Method and system for analyzing the performance of affiliate sites

• US 7,797,197 B2
• Filed: 11/12/2004
• Issued: 09/14/2010
• Est. Priority Date: 11/12/2004
• Status: Expired due to Fees

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Kumar, Dilip S., Rusmevichientong, Paat, Anderson, Michelle K., Selinger, David L.
• Primary Examiner(s): Smith; Jeffrey A.
• Assistant Examiner(s): Misiaszek; Michael A.
• Application Number:
  US10/987,309
• Publication Number:
  US 20060106665A1
• Time in Patent Office: 2,132 Days
• Field of Search: 705/26, 705/27, 705/1
• US Class Current: 705/26.1
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0211 Determining the effectiveness of discounts or incentives
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A performance analysis engine analyzes the performance of affiliate web sites that provide links to specific items in an electronic catalog, and identifies catalog items that can be listed by such affiliate web sites to improve performance. An association mining component analyzes transaction data attributable to specific categories or types of affiliate web sites to identify items that are frequently purchased in combination by users of such sites. The detected item associations are used to evaluate, for a given affiliate site, whether significant disparities exist between the expected and actual sales quantities of specific items. The results of the analysis are incorporated into affiliate-specific performance reports, which may include specific recommendations for improving performance. The disclosed methods may also be used to analyze the performance of, and provide recommendations to, online sellers within an online mall, online marketplace, or online auction system.

Claims

1. A method of analyzing the performance of affiliate sites that refer users to an electronic commerce site that hosts an electronic catalog of items that are available for purchase, the method comprising:

by a computer system comprising one or more computers;

storing transaction data descriptive of purchases made by users referred to the electronic commerce site by a plurality of affiliate sites, said transaction data reflective of item-specific links provided on the affiliate sites, each item-specific link being specific to a particular item represented in the electronic catalog of the electronic commerce site, said item-specific links being selectable by users to access corresponding item descriptions in the electronic catalog;

applying an association-rule mining algorithm to the transaction data to generate a set of association rules, said association rules identifying items that tend to be purchased in combination by said users;

analyzing performance of a particular affiliate site by using the association rules, in combination with transaction data associated with the particular affiliate site, to identify one or more disparities between expected and actual quantities of specific items purchased by users referred by the particular affiliate site; and

generating, for presentation to an operator of the affiliate site, a recommendation of at least one item for which to provide an item-specific link on the affiliate site to improve the performance of the affiliate site, said at least one item identified based on the one or more identified disparities.

2. The method of claim 1, wherein each association rule identifies a first set of items, X1, and a second set of items, X2, and specifies a conditional probability that a purchaser of X1 will also purchase X2.

3. The method of claim 1, wherein each association rule comprises a data value representing a conditional probability that a purchaser of X1 will also purchase X2, where X1 and X2 are mutually exclusive sets of one or more items.

4. The method of claim 1, wherein at least one of the association rules maps a two-item set to a single item.

5. The method of claim 1, wherein the set of association rules is specific to a particular affiliate site category in which the particular affiliate site falls, such that the performance of the particular affiliate site is compared to the performance of other affiliate sites within said category.

6. The method of claim 5, wherein applying an association-rule mining algorithm comprises using category information supplied by affiliates to identify affiliate sites falling within said category.

7. The method of claim 1, wherein the association rules are specific to a particular type of affiliate site, and are generated based on transaction data attributable to affiliate sites of said type.

8. The method of claim 1, further comprising generating an electronic report reflective of the one or more disparities, and transmitting the report to a corresponding affiliate, said electronic report including said recommendation.

9. The method of claim 8, wherein the electronic report identifies at least one purchased item that provides a basis for the recommendation.

10. The method of claim 8, wherein the electronic report includes link coding for adding an item-specific affiliate link to the particular site.

21. The method of claim 1, wherein the method is performed in its entirety by execution of program code by said one or more computers.

11. Computer storage that stores executable code which, when executed by a computer system comprising one or more computers, causes the computer system to:

store transaction data descriptive of purchases made by users referred to the electronic commerce site by a plurality of affiliate sites, said transaction data reflective of item-specific links provided on the affiliate sites, each item-specific link being specific to a particular item represented in the electronic catalog of the electronic commerce site, said item-specific links being selectable by users to access corresponding item descriptions in the electronic catalog;

programmatically apply an association-rule mining algorithm to the transaction data to generate a set of association rules, said association rules identifying items that tend to be purchased in combination by said users;

programmatically analyze performance of a particular affiliate site by using the association rules, in combination with transaction data associated with the particular affiliate site, to identify one or more disparities between expected and actual quantities of specific items purchased by users referred by the particular affiliate site; and

generate, for presentation to an operator of the affiliate site, a recommendation of at least one item for which to provide an item-specific link on the affiliate site to improve the performance of the affiliate site, said at least one item identified based on the one or more identified disparities.

22. The computer storage of claim 11, wherein the executable code further instructs the computer system to communicate the recommendation to the operator of the affiliate site together with an indication of a basis for the recommendation, said basis including an identification of at least one item purchased by users referred by the affiliate site.

12. A system for analyzing the performance of affiliate sites that provide item-specific links to an electronic catalog of an electronic commerce site each item-specific link being specific to a particular item represented in the electronic catalog, and being selectable by users to access corresponding item information in the electronic catalog, the system comprising computer hardware configured to implement:

a data repository that stores transaction data descriptive of item purchases made from the electronic catalog by users referred by the affiliate sites, said transaction data reflective of an effectiveness of the item-specific links provided on the affiliate sites;

an association mining component that analyzes, and generates association rules reflective of, the transaction data stored in the data repository, said association rules identifying items that are associated based on purchase activities of referred users;

a disparity detection module that uses the association rules generated by the association mining component, in combination with transaction data descriptive of item purchases made by users referred by a particular affiliate site, to evaluate whether disparities exist between expected and actual performance of the particular affiliate site; and

a report generation component that uses the disparities detected by the disparity detection module to generate affiliate-specific recommendations regarding items for which to provide item-specific links, said report generation component thereby providing information for improving affiliate site performance.

13. The system of claim 12, wherein the disparity detection module evaluates whether disparities exist between expected and actual quantities of specific items purchased by users referred by the particular affiliate site.

14. The system of claim 12, wherein the association mining component generates an association rule that (a) identifies a first set, X1, of one or more items, and a second set, X2, of one or more items, and (b) specifies a conditional probability that a purchaser of X1 will also purchase X2, and wherein the disparity detection module uses the association rule to evaluate performance of the particular affiliate site with respect to an item in X2.

15. The system of claim 12, wherein the association mining component generates association rules comprising data values representing conditional probabilities that purchasers of X1 will also purchase X2, where X1 and X2 are sets of one or more items.

16. The system of claim 12, wherein the association mining component generates an association rule that maps a two-item set to a single item, and the disparity detection module uses the association rule to evaluate performance of the particular affiliate site with respect to the single item.

17. The system of claim 12, wherein the association mining component generates a set of association rules that is specific to an affiliate site category in which the particular affiliate site falls, and the disparity detection module uses the set of association rules to evaluate performance of the particular affiliate site relative to performance of other affiliate sites in said category.

18. The system of claim 17, wherein the association mining component uses category information supplied by affiliates to identify affiliate sites falling within said category.

19. The system of claim 12, wherein the report generation component is operative to generate an affiliate-specific report that includes link coding for adding a recommended item-specific link to an affiliate site.

20. The system of claim 12, wherein the report generation component is operative to generate, for the particular affiliate site, a report that (1) includes a recommendation of a first item for which to include an item-specific link, and (2) specifies a basis for the recommendation of the first item, said basis including an identification of a second item purchased by users referred by the particular affiliate site.