 illustrates a method for effectively issuing targeted promotions after a consumer request for a meal recommendation. In step S310, a consumer is identified. The identification of the consumer can occur by any of a variety of different manners, for example, recognition of a preferred customer card or ID number. The request thus need not be made volitionally by the consumer. In other words, it could be automatically triggered by a specific act of the consumer such as, e.g., logging on to a web site, sampling a food product, using a credit card, using a customer card, watching a television program, participating in a survey, and/or purchasing (or registering) a product. In step S320, a consumer requests a particular meal recommendation. The consumer is then queried regarding the particular motivation factors related to the particular meal recommendation in step S330. Example particular motivation factors that may be the subject of the querying of step S330 may include, but are not limited to, the time available for preparation of the particular meal, the number of guests who will be eating a particular meal, and any of the above-identified motivation factors in regard to either the individual consumer or any of the guests who will be partaking in the particular meal. Examples of such further information include but are not limited to the fact that one person who will be consuming the particular meal is allergic to nuts, while another such person is a vegetarian. In this example embodiment, since the particular motivation factors apply only to the particular meal, particular information regarding these particular motivation factors is not stored. However, in alternate embodiments, the particular information obtained in S330 can be stored even though even though the particular information may be particular to a single meal situation or unrelated to the "taste" and/or other motivation factors that are the subject of querying such as occurs in step S230 of FIG..2. After the querying of step S330 is complete, the particular information obtained in step S330 is analyzed in light of the "taste" and/or other motivation factor information previously obtained in, for example, step S330 and/or previously stored in the database.

Analysis of the information in step S330 proceeds using any of a number of predictive targeting software applications and/or algorithms. These are well known in the art, and focus marketing efforts upon an individual or group of individuals that have characteristics which indicate the likelihood of a certain act, like a purchase, being performed by the individual or group of individuals. A more complete description of predictive targeting and marketing is given, e.g., in "The Direct Marketing Handbook," Edward L. Nash, ed., McGraw-Hill, New York, 1992, the entire contents of which are incorporated herein by reference, and in United States Patents 6,026,370, 5,974,399, 5,892,827, 5,832,457, 5,612,868, 5,173,851, 4,910,672, 6,014,634, 6,055,573 the entire contents of all of which are incorporated herein by reference. The goal of step S340 is to provide a consumer with a promotion based upon the motivation factors underlying a purchase. In a preferred embodiment, these motivation factors are the consumer's "taste" for a food product. The goal of step S340 is also reached by analyzing the information provided by the consumer in light of other information previously stored in the database. The previously stored other information may include information characterizing certain food products, including, but not limited to, taste (for example, saltiness, sweetness, bitterness of the food product), health aspects (for example, presence of common allergens in the food product), nutritional aspects (for example, the "Nutritional Facts" commonly found on food products), and the availability of promotional material (for example, the right to print discount coupons) related to certain food products. In an alternate embodiment, the previously stored other information will also include predictive information relating to the motivation factors of demographic groups when purchasing food products, including, but not limited to, taste (for example, the average "taste" of teenage males from Nebraska for fish), health aspects (for example, the likelihood that elderly individuals are on a low sodium diet), nutritional aspects (for example, the likelihood that a middle-aged housewife is concerned about the cholesterol content of a food product), and promotional products (for example, the likelihood that an unmarried male will use a coupon or a recipe). In another embodiment, the previously stored other information will also include predictive information relating to the historical record of purchases by the individual consumer alone or in conjunction with further information regarding the motivation factors behind those purchases.

Ideally, the querying of step S330 would proceed until an individual's motivation factors underlying the purchase of a food product have been "completely determined" or even "overdetermined." In other words, the analysis regarding a consumer's motivation factors for any particular food product or recipe could simply be performed by looking up data previously input by the consumer in step S330 regarding that particular food product or recipe. There would be no need to extrapolate information to a new food product or recipe, because the consumer would already have been queried regarding every food product or recipe. This is clearly not practical, nor is it even likely to be effective enough to warrant the effort since motivation factors might change between the time when the querying of step S330 occurred and the time when the analysis of step S340 occurred. For example, an individual might be very concerned regarding the nutritional content of food immediately after a New Year's resolution to lose weight, but would be significantly less concerned a month later.

However, since querying and storing information regarding every food product is clearly not possible, analysis in step S340 will proceed with a subset of the completely determined data set. As previously mentioned, a threshold data set meeting any of a number of different criteria can be gathered. In many such embodiments, the data set can be supplemented with data regarding the motivation factors of demographic groups to which the individual consumer belongs or the historical record of purchases by the individual. Predictive targeting analysis in step S340 then proceeds by examining the consumer's (supplemented) motivation factors, and comparing those motivation factors with the previously stored information characterizing certain food products. In one embodiment of step S340, the characteristics of a list of food products and/or recipes for which promotions are available is simply compared with the importance of those characteristics to a consumer, determined by comparing the consumer input score(s) or rating(s) regarding other food products with the characteristics of these other food products. In an alternate embodiment of step S340, other food products with favorable consumer input score(s) or rating(s) are identified, and similar food products from the list of food products and/or recipes for which promotions are available are selected and the relevant promotion provided to the consumer.

Once the consumer information has been analyzed, the consumer is provided with a number of recommendations related to the consumer request for a meal recommendation made in step S320. The consumer will then select a subset of recommendations from the number of recommendations that the consumer feels are of interest or appropriate in step S350.

In step S360, the consumer is provided with one or more targeted promotions based upon the recommendations selected in step S350. Provided promotions can constitute, for example, a recipe, a meal plan, the same regarding a portion of a meal (for example, a wine), a coupon, dietary information, and/or any other offer, advertisement, incentive, coupon, commercial, recipe, and/or communication relating to a food product and/or recipe. The promotion need not be used volitionally by the consumer. In other words, the promotion could be automatically triggered by a specific act of the consumer such as, e.g., logging on to a web site, sampling a food product, using a credit card, using a customer card, watching a television program, participating in a survey, and/or purchasing (or registering) a product. The promotion provided in step S360 can be used in a public facility such as a kiosk in a food store, the checkout cashier of a food store, or at a private facility such as at home using, for example, an Internet connection, interactive TV, or other networked device. Provided promotions are not limited to the meal recommendation requested in step S320. For example, a request for a meal recommendation in step S320 by a consumer could be answered with a recommendation as well as one or more coupons relating to food products that go with the recommendation selected in step S350 based upon information regarding motivation factors determined in step S330. Since these promotions are targeted based upon the analysis performed in step S340 using the information regarding motivation factors determined in step S330, the targeting of these promotions is highly accurate and minimizes marketing costs. In a preferred embodiment, a promotion is distributed from a printer at a supermarket kiosk.

FIG. 4 illustrates a method for effectively issuing targeted promotions after a consumer request for a meal recommendation and acquiring consumer information regarding the accepted meal recommendation. After a consumer is provided in step S440 with a targeted promotion based upon a subset of meal recommendations selected in step S430, the consumer will presumably proceed to use the promotion in step S450, either volitionally or automatically as described above. After the promotion has been used, the consumer can then be queried in step S460 regarding the consumer's opinion of the food product and/or recipe subject to the promotion provided in step S450. Step S460 can be performed either immediately after the promotion provided in step S450 is exercised, or at a later time, such as the next time that a consumer logs into a web site. The data acquired during step S460 can then be added to the database for future use.

FIG. 5 illustrates a method for effectively issuing targeted promotions after a consumer request for a meal recommendation and acquiring consumer information regarding the accepted meal recommendation. In step S510, a consumer requests a promotion. This request can constitute, for example, a request for a recipe, a request for a meal plan, a request regarding a portion of a meal (for example, a wine), a request for a coupon, a request for dietary information, and/or any other offer, advertisement, incentive, coupon, commercial, recipe, and/or communication relating to a food product and/or recipe, and an identification of the consumer (by way of, for example, preferred customer card or ID number). The request thus need not be made volitionally by the consumer. In other words, it could be automatically triggered by a specific act of the consumer such as, e.g., logging on to a web site, sampling a food product, using a credit card, using a customer card, watching a television program, participating in a survey, and/or purchasing (or registering) a product. The promotion of step S510 can constitute, e.g., an offer, advertisement, incentive, coupon, commercial, recipe, and communication for promoting one or more goods and/or services. The request of step S510 can occur in a public facility such as a kiosk in a food store, the checkout cashier of a food store, or at a private facility such as at home using, for example, an Internet connection, interactive TV, or other networked device. In a preferred embodiment, a consumer would request a recipe from a web site specializing in the storage and distribution of such information.

After the initial request of step S510, this embodiment of the invention proceeds to query the consumer regarding the motivation factors (step S520) behind the request of step S510. This query can take any of a number of different forms, including, but not limited to, having the consumer rate or score the taste (or other characteristics) of various previously consumed food products and/or recipes, or give information regarding the future needs in food products and/or recipes. Rating or scoring can be performed on a numerical or qualitative score. Rated or scored characteristics include, but are not limited to, the individual's "taste" for the food product and/or recipe, the "taste" of the individual's family and/or friends for the food product and/or recipe, the financial, religious, social, and/or ethical opinion of the individual or the individual's family members regarding the food product and/or recipe, the opinion of the individual regarding other food products and/or similar recipes, the individual's opinion regarding the time, skill, and/or utensils required for preparation of the food product and/or recipe, the traditional uses of a food product and/or recipe by the individual, and/or the traditional and/or religious connotations of a food product and/or recipe for an individual and or his or her family and friends. The querying can be performed locally, or remotely using, for example, a network device. Querying of other databases might also be performed. For example, a medical database might be queried to determine if an individual is, for example, allergic to certain food products, diabetic, or lactose intolerant. A religious database might be queried to eliminate certain foodstuffs from consideration. In a preferred embodiment, an individual is simply queried regarding the individual's taste in various food products and/or recipes remotely using a website.

As the extent of querying (number of questions posed and answered) increases, so does the predictive ability of the analysis performed later in step S540. In a preferred embodiment, a threshold number of queries will be made and answered to allow a certain submaximal level of predictive ability. This threshold can increase with repeated consumer use of the target rater. In one embodiment, this threshold can be based upon a predetermined consumer tolerance for responding to queries.

After the consumer has been queried regarding a particular food product and/or recipe (or group of food products and/or recipes), the consumer's information is stored in a database during step S530. In a preferred embodiment, this database is a remote, electronic database of the type described later in FIG. 8. In this preferred embodiment, data collection is cumulative through several iterations of the steps outlined in FIG. 2. In an alternate embodiment, the storage of the consumer's information is delayed until after analysis of the consumer's information in step S540 alone or in conjunction with other information.

Analysis of the information in step S540 proceeds using any of a number of predictive targeting software applications and/or algorithms. These are well known in the art, and focus marketing efforts upon an individual or group of individuals that have characteristics which indicate the likelihood of a certain act, like a purchase, being performed by the individual or group of individuals. A more complete description of predictive targeting and marketing is given, e.g., in "The Direct Marketing Handbook," Edward L. Nash, ed., McGraw-Hill, New York, 1992, the entire contents of which are incorporated herein by reference. The goal of step S540 is to provide a consumer with a promotion based upon the motivation factors underlying a purchase. In a preferred embodiment, these motivation factors are the consumer's "taste" for a food product. The goal of step S540 is reached by analyzing the information provided by the consumer in light of other information previously stored in the database. The previously stored other information will include information characterizing certain food products, including, but not limited to, taste (for example, saltiness, sweetness, bitterness of the food product), health aspects (for example, presence of common allergens in the food product), nutritional aspects (for example, the "Nutritional Facts" commonly found on the labels of food products), and the availability of promotional material (for example, the right to print discount coupons) related to certain food products. In an alternate embodiment, the previously stored other information will also include predictive information relating to the motivation factors of demographic groups when purchasing food products, including, but not limited to, taste (for example, the average "taste" of teenage males from Nebraska for fish), health aspects (for example, the likelihood that elderly individuals are on a low sodium diet), nutritional aspects (for example, the likelihood that a middle-aged housewife is concerned about the cholesterol content of a food product), and promotional products (for example, the likelihood that an unmarried male will use a coupon or a recipe). In another embodiment, the previously stored other information will also include predictive information relating to the historical record of purchases by the individual consumer used alone or in conjunction with information regarding the motivation factors behind those purchases.

Ideally, the querying of step S520 would proceed until an individual's motivation factors underlying the purchase of a food product have been "completely determined" or even "overdetermined." In other words, the analysis regarding a consumer's motivation factors for any particular food product or recipe could simply be performed by looking up data previously input by the consumer in step S520 regarding that particular food product or recipe. There would be no need to extrapolate information to a new food product or recipe, because the consumer would already have been queried regarding every food product or recipe. This is clearly not practical, nor is it even likely to be effective enough to warrant the effort since motivation factors might change between the time when the querying of step S520 occurred and the time when the analysis of step S540 occurred. For example, an individual might be very concerned regarding the nutritional content of food immediately after a New Year's resolution to lose weight, but would be significantly less concerned a month later.

However, since querying and storing information regarding every food product is clearly not possible, analysis in step S540 will proceed with a subset of the completely determined data set. As previously mentioned, a threshold data set meeting any of a number of different criteria can be gathered. In many such embodiments, the data set can be supplemented with data regarding the motivation factors of demographic groups to which the individual consumer belongs or the historical record of purchases by the individual. Predictive targeting analysis in step S540 then proceeds by examining the consumer's (supplemented) motivation factors, and comparing those motivation factors with the previously stored information characterizing certain food products. In one embodiment of step S540, the characteristics of a list of food products and or recipes for which promotions are available is simply compared with the importance of those characteristics to a consumer, determined by comparing the consumer input score(s) or rating(s) regarding other food products with similar characteristics. In an alternate embodiment of step S540, other food products with favorable consumer input score(s) or rating(s) are identified, and similar food products from the list of food products and/or recipes for which promotions are available are selected and the relevant promotion provided to the consumer.

Once the consumer information has been analyzed, the consumer is provided in step S550 with a promotion targeted to the consumer based upon information regarding motivation factors determined in step S520. In a preferred embodiment, the motivational factors are the "tastes" of the individual. Provided promotions can be the same as those described in regard to step S510, but are not limited to the promotion requested in step S510. For example, a request for a recipe in step S510 by a consumer could be answered with a recipe as well as one or more coupons relating to ingredients for the recipe in step S550 based upon information regarding motivation factors determined in step S520. Since these promotions are targeted based upon the analysis performed in step S540 using the information regarding motivation factors determined in step S520, the targeting of these promotions is highly accurate and minimizes marketing costs.

An alternate embodiment of this invention is illustrated in FIG. 6. In this embodiment, a database of suitable size regarding the motivation factors of an individual has already been gathered. This can, for example, be performed through one or more iterations of the steps S520 and S530 illustrated in FIG. 5. In this case, a suitable database exists for the targeting of promotions based upon the known motivational factors of the individual. In a preferred embodiment, the known motivational factors are the "tastes" of the individual. Thus, the database is directly queried regarding the motivational factors of the individual in step S620, and the resulting analysis in step S630 is based upon this stored information. This will limit the effort required to determine the promotion provided in step S640. In an alternate embodiment, the known motivational factors are generic to a group or subgroup of individuals that may or may not share certain demographic and/or historical traits.

FIG. 7 illustrates a method for effectively issuing targeted promotions initiated by a provider of promotions where information regarding the consumer's motivation factors is drawn from a previously populated database prior to providing a promotion. In this case, in step S710, a promoter requests a list of one or more consumers that display motivation factors which make it likely that they will purchase the promoter's products. The database is queried in step S720 to identify such a list of consumers, and consumer information regarding the motivation factors is analyzed in step S730. After analysis, the promoter has the option of providing the consumers) on the list of identified consumers with one or more of the above-identified promotions in step S740.

FIG. 8 illustrates an alternate method of gathering a consumer's information regarding motivation factors. After a promotion has been provided in step S810 (such after the events illustrated in, e.g., FIG. 3, 5, 6 or 7), the individual consumes the promotional food product and/or recipe and is then queried regarding the individual's opinion of the food product and/or recipe in step S820. The subject of these queries can encompass many of the motivational factors described above. For example, the individual can be queried regarding the "taste" of the individual for the food product and/or recipe, the "taste" of the individual's family and/or friends for the food product and/or recipe, the financial opinion of the individual regarding the food product and/or recipe, the individual's opinion regarding the time, skill, and/or utensils required for preparation of the food product and/or recipe, and the possibility of the individual incorporating the food product and/or recipe into traditional and or religious food events, as well as related information for family members and/or friends. The querying can be performed locally, or remotely using, for example, a network device. In a preferred embodiment, an individual is simply queried regarding the individual's taste for the food product and or recipe remotely using a website the next time that the individual accesses the website.

After the querying of step S820 has been performed, the information ascertained therein is added to the database in step S830. In a preferred embodiment, this database is a remote, electronic database of the type described later in FIG. 11.

FIG. 9 illustrates a specific embodiment of the present invention relating entirely to a consumer request for a food product recommendation. In step S910, a consumer requests a food product recommendation. This recommendation can include, for example, a request for a recipe, a request for a wine suggestion to match a meal, or a request for a food product that meets certain dietary/time/religious/social/or other requirements. This request would be made, for example, by the consumer from a website, or at a kiosk located within a store that sells food products. Once the request has been made, the consumer is queried regarding the consumer's "taste" for certain food products in step S920. These queries can include generic questions, such as if the consumer prefers spicy dishes, as well as specific questions, such as if the consumer likes the taste of a specific food product such as a particular vegetable, type of cheese, or type of meet. Once a sufficient number of queries have been made to draw a reasonable conclusion regarding the consumer's "taste," the answers to these queries are stored in step S930 and analyzed in step S940. The data is preferably stored in a remote database accessible from multiple locations by way of, for example, the Internet. The analysis is likewise preferably performed at a remote processor in order to minimize the number of processors necessary and to facilitate updating and maintaining of the processors. The order of steps S930 and S940 can be readily switched, or they can be performed simultaneously. Alternatively, in an embodiment representative of the process described in FIG. 6, previously stored data regarding the consumer's "taste"can be drawn upon to omit steps S920 and S930, and the analysis of step S940 can be performed using this previously stored data. This analysis may even be performed prior to the consumer request in step S910 and the results thereof stored. Regardless of the order or source of information used to perform step S940, once the analysis is complete, the consumer is provided with a food product suggestion and, under certain circumstances, various promotions related to the food product suggestion in step S950. The circumstances used to identify promotions may include, for example, the companies that have signed a promotion distribution concract with the provider of the database and analysis processors.

FIG. 10 illustrates an example embodiment of providing a consumer with a targeted promotion wherein the promotion is a recommendation for a particular food product and/όr recipe. After analysis of the motivation factors underlying a consumer's purchase such as illustrated in, e.g., FIG. 3, 5, 6, and 7, at least one food product and/or recipe is recommended to the consumer in step S1010. If, in step S1020, the consumer does not accept a subset of the recommended food product(s) and/or recipe(s), then the process flow returns to step S1010 and at least one new food product and/or recipe is recommended. Alternatively, the consumer is queried regarding the motivation factors behind the consumer's declination of the recommended food product(s) and/or recipe(s), and this data stored in a database. Once an acceptable recommendation has been made in step S1010 as ascertained in step S1020, advertisements related to the accepted recommendation are displayed in step S1030, coupons related to the recommendation are provided in step SI 040, and food products related to the recommendation are ordered directly from a food store that can receive such electronic orders in step S1050. In the absence of a particular form of promotion, the corresponding step S1030 or S1040 can be omitted. Alternatively, if a particular form of promotion is present for two discrete food products related to the same recommendation, the corresponding step S1030 or S1040 can be repeated. Step S1050 can also be omitted based upon several factors, including the consumer's discretion and the absence of food stores that can receive electronic orders.

FIG. 11 illustrates an example of a network structure for issuing promotions based upon previously gathered consumer input. The three primary components of this example system are a central database 610, at least one geographically dispersed interaction site (shown as three alternate and/or simultaneous embodiments 630, 640, and 650), and a network 620 that transmits data between the central database 610 and the interaction sites 630, 640, and 650. The central database 610 preferably includes a processor 611 for, e.g., coding and decoding data transmitted of network 620, controlling reading and writing of data in data storage records 612a-d, and analyzing the data in data storage records 612a-d in, for example, steps s240 and s240e described above. The data storage records 612a-d can be any sort of processor-accessible data medium, including but not limited to any type of disk including floppy disks, optical disks, CD-Rom, magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, flash memory, magnetic or optical cards, or any type of media suitable for storing electronic data. The processor 611 can be any processor configured for high volume data transmission and performing a significant number of mathematical calculations in processing communications (possibly as a webserver), database searches, and computational algorithms. A conventional personal computer or a workstation with sufficient memory and processing capability may be configured to act as processor 611. A PENTIUM III microprocessor such as the 1GHz PENTIUM III for the SC 242 manufactured by Intel Inc., a Motorola 500 MHz POWERPC G4 processor, and the Advanced Micro Devices 1 GHz AMD ATHLON processor may all be configured to suitable for processor 611. The network 620 may be a local area network, a wide area network, a virtual private network, and/or even a connection via a public switch telephone network. In a preferred embodiment, the network includes a number of connection modalities, including a cable- modem connection, a DSL connection, a dial-up modem connection, and the like.

The data storage records 612a-d include data concerning a number of different subjects. Element 612a includes generic, group, or demographic data relating to groups of individuals and their historical purchase patterns and motivational factors. Element 612b includes data relating to the both the historical and motivational record of certain individual consumers. These data records will be associated with the identity of a specific individual consumers, and, in a preferred embodiment, will have been input by the individual consumer him- or herself. Motivational records may include but are not limited to the "taste" opinions of the individual consumer regarding certain food products and/or recipes, the nutritional, religious, financial, social, traditional, and/or ethical concerns of the individual consumer, similar motivational factors for the individual consumer's family and or friends, and the time, skill, and/or utensils available to the individual consumer. Element 612 c includes data relating to food products. Examples of this data may include but are not limited to rankings of various taste attributes such as sweetness, bitterness, acidity, sourness, saltiness, fhiitiness, texture, nutritional information, religious, ethical, social, and traditional information, time, skill, and/or utensils required for preparation, and/or cost information. Element 612d includes data relating the clients of the central database provider. In a preferred embodiment, these clients are individuals or organizations who have hired to central database provider to provide promotions related the clients' products.

The data stored in central database 610 is accessed by the individual consumer from at least one interaction site 630, 640, and/or 650 connected thereto by way of network 620. Interaction site 630 illustrates one embodiment of such a site and includes a remote terminal 630a connected to a promotion output device 630b as well as an input device 630c. The remote terminal can include a processor similar to processor 611, but in a preferred embodiment it is simply dedicated to the reception and transmission of data over network 620 and the coding and decoding of that data when received from input device 630c and output to promotion output device 630b. Input device 630c can be any of a number of different devices capable of transforming a consumer's responses to queries and/or requests for promotions into electronic form. These include but are not limited to keyboards, touch screens, computer mouses, bar code readers, magnetic readers (including strip, disk, and tape readers), smart card readers, pressure sensors, motion detectors, fingerprint readers, iris recognition devices, electromagnetic receivers, voltmeters, heat sensors, and other transducers capable of being interfaced with a digital processor. Input device 630c must simply be capable of receiving input from a consumer, including input indicating the consumer's presence and/or tastes in food and/or other factors that motivate a purchase decision. Promotion output device 630b likewise can be made of any of a number of different devices, including a computer monitor, printers (paper or otherwise), magnetic writing devices (including disk drives, magnetic strip writers, tape writers), bar code writers, television screens, radio broadcast, Internet data transmission, print advertisement in a newspaper, or simply electronic promotions communicated automatically to another device, such as, for example, a check-out cashier or a credit card company. The type of promotion output will depend upon the initial consumer request, for example, during step S320 of FIG. 3 or step S510 of FIG. 5. If a consumer requests a food product recommendation, a recipe and coupons related to that recipe can be printed on a printer. Alternatively, the recipe can be displayed upon a computer monitor, and the coupons automatically transmitted in electronic form to a food store, where an order can be automatically placed on the consumer's behalf if so desired by the consumer.

In one embodiment, interaction site 630 would be located in a kiosk at the food store. Interaction site 630 is thus available for "on-site" use by consumers. A consumer could thus walk into a food store, identify him or herself, and request a promotion using input device 630c such as a recommendation for a recipe or a particular food product such as, for example, a wine to go with a certain meal. The remote terminal will forward this request through network 620 to central database 610. Processor 611 will receive and decode the transmitted data, and search data storage records 612a-d for information relevant to the particular consumer and/or the consumers request. If a sufficient amount of data is found in the data storage records 612a-d, then processor 611 can indicate a suitable targeted promotion to interaction site 630 by way of network 620. Alternatively, processor 611 can indicate a lack of sufficient information to interaction site 630 by way of network 620, as well as a course of querying necessary to obtain further information. If a sufficient amount of data was found in the data storage records 612a-d, then remote terminal 639a at interaction site 630 will decode the information received from network 620 and indicate a suitable promotion to be output by promotion output device 630b. If an insufficient amount of data was found in the data storage records 612a-d, then remote terminal 630a at interaction site 630 will decode the queries received from network 620 and use these queries to interrogate the consumer, either by way of promotion output device 630b or through a display device integral to remote terminal 630a.

Other configurations of interaction sites are possible. One such configurations might include a consumer's personal computer, as in interaction site 640. In this case, the consumer's home terminal 640a includes a processor which receives and transmits data transmitted over network 620, and encodes and decodes data for input device 640c and promotion output device 640b. In a preferred embodiment, input device 640c would pass along an indication to open a particular website to consumer's home terminal 640a, along with a request for a particular promotion such as a recipe and/or food recommendation. This request would, e.g., be transmitted over network 620 to central database 610, where it would be processed in a manner substantially identical to the manner as if it had originated from interaction site 630. In another embodiment of interaction site 640, the consumer's home terminal receives input from input device 640c indicating the amounts of various foodstuffs present in a food storage location in the home. The food storage location can include, for example, the refrigerator and/or a cupboard. This information can be passed along to central database 610 and handled. In one version of this embodiment, when a promotion is returned to the consumer's home terminal 640, then promotion output device 640b automatically transmits a request for purchase to a food store, and the food is automatically delivered. In yet another embodiment, the consumer's home terminal 640 can include the central database 610 (or portions thereof) on-site at the consumer's home

Still another configuration of an interaction site is illustrated in element 650. This interactions site lacks and input device. Rather than relying on a consumer's request for information to trigger a promotion, targeted promotions selected by central database 610 based upon previously stored data in data storage records 612a-d can be directed automatically to a consumer. These targeted promotions will thus be selected based upon the motivation factors, including "tastes" of the consumer, identified by data storage records 612a-d. The promotions may be ouput using, for example, digital television and/or web page displays.

FIG. 12 illustrates two different data records structures that may be used to store an individual consumer's data in data storage records 612a-d of FIG. 11. Data record structure 710 illustrates a data record centered about an individual food product. Field 710c includes an individual consumer's identifier, and field 710d includes data describing a particular food product. The particular food product can be a class of foods, such as cheeses, meats, and grains, it can be individual products within those classes, such as Swiss cheese, chicken, and rice, or it can be recipes made with those products, such as ham and cheese sandwiches, southern fried chicken, and rice pilaf. The individual food factors shown as elements 710e-i would be ratings or scores preferably provided by the individual regarding certain factors that would influence the individual's decision to purchase the particular food product. These factors might include but are not limited to the individual's "taste" for the food product, the "taste" of the individual's family and friends, the nutritional, religious, ethical, traditional, cultural, and social ratings or scores of the food product, and the time, skill, and utensil requirement ratings and scores of the particular product.

An alternate data record structure is shown in element 720. Data record structure 720 illustrates a data record centered about an individual's composite scores with regards to a number of factors. For example, field 720d might be a rating or score describing an individual's "taste" regarding sweets, while 720e might be an individual's "taste" regarding salty foods. These composite scores could be assembled by synthesizing a large number of data records for a particular food product using a broad spectrum of food products. Alternatively, data record 720 could be prepopulated with average values for a particular demographic population, and these values gradually changed based upon the individual's response to queries, such as would occur, e.g., in step S240 of FIG. 2, step S530 of FIG 5, or step S830 of FIG. 8. Example consumer factors include but are not limited to various aspects of an individual consumer's "taste", including sweetness, sourness, bitterness, salinity, texture, nutrition, religious concerns, ethical concerns, social concerns, traditional concerns, and the time, skill, and utensils that an individual commonly has for food preparation.

FIGURE 13 illustrates a computer system 801 that can form several different units in an embodiment of the present invention. For example, computer system 801 can alternately form the central database 610 or the interaction sites 630, 640, or 650 of FIG. 11. For this reason, the computer system 801 will be described using unique reference numerals. When a part of computer system 801 that is analogous to a part in another figured is described, this will be explicitly stated in the text. Computer system 801 includes a bus 803 or other communication mechanism for communicating information, and a processor 805 coupled with bus 803 for processing the information. Processor 805 can form processor 611 of FIG. 11. Computer system 801 also includes a main memory 807, such as a random access memory (RAM) or other dynamic storage device (e.g., dynamic RAM (DRAM), static RAM (SRAM), synchronous DRAM (SDRAM), flash RAM), coupled to bus 803 for storing information and instructions to be executed by processor 805. In addition, main memory 807 may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 805. Computer system 801 further includes a read only memory (ROM) 809 or other static storage device (e.g., programmable ROM (PROM), erasable PROM (EPROM), and electrically erasable PROM (EEPROM)) coupled to bus 803 for storing static information and instructions for processor 805. A storage device 811, such as a magnetic disk or optical disk, is provided and coupled to bus 803 for storing information and instructions. Storage device 811 can contain the data storage records 612a, 612b, 612c, and 612d of FIG. 11.

The computer system 801 may also include special purpose logic devices (e.g., application specific integrated circuits (ASICs)) or configurable logic devices (e.g., generic array of logic (GAL) or reprogrammable field programmable gate arrays (FPGAs)). Other removable media devices (e.g., a compact disc, a tape, and a removable magneto-optical media) or fixed, high density media drives, may be added to the computer system 801 using an appropriate device bus (e.g., a small computer system interface (SCSI) bus, an enhanced integrated device electronics (IDE) bus, or an ultra-direct memory access (DMA) bus). Such removable media devices and fixed, high density media drives can also contain the data storage records 612a, 612b, 612c, and 612d of FIG. 11. The computer system 801 may additionally include a compact disc reader, a compact disc reader- writer unit, or a compact disc juke box, each of which may be connected to the same device bus or another device bus.

Computer system 801 may be coupled via bus 803 to a display 813, such as a cathode ray tube (CRT), for displaying information to a computer user. Display 813 can form a promotion output device 630b, 640b, or 650b of FIG. 11, especially wherein the promotion is a recipe or an advertisement. The display 813 may be controlled by a display or graphics card. The computer system includes input devices, such as a keyboard 815 and a cursor control 817, for communicating information and command selections to processor 805. The keyboard 815 and a cursor control 817 can form an input device 630c or 640c of FIG. 11. The cursor control 817, for example, is a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor 805 and for controlling cursor movement on the display 813. In addition, a printer (not shown) may provide a promotion output device 630b, 640b, or 650b of FIG. 11, especially wherein the promotion is a coupon.

The computer system 801 performs a portion or all of the processing steps of the invention in response to processor 805 executing one or more sequences of one or more instructions contained in a memory, such as the main memory 807. Such instructions may be read into the main memory 807 from another computer readable medium, such as storage device 811. One or more processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in main memory 807. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions. Thus, embodiments are not limited to any specific combination of hardware circuitry and software.

As stated above, the system 801 includes at least one computer readable medium or memory programmed according to the teachings of the invention and for containing data structures, tables, records, or other data described herein. Examples of computer readable media are compact discs, hard disks, floppy disks, tape, magneto-optical disks, PROMs (EPROM, EEPROM, Flash EPROM), DRAM, SRAM, SDRAM, etc. Stored on any one or on a combination of computer readable media, the present invention includes software for controlling the computer system 801, for driving a device or devices for implementing the invention, and for enabling the computer system 801 to interact with a human user. Such software may include, but is not limited to, device drivers, operating systems, development tools, and applications software. Such computer readable media further includes the computer program product of the present invention for performing all or a portion (if processing is distributed) of the processing performed in implementing the invention.

The computer code devices of the present invention may be any interpreted or executable code mechanism, including but not limited to scripts, interpreters, dynamic link libraries, Java classes, and complete executable programs. Moreover, parts of the processing of the present invention may be distributed for better performance, reliability, and/or cost.

The term "computer readable medium" as used herein refers to any medium that participates in providing instructions to processor 805 for execution. A computer readable medium may take many forms, including but not limited to, non- olatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical, magnetic disks, and magneto-optical disks, such as storage device 811. Volatile media includes dynamic memory, such as main memory 807. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus 803. Transmission media also may also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications.

Common forms of computer readable media include, for example, hard disks, floppy disks, tape, magneto-optical disks, PROMs (EPROM, EEPROM, Flash EPROM), DRAM, SRAM, SDRAM, or any other magnetic medium, compact disks (e.g., CD-ROM), or any other optical medium, punch cards, paper tape, or other physical medium with patterns of holes, a carrier wave (described below), or any other medium from which a computer can read.

Various forms of computer readable media may be involved in carrying out one or more sequences of one or more instructions to processor 805 for execution. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions for implementing all or a portion of the present invention remotely into a dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 801 may receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal. An infrared detector coupled to bus 803 can receive the data carried in the infrared signal and place the data on bus 803. Bus 803 carries the data to main memory 807, from which processor 805 retrieves and executes the instructions. The instructions received by main memory 807 may optionally be stored on storage device 811 either before or after execution by processor 805.

Computer system 801 also includes a communication interface 819 coupled to bus 803. As described previously, communication interface 819 can itself form a promotion output device 630b, 640b, or 650b wherein an electronic promotion is communicated electronically to a remote system. Such electronic promotions can include, for example, electronic coupons automatically transmitted to the register of a vendor, electronic order placed directly with a vendor upon the consumer's discretion, or credits allocated to a consumer's account upon purchase or order of a product. Communication interface 819 provides a two-way data communication coupling to a network link 821 that is connected to a local network 823. For example, communication interface 819 may be a network interface card to attach to any packet switched local area network (LAN). As another example, communication interface 819 may be an asymmetrical digital subscriber line (ADSL) card, an integrated services digital network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line. Wireless links may also be implemented. In any such implementation, communication interface 819 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.

Network link 821 typically provides data communication through one or more networks to other data devices. For example, network link 821 may provide a connection to a computer 825 through local network 823 (e.g., a LAN) or through equipment operated by a service provider, which provides communication services through a communications network 827. Communications network 827 can form network 620 of FIG. 11. In one embodiment, computer 825 is one of the interactions sites 630, 640, or 650, while computer 601 is the central database 610 of FIG. 11. In preferred embodiments, local network 823 and communications network 827 preferably use electrical, electromagnetic, or optical signals that carry digital data streams. The signals through the various networks and the signals on network link 821 and through communication interface 819, which carry the digital data to and from computer system 801, are exemplary forms of carrier waves transporting the information. Computer system 801 can transmit notifications and receive data, including program code, through the network(s), network link 821 and communication interface 819.

Obviously, numerous modifications and variations of the present invention are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the invention may be practiced otherwise than as specifically described herein.

Claims

CLAIMS:

1. A method comprising the steps of: receiving identification information from a consumer; identifying said consumer and a motivation factor provided by said consumer using said identification information, said motivation factor corresponding to a ground that influences a decision to purchase of said consumer; selecting a targeted promotion based upon said motivation factor provided by said consumer; and providing said consumer with said targeted promotion.

2. The method according to claim 1, further comprising the step of querying said consumer regarding said motivation factor behind said promotion request.

3. The method according to claim 2, wherein said step of querying is performed prior to said step of receiving.

4. The method according to claim 2, wherein said step of querying said consumer regarding said motivation factor comprises the step of querying said consumer regarding a taste of said consumer for said food product.

5. The method according to claim 2, wherein said step of querying said consumer regarding said motivation factor comprises the step of querying said consumer regarding at least one of a taste of a family member, a nutritional opinion, a financial opinion, a religious opinion, a social opinion, an ethical opinion, an opinion regarding a time needed for a food preparation, an opinion regarding a skill needed for said food preparation, an availability of a utensil needed for food preparation, and a presence of a food tradition for said food product.

6. The method according to claim 2, wherein said step of querying said consumer regarding said motivation factor comprises the steps of: listing a plurality of food products; and requesting a taste score regarding said plurality of food products.

7. The method according to claim 2, further comprising the step of storing a consumer response to said step of querying in a database.

8. The method according to claim 7, wherein said consumer response is a score.

9. The method according to claim 7, wherein said database is a central database and said step of querying is performed at a remote terminal.

10. The method according to claim 7, wherein said database is located at a consumer's home computer and said step of querying is performed from said consumer's home computer.

11. The method according to claim 1, further comprising the step of analyzing said motivation factor in light of further information.

12. The method according to claim 11, wherein said further information comprises demographic information regarding said consumer.

13. The method according to claim 11, wherein said further information comprises food characteristic information.

14. The method according to claim 1, further comprising the step of receiving a promotion request from said consumer.

15. The method according to claim 14, wherein said step of receiving a promotion request comprises the step of receiving at least one of a food product recommendation request and a recipe recommendation request.

16. The method according to claim 7, further comprising: querying said consumer regarding said motivation factor behind said promotion request including asking said consumer to identify at least one of a time available for a preparation of said particular meal, a skill available for said preparation of said particular meal, and a nutritional concern of those who will be eating said particular meal, wherein: said promotion request includes a request for a recommendation for a particular meal.

17. The method according to claim 1, wherein said step of providing said consumer with said targeted promotion comprises the step of providing said consumer with at least one of an offer, an advertisement, an incentive, a coupon, a commercial, a recipe, and a communication.

18. The method according to claim 1, wherein said motivation factor corresponds to a ground that influences a decision to purchase a food product.

19. A method comprising the steps of: storing electronically information regarding a plurality of food products; querying an individual regarding tastes of said individual for said plurality of food products; storing electronically responses of said individual to said querying regarding said plurality of food products; and providing a promotion to said individual to encourage said individual to try a particular food product.

20. The method of claim 19, further comprising the steps of: querying said individual regarding said tastes of an individual for said particular food product; and storing electronically responses of said individual to said querying regarding said particular of food product.

21. A method comprising the steps of: receiving identification information from a consumer; identifying said consumer and a motivation factor provided by said consumer using said identification information, said motivation factor corresponding to a ground that influences a decision to purchase of said consumer; selecting a targeted promotion related to a food product of a client based on said motivation factor provided by said consumer; providing said consumer with said targeted promotion related to said food product; and charging said client.

22. The method according to Claim 21, wherein said step of selecting is also based upon a list of client food products.

23. A terminal configured to provide a suitable promotion to a consumer, comprising: means for receiving identification information from said consumer; means for identifying said consumer and a motivation factor provided by said consumer using said identification information, said motivation factor corresponding to a ground that influences a decision to purchase of said consumer; means for selecting said suitable promotion for said consumer; and means for providing said suitable promotion to said consumer.

24. The terminal of claim 23, further comprising: means for storing data records regarding said motivation factor provided by said consumer; means for writing and reading said data records to and from said means for storing, and means for analyzing said data records to ascertain said suitable promotion.

25. The terminal of claim 24, further comprising means for transmitting data between said means for processing said data records and said means for providing said suitable promotion.

26. The terminal of claim 23, wherein said means for identifying is located in a food store.

27. The terminal of claim 23, wherein said means for identifying is located in a consumer's home.

28. The terminal of claim 23, wherein said means for providing is located in a food store.

29. The terminal of claim 23, wherein said means for providing is located in a consumer's home.

30. The terminal of claim 23, wherein said motivation factors comprise a taste of said consumer for a food product.

31. The terminal of claim 23, wherein said motivation factors comprise at least one of a taste of a family member, a nutritional opinion, a financial opinion, a religious opinion, a social opinion, an ethical opinion, an opinion regarding a time needed for a food preparation, an opinion regarding a skill needed for said food preparation, an availability of a utensil needed for food preparation, and a presence of a food tradition for a food product.

32. A system comprising: an input device configured to receive identification information from a consumer; a motivation factor database configured to store a motivation factor data record regarding said consumer; a processor configured to identify said consumer using said identification information, to retrieve said motivation factor data record regarding said consumer from said database, and to select a promotion targeted to said consumer using said motivation factor data record; and an output device configured to provide said promotion to said consumer.

33. The system according to claim 32, further comprising: a network connecting said processor with at least one of said input device and said output device.

34. The system according to claim 32, wherein said motivation factor data record contains information in regards to the taste of said consumer for a food product.

35. The system according to claim 32, further comprising a querying device configured to query said consumer in regard to a motivation factor of said consumer.

36. The system according to claim 35, wherein said querying device further comprises: a query output device configured to indicate a query to said consumer; and a response input device configured to receive a consumer response to said query.

37. The system according to claim 32, wherein said input device further comprises a response input device configured to receive a consumer request for promotion.

38. The system according to claim 32, wherein said promotion is automatically transmitted to a vendor on behalf of said consumer.

39. The system according to claim 32, wherein said promotion comprises: a recipe suggestion; and a further promotion related to said recipe.

40. A system comprising: means for inputting a request for promotion from a consumer; means for processing said request for promotion; and means for providing said request to said consumer.

41. A computer readable medium containing program instructions for execution on a computer system, which when executed by a computer, cause the computer system to perform the method recited in any of claims 1-22.