METHOD AND SYSTEM FOR PROVIDING PERFORMANCE METRICS

• US 20100205550A1
• Filed: 02/02/2010
• Published: 08/12/2010
• Est. Priority Date: 02/05/2009
• Status: Active Grant

• Current Assignee: Bazaarvoice Incorporated
• Original Assignee: Bazaarvoice Incorporated
• Inventors: Loyens, Jon, Legault, Jacy, Chen, Andrew
• Granted Patent: US 9,230,239 B2
• Time in Patent Office: Days
• US Class Current: 715/760
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Systems and methods to facilitate the collection and processing of content generated by users are disclosed. Specifically, in one embodiment, user generated content may be aggregated from multiple retailers. This user generated content may be processed to obtain a variety of statistical data associated with the user generated content, including an importance metric. This importance metric may be utilized to rank the products of the manufacturer such that statistical, or other, data related to the manufacturer'"'"'s products may be presented to a user in the order of product importance.

Claims

1. A method for processing user generated content in a system comprising a set of retailers coupled to a content processing system having a processor, comprising

receiving first user generated content of a first type associated with a plurality of products, where the first user generated content was generated at a plurality of first web sites, each of the first web sites associated with a different one of the set of retailers;

determining an importance metric associated with each of the products based on a portion of the user generated content associated with the product;

ordering the set of products based on the importance metric associated with each of the set of products; and

presenting the plurality of products to a user according to their ordering.

2. The method of claim 1, further comprising determining statistical data associated with each of the set of products based on the portion of the user generated content associated with the product.

3. The method of claim 1, wherein the importance metric is a count of the portion of user generated content.

4. The method of claim 3, wherein the first type of user generated content comprises questions and corresponding answers or a review.

5. The method of claim 1, wherein the first type of user generated content is a review comprising a rating and the portion of user generated content associated with each product is a plurality of reviews generated at the plurality of first web sites.

6. The method of claim 5, wherein the importance metric is determined based on a first sum of all ratings in the plurality of reviews for the product which were generated more than 90 days ago, a second sum of all ratings in the plurality of reviews for the product generated in the past 90 days;

a first count of ratings in the plurality of reviews for the product which were generated more than 90 days ago and a second count of all ratings in the plurality of reviews for the product which were generated in the past 90 days.

7. The method of claim 6, wherein the statistical data comprises an average rating for each product based on the plurality of reviews associated with the product.

8. The method of claim 7, wherein the statistical data associated with each product is generated based on the plurality of reviews for the product and includes one or more of a first average rating over time, a second average rating over time for each retailer, a first volume of user generated content over time, a second volume of user generated content over time per retailer, a first number of reviews per rating level, a second number of reviews per retailer, a third average rating per retailer, a set of highest rated products, a set of lowest rated products, a fastest rising product, a fastest dropping product, a set of common words in the plurality of reviews, a set of positive words in reviews or a set of negative words in reviews.

9. A system for distributing generated content, comprising

a set of first computing devices implementing a set of first web sites, each of the first web sites associated with a different one of a set of retailers

a second computing device implementing a content processing system, the second computing device executing computer instructions for:

receiving first user generated content of a first type associated with a plurality of products, where the first user generated content was generated at the plurality of first web sites;

determining an importance metric associated with each of the products based on a portion of the user generated content associated with the product;

ordering the set of products based on the importance metric associated with each of the set of products; and

presenting the plurality of products to a user according to their ordering.

10. The system of claim 9, wherein the computer instructions are operable for determining statistical data associated with each of the set of products based on the portion of the user generated content associated with the product.

11. The system of claim 9, wherein the importance metric is a count of the portion of user generated content.

12. The system of claim 11, wherein the first type of user generated content comprises questions and corresponding answers or a review.

13. The system of claim 9, wherein the first type of user generated content is a review comprising a rating and the portion of user generated content associated with each product is a plurality of reviews generated at the plurality of first web sites.

14. The system of claim 13, wherein the importance metric is determined based on a first sum of all ratings in the plurality of reviews for the product which were generated more than 90 days ago, a second sum of all ratings in the plurality of reviews for the product generated in the past 90 days;

a first count of ratings in the plurality of reviews for the product which were generated more than 90 days ago and a second count of all ratings in the plurality of reviews for the product which were generated in the past 90 days.

15. The system of claim 14, wherein the statistical data comprises an average rating for each product based on the plurality of reviews associated with the product.

16. The system of claim 15, wherein the statistical data associated with each product is generated based on the plurality of reviews for the product and includes one or more of a first average rating over time, a second average rating over time for each retailer, a first volume of user generated content over time, a second volume of user generated content over time per retailer, a first number of reviews per rating level, a second number of reviews per retailer, a third average rating per retailer, a set of highest rated products, a set of lowest rated products, a fastest rising product, a fastest dropping product, a set of common words in the plurality of reviews, a set of positive words in reviews or a set of negative words in reviews.

17. A computer readable media comprising instructions for processing user generated content in a system comprising a set of retailers coupled to a content processing system having a processor, including:

receiving first user generated content of a first type associated with a plurality of products, where the first user generated content was generated at a plurality of first web sites, each of the first web sites associated with a different one of the set of retailers;

determining an importance metric associated with each of the products based on a portion of the user generated content associated with the product;

ordering the set of products based on the importance metric associated with each of the set of products; and

presenting the plurality of products to a user according to their ordering.

18. The computer readable media of claim 17, further comprising instructions for determining statistical data associated with each of the set of products based on the portion of the user generated content associated with the product.

19. The computer readable media of claim 17, wherein the importance metric is a count of the portion of user generated content.

20. The computer readable media of claim 19, wherein the first type of user generated content comprises questions and corresponding answers or a review.

21. The computer readable media of claim 17, wherein the first type of user generated content is a review comprising a rating and the portion of user generated content associated with each product is a plurality of reviews generated at the plurality of first web sites.

22. The computer readable media of claim 21, wherein the importance metric is determined based on a first sum of all ratings in the plurality of reviews for the product which were generated more than 90 days ago, a second sum of all ratings in the plurality of reviews for the product generated in the past 90 days;

a first count of ratings in the plurality of reviews for the product which were generated more than 90 days ago and a second count of all ratings in the plurality of reviews for the product which were generated in the past 90 days.

23. The computer readable media of claim 22, wherein the statistical data comprises an average rating for each product based on the plurality of reviews associated with the product.

24. The computer readable media of claim 23, wherein the statistical data associated with each product is generated based on the plurality of reviews for the product and includes one or more of a first average rating over time, a second average rating over time for each retailer, a first volume of user generated content over time, a second volume of user generated content over time per retailer, a first number of reviews per rating level, a second number of reviews per retailer, a third average rating per retailer, a set of highest rated products, a set of lowest rated products, a fastest rising product, a fastest dropping product, a set of common words in the plurality of reviews, a set of positive words in reviews or a set of negative words in reviews.