COMPUTER-BASED ANALYSIS OF AFFILIATE SITE PERFORMANCE

• US 20100324979A1
• Filed: 08/09/2010
• Published: 12/23/2010
• Est. Priority Date: 11/12/2004
• Status: Active Grant

• Current Assignee: David L. Selinger, Dilip S. Kumar, Michelle K. Anderson, Paat Rusmevichientong
• Original Assignee: David L. Selinger, Dilip S. Kumar, Michelle K. Anderson, Paat Rusmevichientong
• Inventors: Rusmevichientong, Paat, Anderson, Michelle K., Selinger, David L., Kumar, Dilip S.
• Granted Patent: US 8,224,715 B2
• Time in Patent Office: Days
• US Class Current: 705/14.13
• 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 system analyzes the performance of affiliate 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, the method comprising:

generating, for each of a plurality of categories of affiliate sites, a respective set of item association data that identifies items that are purchased in combination relatively frequently by users referred by affiliate sites falling within the respective category; and

analyzing performance of a particular affiliate site that falls within a first category of said plurality of categories by comparing the set of item association data for said first category to transaction data associated with the particular affiliate site;

said method performed by a computer system that comprises one or more computers.

2. The method of claim 1, wherein analyzing the performance of the particular affiliate site comprises using the transaction data and association data in combination to identify items to list on the particular affiliate site to improve said performance.

3. The method of claim 1, wherein analyzing the performance of the particular affiliate site comprises detecting disparities between expected and actual quantities of specific items purchased by users referred by the particular affiliate site.

4. The method of claim 3, further comprising using said disparities to generate recommendations of items to list on the particular affiliate site to improve performance.

5. The method of claim 1, wherein the particular affiliate site comprises a plurality of item-specific links to the electronic commerce site, each item-specific link corresponding to a respective item represented in an electronic catalog of the electronic commerce site, and wherein analyzing the performance of the particular affiliate site comprises using the transaction data and association data in combination to generate a recommendation of at least one additional item-specific link to provide on the particular affiliate site to improve performance.

6. The method of claim 1, wherein each set of item association data comprises one or more association rules.

7. The method of claim 6, wherein each association rule identifies a first set of on items, X1, and a second set of items, X2, and specifies a conditional probability that a purchaser of X1 will also purchase X2.

8. The method of claim 6, wherein at least one of the association rules maps a two-item set to a single item.

9. The method of claim 1, wherein the item association data comprises data values reflective of frequencies with which specific items are purchased in combination.

10. The method of claim 1, wherein generating the item association data comprises using category information supplied by affiliates to identify affiliate sites falling within each of the plurality of categories.

11. The method of claim 1, wherein generating the item association data for each category comprises programmatically categorizing the affiliate sites based on at least one of (a) content of the affiliate sites, and (b) purchases made by users referred by the affiliate sites.

17. The computer system of claim 6, wherein each association rule identifies a first set of on items, X1, and a second set of items, X2, and specifies a conditional probability that a purchaser of X1 will also purchase X2.

12. A computer system for of analyzing the performance of affiliate sites that refer users to an electronic commerce site, said computer system comprising one or more computers, said computer system programmed to implement:

an association mining engine that generates, for each of a plurality of categories of affiliate sites, a respective set of item association data that identifies items that are purchased in combination relatively frequently by users referred by affiliate sites falling within the respective category; and

an analysis system that analyzes performance of a particular affiliate site that falls within a first category of said plurality of categories by comparing the set of item association data for said first category to transaction data associated with the particular affiliate site.

13. The computer system of claim 12, wherein the analysis system uses the association data and transaction data in combination to detect disparities between expected and actual quantities of specific items purchased by users referred by the particular affiliate site.

14. The computer system of claim 13, wherein the analysis system additionally uses the disparities to generate recommendations of additional items to list on the affiliate site to improve performance.

15. The computer system of claim 12, wherein the particular affiliate site comprises a plurality of item-specific links to the electronic commerce site, each item-specific link corresponding to a respective item represented in an electronic catalog of the electronic commerce site, and wherein the analysis system uses the transaction data and association data in combination to generate a recommendation of at least one additional item-specific link to provide on the particular affiliate site to improve performance.

16. The computer system of claim 12, wherein each set of item association data comprises one or more association rules.

18. The computer system of claim 12, wherein the computer system is additionally programmed to categorize the affiliate sites based on at least one of (a) content of the affiliate sites, and (b) purchases made by users referred by the affiliate sites.

19. Physical computer storage having stored thereon executable code that directs a computer system to perform a method that comprises:

generating, for each of a plurality of categories of affiliate sites, a respective set of item association data that identifies items that are purchased in combination relatively frequently by users referred by affiliate sites falling within the respective category; and

analyzing performance of a particular affiliate site that falls within a first category of said plurality of categories by comparing the set of item association data for said first category to transaction data associated with the particular affiliate site.