WO2016003399A1 - Identifying feasible product configurations for consumers - Google Patents
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- WO2016003399A1 WO2016003399A1 PCT/US2014/044814 US2014044814W WO2016003399A1 WO 2016003399 A1 WO2016003399 A1 WO 2016003399A1 US 2014044814 W US2014044814 W US 2014044814W WO 2016003399 A1 WO2016003399 A1 WO 2016003399A1
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Abstract
Example embodiments relate to identifying feasible product configurations for consumers. In this manner, the embodiments disclosed herein enable obtaining user input comprising a product category and a set of criteria. Based on the set of criteria and product category, order history information may be accessed and a set of product configurations matching the set of criteria and product category may be determined from the order history information. For each product configuration in the set of product configurations, a a set of metrics may be maintained. An ordered set of product configurations from the set of product configurations may be determined based on the set of metrics associated with each individual product configuration. A feasibility check may be performed on a product configuration in the ordered set of product configurations.
Description
IDENTIFYING FEASIBLE PRODUCT CONFIGURATIONS FOR CONSUMERS
BACKGROUND
[0001 ] Merchants often attempt to identify products that may be palatable to their consumers. These products may be products already available to the consumer, an identification of products to manufacture for consumers, and/or other types of products.
BREF DESC IPTION OF THE DRA SNGS
[0002] The following detailed description references the drawings, wherein:
[0003] FIG. 1 is a block diagram of an example computing device for identifying feasible product configurations for consumers;
[0004] FIG. 2 is a block diagram of an example computing device for identifying feasible product configurations for consumers;
[0005] FIG. 3 is a flowchart of an example method for execution by a computing device for identifying feasible product configurations for consumers;
[0006] FIG. 3A is a flowchart of an example method for execution by a computing device for determining a set of product configurations from order history information;
[0007] FIG. 3B is a flowchart of an example method for execution by a computing device for performing a feasibility check for a product configuration; and
[0008] FIG. 3C is a flowchart of an example method for execution by a computing device for performing a feasibility check for a product configuration.
DETAILED DESCRSPTSO
[0009] The following detailed description refers to the accompanying drawings. Wherever possible, the same reference numbers are used in the drawings and the following description to refer to the same or similar parts. While several examples are described in this document, modifications, adaptations, and other implementations are possible. Accordingly, the following detailed description does not limit the disclosed examples, instead, the proper scope of the disclosed examples may be defined by the appended claims.
[0010] Merchants often attempt to identify products that may be palatable to their consumers. These products may be products already available to the consumer, products to manufacture for consumers, and/or other types of products. Determining
what products are both palatable to a consumer and feasible for production may involve time-consuming and complex processing.
[001 1 ] Example embodiments relate to identifying feasible product configurations for consumers in a manner customized for a consumer. A consumer may comprise, for example, an individual buyer, a merchant, a corporation, and/or other entity that may consume a product or make a product available for consumption. As such, the feasible product configurations may be more likely to be acceptable for a consumer. By recognizing customer preferences and performing feasibility checks on product configurations selected from an order transaction history based on customer preferences, the identification of product configurations for a consumer may be more efficient and provide better results to a consumer.
[0012] To that end, the embodiments disclosed herein enable obtaining user input comprising a product category and a set of criteria to determine a set of optimal product configurations for that consumer. Based on the set of criteria and product category, order history information may be accessed and a set of product configurations matching the set of criteria and product category may be determined from the order history information. For each product configuration in the set of product configurations, a set of metrics may be maintained. An ordered set of product configurations from the set of product configurations may be determined based on the set of metrics associated with each individual product configuration. A feasibility check may be performed on product configurations in the ordered set of product configurations until an optimal set of product configurations are determined.
[0013] Referring now to the drawings, FIG. 1 is a block diagram of an example computing device 100 for identifying feasible product configurations for consumers. Computing device 100 may be a cloud server, a mainframe, notebook, desktop, tablet, workstation, mobile device, or any other device suitable for executing the functionality described below, in the embodiment of FIG. 1 , computing device 100 includes a non- transitory machine-readable storage medium 120 and a processor 1 10.
[0014] Processor 1 10 may be one or more central processing units (CPUs), microprocessors, and/or other hardware devices suitable for retrieval and execution of instructions stored in machine-readable storage medium 120. Processor 1 10 may fetch, decode, and execute program instructions 121 , 122, 123, 124, and/or other instructions to identify feasible product configurations for consumers, as described below. As an alternative or in addition to retrieving and executing instructions, processor 1 10 may
include one or more electronic circuits comprising a number of electronic components for performing the functionality of one or more of instructions 121 , 122, 123, 124, and/or other instructions.
[0015] In one example, the program instructions 121 , 122, 123, 124, and/or other- instructions can be part of an installation package that can be executed by processor 1 10 to implement the functionality described herein. In this case, memory 120 may be a portable medium such as a CD, DVD, or flash drive or a memory maintained by a computing device from which the installation package can be downloaded and installed, in another example, the program instructions may be part of an application or applications already installed on computing device 100.
[0016] Machine-readable storage medium 120 may be any hardware storage device for maintaining data accessible to computing device 100. For example, machine- readable storage medium 120 may include one or more hard disk drives, solid state drives, tape drives, and/or any other storage devices. The storage devices may be located in computing device 100 and/or in another device in communication with computing device 100. For example, machine-readable storage medium 120 may be any electronic, magnetic, optical, or other physical storage device that stores executable instructions. Thus, machine-readable storage medium 120 may be, for example, Random Access Memory (RAM), an Electrically-Erasable Programmable Read-Oniy Memory (EEPROM), a storage drive, an optical disc, and the like. As described in detail below, machine-readable storage medium 120 may be encoded with executable instructions for identifying feasible product configurations for consumers. As detailed below, storage medium 120 may maintain and/or store the data and information described herein.
[0017] User input instructions 121 , when executed by processor 1 10, may obtain user input from a user. The user input may comprise, for example, at least a product category and/or a set of criteria. Examples of product categories may include laptops, servers, mobile devices, and/or other categories of products. The set of criteria may comprise, for example, a geographic location of the product (e.g., worldwide, one or more regions, etc.), a date range for transactions to be considered from the order transaction history , a number of results requested (e.g., a number of product configurations to provide to the user), one or more product types to exclude from the product configurations, one or more product types to include in the product configurations, a minimum number of components in the product configurations, a maximum number of
components in the product configurations, required compiiance with one or more standards, particular characteristics associated with a product type, customer industry, and/or other criteria. In some examples, the set of criteria may also include a minimum support threshold, which may comprise a minimum percentage of transactions in which the product configurations should be included in order to be provided to the user as a result of the user input.
[0018] in some examples, user input instructions 121 , when executed by processor 1 10, may require entry of information related to a product type. For example, responsive to providing product configurations for a computing device, the user input instructions 121 , when executed by processor 1 10, may require information related to a default product type that may necessarily be included in the end product, in an example of a computing device, a default product type may be a processor, a chassis, and/or other required component of a computing device, in these examples, the optimal set of product configurations provided to the user may comprise one or more product configurations for each individual product available for a default product type. Further, based on the product category selected by the user, the user input instructions 121 , when executed by processor 1 10, may provide additional required fields related to default product types to be included for determining the optimal set of product configurations to provide to the user.
[0019] Product configuration determination instructions 122, when executed by processor 1 10, may access order history information and determine a set of product configurations from the order history information that match the set of criteria and product category received from the user. Order history information may comprise, for example, a record of all transactions performed, requested, and/or otherwise managed by the merchant. Order history information is not limited to the examples described herein.
[0020] An individual product configuration (and/or information associated with an individual product configuration) of the determined set of product configurations may comprise, for example, a product configuration identifier, a set of component identifiers for each component in the product configuration, and/or other information related to the product configuration, in some examples, an individual product configuration may also comprise how many such product configurations have been ordered, characteristics of one or more components in the product configuration, region of availability of the product configuration, revenue associated with the product configuration, margin associated with
the product configuration, custorner(s) and/or customer industry associated with the product configuration, and/or other information related to the product configuration.
[0021 ] The product configuration determination instructions 122, when executed by processor 1 10, may determine the set of product configurations based on information stored in the non-transitory machine readable storage medium 120. For example, the product configuration determination instructions 122, when executed by processor 1 10, may determine possible product configurations by determining product types and/or product categories requested and comparing them to products, product types, and/or other information stored in the non-transitory machine-readable storage medium 120.
[0022] In another example, the product configuration determination instructions 122, when executed by processor 1 10, may apply frequent itemset mining algorithm to determine the set of product configurations from the order history information. The product configuration determination instructions 122, when executed by processor 1 10, may apply the Apriori algorithm to find the frequent itemsets in the order history.
[0023] In some examples, the product configuration determination instructions 122, when executed by processor 1 10, may use a minimum support threshold to determine the set of product configurations (e.g., using the frequent itemset mining algorithm). For example, responsive to the user input including a minimum support threshold, the product configuration determination instructions 122, when executed by processor 1 10, may include a product configuration in the set of product configurations responsive to the product configuration being included in a number of transactions in the order history information that is greater than (and/or equal to) the minimum support threshold. The product configuration determination instructions 122, when executed by processor 1 10, may check each product configuration determined to match the product category and set of criteria from the user input to further determine whether it exceeds the minimum support threshold requirement.
[0024] In some examples, the set of product configurations may comprise a closed set. For example, the product configuration determination instructions 122, when executed by processor 1 10, may remove any product configuration that is included within another product configuration in the set of product configurations, in another example, the product configuration determination instructions 122, when executed by processor 1 10, may remove any product configuration that includes all of the components of another product configuration included in the set of product configurations.
[0025] In some examples, the product configuration determination instructions 122, when executed by processor 1 10, may exclude any product configurations that comprise a product type, particular component, component with particular characteristics, and/or other component responsive to the user input comprising information related to excluding such a component. In some examples, the product configuration determination instructions 122, when executed by processor 1 10, may exclude any transactions from the order history information that include such a component before determining the set of product configurations.
[0026] in some examples, the product configuration determination instructions 122, when executed by processor 1 10, may exclude any product configurations that do not comprise a product type, particular component, component with particular characteristics, and/or other component responsive to the user input comprising information related to requiring such a component in the product configuration, in some examples, the product configuration determination instructions 122, when executed by processor 1 10, may exclude any transactions from the order history information that do not include such a component before determining the set of product configurations.
[0027] in some examples, the product configuration determination instructions 122, when executed by processor 1 10, may filter the order history information based on the lifecycie of products included in the order history information. For example, responsive to a product no longer being manufactured (and/or otherwise being unavailable), the product configuration determination instructions 122, when executed by processor 1 10, may filter the order history information to remove that product and/or transactions comprising that product. The product configuration determination instructions 122, when executed by processor 1 10, may obtain information related to the lifecycie of the product from a user, from accessing information stored at the non-transitory machine readable storage medium 120, and/or from other sources.
[0028] The manner in which the set of product configurations is determined is not limited to the examples described herein and may include one or more, ail, or none of the examples described herein
[0029] For each product configuration in the set of production configurations, the product configuration determination instructions 122, when executed by processor 1 10, may maintain a set of metrics. The set of metrics may comprise, for example, a frequency metric and/or other metrics. The frequency metric may comprise information related to a number of transactions comprising the product configuration, in some
examples, the product configuration determination instructions 122, when executed by processor 1 10, may determine a frequency metric for each product configuration in the set of product configurations while determining the set of product configurations (e.g., during the Apriori algorithm, etc.).
[0030] in some examples, the product configuration determination instructions 122, when executed by processor 1 10, may also maintain other metrics with each product configuration. For example, the set of metrics may also comprise a total revenue of transactions comprising the product configuration, total margin of transactions comprising the product configuration, total revenue or margin associated with the product configuration, total cost of the product configuration, information related to each individual component of the product configuration, a number of components in the product configuration, characteristics for one or more components in the product configuration (e.g., specifications, standard compliancy, and/or other information that may be maintained in the set of metrics for a product configuration), a minimum, maximum and average price of the product configuration in the transaction history, a minimum, maximum and average price of the product configuration per chassis (e.g., for a server or computing device), region information, inventory information, standard compliancy, and/or other information related to the product configuration.
[0031 ] The product configuration selection instructions 123, when executed by processor 1 10, may determine an ordered set of product configurations from the set of product configurations determined by the product configuration determination instructions 122. The product configuration selection instructions 123, when executed by processor 1 10, may determine a subset of the set of product configurations as the ordered set of product configurations. As such, the system may reduce the amount of product configurations for which a feasibility check (as described below) may need to be performed.
[0032] in some examples, the product configuration selection instructions 123, when executed by processor 1 10, may determine the ordered set based on the set of metrics associated with each individual product configuration in the set of product configurations. For example, the product configuration selection instructions 123, when executed by processor 1 10, may determine the ordered set of product configurations based on the frequency metric associated with each product configuration in the set of product configurations. The product configuration selection instructions 123, when executed by processor 1 10, may order the product configurations in order of popularity (e.g., based
on the frequency metric associated therewith) and may select a predetermined number of the most popular product configurations to include in the ordered set of product configurations. The product configuration selection instructions 123, when executed by processor 1 10, may determine the predetermined number of product configurations to include based on input received from the user, information stored in the non-transitory machine-readable storage medium, and/or based on other information.
[0033] in another example, the product configuration selection instructions 123, when executed by processor 1 10, may use the frequency and/or other metrics from the set of metrics to determine the ordered set of product configurations. For example, the product configuration selection instructions 123, when executed by processor 1 10, may use a desired number of product types, a number of components, availability of a product configuration, revenue, standard compliancy, and/or other metrics) to order the product configurations.
[0034] Responsive to a product configuration from the set of product configurations being included in the ordered set of product configurations, the product configuration selection instructions 123, when executed by processor 1 10, may revise the metrics associated with each product configuration in the set of product configurations not yet included in the ordered set of product configurations. For example, for a particular- product configuration, the product configuration selection instructions 123, when executed by processor 1 10, may deduct the number of transactions common to the included product configuration and the particular product configuration from the frequency metric associated with the particular product configuration. in some examples, the product configuration selection instructions 123, when executed by processor 1 10, may adjust one or more other metrics for the particular product configuration as well.
[0035] The feasibility check instructions 124, when executed by processor 1 10, may perform a feasibility check on one or more product configurations in the ordered set of product configurations. The feasibility check instructions 124, when executed by processor 1 10, may perform a feasibility check on product configurations in the ordered set of product configuration (e.g., in the order in which the product configurations are included in the ordered set). The feasibility check instructions 124, when executed by processor 1 10, may perform these feasibility checks until the optimal set of product configurations is determined. The feasibility check instructions 124, when executed by processor 1 10, may determine that the optimal set is complete based on a number of
product configurations in the optimal set, based on the variety of product configurations in the optimal set, and/or based on other criteria. The criteria may be received from the user, predetermined based on product category, stored in the non-transitory machine readable storage medium 120, and/or otherwise determined.
[0036] In some examples, the feasibility check instructions 124, when executed by processor 1 10, may perform a product check on a product configuration in the ordered set of product configurations as part of a feasibiiity check. For example, the feasibiiity check instructions 124, when executed by processor 1 10, may determine a set of products from the order history information, where each product is included in a transaction that also includes a same product configuration. For a product of the set of products that is not included in the product configuration, the feasibiiity check instructions 124, when executed by processor 1 10, may determine whether that product is included in at least a percentage of transactions that include the product configuration. Responsive to determining that the product is included in at least the predetermined percentage of transactions, the feasibility check instructions 124, when executed by processor 1 10, may identify the product configuration as not feasible.
[0037] in some examples, the feasibility check instructions 124, when executed by processor 1 10, may perform a product type check on a product configuration in the ordered set of product configurations as part of a feasibiiity check. For example, the feasibiiity check instructions 124, when executed by processor 1 10, may determine a set of products from the order history information, where each product is included in a transaction that also includes a same product configuration. For a product of the set of products that is not included in the product configuration, the feasibiiity check instructions 124, when executed by processor 1 10, may replace the product with a product type that includes the product. The feasibiiity check instructions 124, when executed by processor 1 10, may then determine whether that product type is included in at least a percentage of transactions that include the product configuration. Responsive to determining that the product type is included in at least the predetermined percentage of transactions, the feasibility check instructions 124, when executed by processor 1 10, may identify the product configuration as not feasible.
[0038] In some examples, the feasibility check instructions 124, when executed by processor 1 10, may perform both the product check and the product type check for each product in a transaction that comprises the product configuration from the order history information. Responsive to no products or product types that are not included in the
product configuration being included in at least the predetermined percentage of transactions, the feasibility check instructions 124, when executed by processor 1 10, may determine that the product configuration is feasible and may include the product configuration in the optimal set of product configurations,
[0039] in some examples, the feasibility check instructions 124, when executed by processor 1 10, may perform the product check for each product in a transaction comprising the product configuration and may then perform the product type check for each such product. In other examples, the feasibility check instructions 124, when executed by processor 1 10, may perform the product type check first and then perform the product check, in yet other examples, the feasibility check instructions 124, when executed by processor 1 10, may only perform one of the product check and the product type check. The feasibility check instructions 124, when executed by processor 1 10, may perform one or both checks in either order based on instructions from a user, information stored in the non-transitory machine readable storage medium 120, and/or based on other criteria. In some examples, the feasibility check instructions 124, when executed by processor 1 10, may perform one or both of the product check and the product type check using association rule mining. The feasibility check performed by the feasibility check instructions 124, when executed by processor 1 10, may not be limited to the examples described herein.
[0040] FIG. 2 is a block diagram of an example computing device 200 for identifying feasible product configurations for consumers, As with computing device 100, computing device 200 may be a cloud server, a mainframe, notebook, desktop, tablet, workstation, mobile device, or any other device suitable for executing the functionality described below. As with processor 1 10 of FIG, 1 , processor 220 may be one or more CPUs, microprocessors, and/or other hardware devices suitable for retrieval and execution of instructions.
[00413 As detailed below, computing device 200 may include a series of engines 220- 250 for identifying feasible product configurations for consumers. Each of the engines may generally represent any combination of hardware and programming. For example, the programming for the engines may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the engines may include at least one processor of the computing device 200 to execute those instructions. In addition or as an alternative, each engine may include one or more hardware devices including electronic circuitry for implementing the functionality described below.
[0042] Criteria selection engine 220 may obtain user input from a user, the user input comprising a product category and a set of criteria. In some examples, the criteria selection engine 220 may obtain the user input in a manner the same as or similar to that of the user input instructions 122 of computing device 100. Further details regarding an example implementation of criteria selection engine 220 are provided above in connection with user input instructions 122 of FIG. 1 .
[0043] Product configuration selection engine 230 may determine a set of product configurations that match the set of criteria and the product category from order history information based on the set of criteria and the product category. The product configurations election engine 230 may also maintain a set of metrics for each product configuration in the set of product configurations and determine an ordered set of product configurations from the set of product configurations based on the set of metrics associated with each individual product configuration in the set of product configurations. In some examples, the product configuration selection engine 230 may determine a set of matching product configurations in a manner the same as or similar to that of the computing device 1 (30. Further details regarding an example implementation of product configuration selection engine 230 are provided above in connection with product configuration selection instructions 123 of FIG. 1 .
[0044] Feasibility check engine 240 may perform a feasibility check on product configurations in the ordered set of product configurations. The feasibility check engine 240 may also determine an optimal set of product configurations from the ordered set of product configurations based on the performed feasibility checks. In some examples, the feasibility check engine 240 may perform a feasibility check and determine the optimal set of product configurations in a manner the same as or similar to that of the computing device 100. Further details regarding an example implementation of feasibility check engine 240 are provided above in connection with feasibility instructions 124 of FIG. 1 .
[0045] Product configuration access engine 250 may provide access, for the user, to the optimal set of product configurations. For example, the product configuration access engine 250 may provide the user access to information related to the optimal set of product configurations. The information related to the optimal set of product configurations may comprise, for example, information related to each product configuration in the optimal set. The product configuration access engine 250 may provide the user access by providing a report, sending the user a link to a website
including the information, and/or otherwise providing access. The type of access and/or information included with the access may be predetermined, determined based on a request by the user, determined based on information stored in the non-transitory machine readable storage medium 120, and/or otherwise determined. Further details regarding an example implementation of product configuration access engine 250 are provided above in connection with computing device 100 of FIG. 1 .
[0046] FIG. 3 is a flowchart of an example method for execution by a computing device for identifying feasible product configurations for consumers.
[0047] Although execution of the methods described below are with reference to computing device 100 of FIG. 1 and/or computing device 200 of FIG. 2, other suitable devices for execution of this method will be apparent to those of skill in the art. The method described in FIG. 3 and other figures may be implemented in the form of executable instructions stored on a machine-readable storage medium, such as storage medium 120, by one or more engines described herein, and/or in the form of electronic circuitry.
[0048] In an operation 300, a set of product configurations may be determined from order history information. For example, the computing device 100 (and/or the user input instructions 121 . the criteria selection engine 220, or other resource of the computing device 100) may determine the set of product configurations. The computing device 100 may determine the set of product configurations a manner similar or the same as that described above in relation to the execution of the user input instructions 121 , the criteria selection engine 220, and/or other resource of the computing device 100.
[0049] In some examples, the set of product configurations may be determined in various manners. FIG. 3A is a flowchart of an example method for execution by a computing device for determining a set of product configurations.
[0050] In an operation 301 , the order history information may be filtered based on the lifecycle of products included in the order history information. For example, the computing device 100 (and/or the user input instructions 121 , the criteria selection engine 220, and/or other resource of the computing device 100) may filter the order history information. The computing device 100 may filter the order history information in a manner similar or the same as that described above in relation to the execution of the user input instructions 121 , the criteria selection engine 220, and/or other resource of the computing device 100.
[0051 ] In an operation 302, the set of product configurations may be determined from the filtered order history information. For example, the computing device 100 (and/or the user input instructions 121 , the criteria selection engine 220, and/or other resource of the computing device 100) may determine the set of product configurations from the filtered order history information. The computing device 100 may determine the set of product configurations from the filtered order history information associated with the first subset of proxies in a manner similar or the same as that described above in relation to the execution of the user input instructions 121 , the criteria seiection engine 220, and/or other resource of the computing device 100.
[0052] Returning to FIG. 3, in an operation 310, a set of metrics may be maintained for each product configuration. For example, the computing device 100 (and/or the product configuration selection instructions 123, product configuration selection engine 230, or other resource of the computing device 100) may maintain the set of metrics. The computing device 100 may maintain the set of metrics in a manner similar or the same as that described above in relation to the execution of the product configuration selection instructions 123, product configuration seiection engine 230, or other resource of the computing device 100.
[0053] In an operation 320, an ordered set of product configurations may be determined based on the set of metrics for each product configuration. For example, the computing device 100 (and/or the product configuration selection instructions 123, the product configuration seiection engine 230, or other resource of the computing device 100) may determine the ordered set of product configurations. The computing device 100 may determine the ordered set of product configurations in a manner similar or the same as that described above in relation to the execution of the product configuration selection instructions 123, the product configuration selection 230, or other resource of the computing device 100.
[0054] in an operation 330, a feasibility check may be performed on a product configuration. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 1 (30) may perform the feasibility check. The computing device 100 may perform the feasibility check in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0055] In some examples, a feasibility check for a product configuration may be performed in various manners. FIG. 3B is a flowchart of an example method for execution by a computing device for performing a feasibility check for a product configuration. FIG. 3C is a flowchart of another example method for execution by a computing device for performing a feasibility check for a product configuration, in some examples, performing a feasibility check for a product configuration may comprise performing the methods described in both FIGS. 3B and 3C. in some examples, the method described in FIG. 3B may be performed first while the method in FIG. 3C may be performed responsive to the method described in FIG. 3B determining that the product was not found to be infeasible. In other examples, the method described in FIG. 3C may be performed first while the method in FIG. 3B may be performed responsive to the method described in FIG. 3C determining that the product was not found to be infeasible. In yet other examples, the methods described in FIGS. 3B and 3C may be performed concurrently.
[0056] As mentioned above, FIG. 3B is a flowchart of an example method for execution by a computing device for performing a feasibility check for a product configuration.
[0057] In an operation 331 , a set of products may be determined from the order history information, where each product is included in a transaction that also includes a same product configuration. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may determine the set of products. The computing device 100 may determine the set of products in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0058] in an operation 332, for a product of the set of products that is not included in the product configuration, a determination is made as to whether that product is included in a percentage of transactions that include the product configuration. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may determine whether the product is included in a percentage of transactions that include the product configuration. The computing device 100 may determine whether the product is included in a percentage of transactions that include the product configuration in a manner similar or the same as that described above in relation to the execution of the feasibility check
instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0059] In an operation 333, the product configuration may be identified as not feasible responsive to determining that the product is included in the predetermined percentage of transactions. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may identify the product configuration as infeasible. The computing device 100 may identify the product configuration as infeasible in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0060] As mentioned above, FIG. 3C is a flowchart of another example method for execution by a computing device for performing a feasibility check for a product configuration.
[0061 ] In an operation 334, a set of products may be determined from the order history information, where each product is included in a transaction that also includes a same product configuration. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may determine the set of products. The computing device 100 may determine the set of products in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0062] In an operation 335, for a product of the set of products that is not included in the product configuration, replace the product with a product type that includes the product. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may replace the product with the product type. The computing device 100 may replace the product with the product type in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0063] In an operation 336, for the product type, a determination is made as to whether that product type is included in a percentage of transactions that include the product configuration. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may determine whether the product type is included in a
percentage of transactions that include the product configuration. The computing device 100 may determine whether the product type is included in a percentage of transactions that include the product configuration in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0064] In an operation 337, the product configuration may be identified as not feasible responsive to determining that the product type is included in the predetermined percentage of transactions. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may identify the product configuration as infeasibie. The computing device 100 may identify the product configuration as infeasibie in a manner- similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, and/or other resource of the computing device 100.
[0065] Returning to FIG. 3, in an operation 340, a set of optimal product configurations may be determined from the determined set of product configurations based on the performed feasibility check. For example, the computing device 100 (and/or the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100) may determine the set of optimal product configurations. The computing device 10(3 may determine the set of optimal product configurations in a manner similar or the same as that described above in relation to the execution of the feasibility check instructions 124, the feasibility check engine 240, or other resource of the computing device 100.
[0066] The foregoing disclosure describes a number of example embodiments for identifying feasible product configurations for consumers. The disclosed examples may include systems, devices, computer-readable storage media, and methods for identifying feasible product configurations for consumers. For purposes of explanation, certain examples are described with reference to the components illustrated in FIGS. 1 -3C, The functionality of the illustrated components may overlap, however, and may be present in a fewer or greater number of elements and components. Further, all or part of the functionality of illustrated elements may co-exist or be distributed among several geographically dispersed locations. Moreover, the disclosed examples may be implemented in various environments and are not limited to the illustrated examples.
[0067] Further, the sequence of operations described in connection with FIGS. 1-3C are examples and are not intended to be limiting. Additional or fewer operations or combinations of operations may be used or may vary without departing from the scope of the disclosed examples. Furthermore, implementations consistent with the disclosed examples need not perform the sequence of operations in any particular order. Thus, the present disclosure merely sets forth possible examples of implementations, and many variations and modifications may be made to the described examples. All such modifications and variations are intended to be included within the scope of this disclosure and protected by the following claims.
Claims
1 . A non-transitory machine-readable storage medium comprising instructions executable by a processor of a computing device for identifying feasible product configurations for consumers to:
obtain user input from a user, the user input comprising a product category and a set of criteria;
based on the set of criteria and the product category included in the user input, access order history information and determine a set of product configurations that match the set of criteria and the product category from the order history information; for each product configuration in the set of product configurations, maintain a set of metrics;
determine an ordered set of product configurations from the set of product configurations based on the set of metrics associated with each individual product configuration in the determined set of product configurations; and
perform a feasibility check on a product configuration in the ordered set of product configurations.
2. The storage medium of claim 1 , wherein the instructions to perform the feasibility check on an individual product configuration comprise instructions to:
determine, from a plurality of transactions included in the order history information, a set of products, wherein each product in the set of products is included in a transaction with the individual product configuration;
determine, for a product in the set of products that is not included in the individual product configuration, whether the product is included in a predetermined percentage of the plurality of transactions comprising the individual product configuration; and
responsive to determining that the product is included in the predetermined percentage of the plurality of transactions, identify the product configuration as not feasible.
3. The storage medium of claim 1 , wherein the instructions to perform the feasibility check on the individual product configuration comprise instructions to:
determine, from a plurality of transactions included in the order history information, a set of products, wherein each product in the set of products is included in a transaction with the individual product configuration;
for a product in the set of products that is not included in the individual product configuration, replace the product with a product type that comprises the product; determine whether the product type is included in a predetermined percentage of the plurality of transactions comprising the individual product configuration; and responsive to determining that the product type is included in the predetermined percentage of the plurality of transactions comprising the individual product configuration, identify the product configuration as not feasible.
4. The storage medium of claim 3, wherein the instructions to perform the feasibility check on the individual product configuration comprise instructions to: responsive to determining that the product is not included in at least a predetermined percentage of the plurality of transactions comprising the individual product configuration and responsive to determining that the product type is not included in the predetermined percentage of the plurality of transactions comprising the individual product configuration, identify the individual product configuration as feasible; and
responsive to identifying the individual product configuration as feasible, provide access, for the user, to the individual product configuration,
5. The storage medium of claim 1 , further comprising instructions executable by the processor of the computing device to:
responsive to including a product configuration in the determined set of product configurations, adjust a frequency metric of the set of metrics for each other product configuration in the set of product configurations that has not been included in the determined set of product configurations,
6. The storage medium of claim 1 , further comprising instructions executable by the processor of the computing device to:
determine the set of product configurations from the order history information based on a minimum support threshold, wherein the minimum support threshold
comprises a minimum percentage of transactions in the order history information that include an individual product configuration,
wherein the set of product configurations is determined by including an individual product configuration in the set of product configurations responsive to the individual product configuration being included in a percentage of transactions in the order history information greater than the minimum support threshold.
7. A computing device for identifying feasible product configurations for consumers, the computing device comprising:
a criteria selection engine to:
obtain user input from a user, the user input comprising a product category and a set of criteria; and
a product configuration selection engine to:
based on the set of criteria and the product category, determine a set of product configurations that match the set of criteria and the product category from order history information;
maintain a set of metrics for each product configuration in the set of product configurations; and
determine an ordered set of product configurations from the set of product configurations based on the set of metrics associated with each individual product configuration in the set of product configurations;
a feasibility check engine to:
perform a feasibility check on a subset of product configurations in the ordered set of product configurations; and
determine an optimal set of product configurations from the ordered set of product configurations based on the performed feasibility checks; and a product configuration access engine:
provide access, for the user, to the optimal set of product configurations.
8. The computing device of claim 7, wherein the feasibility check engine performs a feasibility check on an individual product configuration by:
determining, from a plurality of transactions included in the order history information, a set of products, wherein each product in the set of products is included in a transaction with the individual product configuration;
determining, for a product in the set of products that is not included in the individual product configuration, whether the product is included in a predetermined percentage of the plurality of transactions comprising the individual product configuration;
responsive to determining that the product is included in the predetermined percentage of the plurality of transactions, identify the product configuration as not feasible;
for a product in the set of products that is not included in the individual product configuration, replace the product with a product type that comprises the product; determining whether the product type is included in a predetermined percentage of the plurality of transactions comprising the individual product configuration; and
responsive to determining that the product type is included in the predetermined percentage of the plurality of transactions comprising the individual product configuration, identify the product configuration as not feasible,
9. The computing device of claim 8, wherein the feasibility check engine:
responsive to determining that the product is not included in at least a predetermined percentage of the plurality of transactions comprising the individual product configuration and responsive to determining that the product type is not included in the predetermined percentage of the plurality of transactions comprising the individual product configuration, identifies the individual product configuration as feasible; and
includes the identified individual product configuration in the optimal set of product configurations.
10. The computing device of claim 7, wherein the criteria selection engine:
requires the user input to include information related to a default product type.
1 1 . The computing device of claim 7, wherein the user input comprises
information related to a product type to exclude in the product configuration, and wherein the product configuration selection engine:
excludes from order history data any transaction that includes an item of the excluded product type,
12. A method for execution by a computing device for identifying feasible product configurations for consumers, the method comprising:
determining, from order history information, a set of product configurations that match a set of criteria and a product category included in user input obtained from a user;
for each product configuration in the set of product configurations, maintain a set of metrics, the set of metrics including a frequency metric;
determining an ordered set of product configurations from the set of product configurations based on the metrics associated with each individual product configuration in the set of product configurations;
performing a feasibility check on a subset of the product configurations in the ordered set of product configurations; and
determining an optimal set of product configurations from the ordered set of product configurations based on the performed feasibility checks.
13. The method of claim 12, wherein performing the feasibility checks comprises: determining, from a plurality of transactions included in the order history information, a set of products, wherein each product in the set of products is included in a transaction with the individual product configuration;
for a product in the set of products that is not included in the individual product configuration, replacing the product with a product type that comprises the product; determining whether the product type is included in a predetermined percentage of the plurality of transactions comprising the individual product configuration;
responsive to determining that the product type is included in the predetermined percentage of the plurality of transactions comprising the individual product configuration, identifying the product configuration as not feasible;
determining, for a product in the set of products that is not included in the individual product configuration, whether the product is included in a predetermined percentage of the plurality of transactions comprising the individual product configuration; and
responsive to determining that the product is included in the predetermined percentage of the plurality of transactions, identifying the product configuration as not feasible.
14. The method of claim 13, further comprising:
responsive to determining that the item is not included in at least a predetermined percentage of the plurality of transactions comprising the individual product configuration and responsive to determining that the individual product type is not included in the predetermined percentage of the plurality of transactions comprising the individual product configuration, identifying the individual product configuration as feasible; and
including the identified individual product configuration in the optimal set of product configurations.
15. The method of claim 12, further comprising:
filtering the order history information based on the lifecycle of products included in the order history information; and
determining the set of product configurations from the filtered order history information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/US2014/044814 WO2016003399A1 (en) | 2014-06-30 | 2014-06-30 | Identifying feasible product configurations for consumers |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/US2014/044814 WO2016003399A1 (en) | 2014-06-30 | 2014-06-30 | Identifying feasible product configurations for consumers |
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| Publication Number | Publication Date |
|---|---|
| WO2016003399A1 true WO2016003399A1 (en) | 2016-01-07 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/US2014/044814 WO2016003399A1 (en) | 2014-06-30 | 2014-06-30 | Identifying feasible product configurations for consumers |
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| Country | Link |
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| WO (1) | WO2016003399A1 (en) |
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| CN113052417A (en) * | 2019-12-27 | 2021-06-29 | 北京国双科技有限公司 | Resource allocation method and device |
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