System and method of identifying trendsetters

• US 7,890,363 B2
• Filed: 06/07/2004
• Issued: 02/15/2011
• Est. Priority Date: 06/05/2003
• Status: Active Grant

• Current Assignee: Xylon LLC (Intellectual Ventures LLC)
• Original Assignee: Hayley Logistics LLC (Intellectual Ventures LLC)
• Inventors: Gross, John N.
• Primary Examiner(s): Jeanty; Romain
• Assistant Examiner(s): Fleischer; Mark A
• Application Number:
  US10/862,930
• Publication Number:
  US 20040249700A1
• Time in Patent Office: 2,444 Days
• Field of Search: 705/10
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0204 Market segmentation

Abstract

A system and method for determining and identifying trendsetters within a member population, such as an online community. The trendsetters can then be used for a number of useful purposes, such as predicting future product/service trends, evaluating advertising techniques, identifying collectible items in an electronic auction, influencing search engines and recommender systems, etc. In a similar fashion, the counterparts to trendsetters, namely, trend rejecters and trend laggards can also be identified and compiled.

Claims

1. A method, comprising:

identifying, on a computing device, adoptions of a first item made by members of an online community;

ranking, on the computing device, by time of adoption the adoptions of the first item by the members of the online community;

repeating the identifying and the ranking for a plurality of other items;

determining, on the computing device, a score by tallying the time of adoption of the first item adopted by the members of the online community with a number and the time of adoption of other items adopted by the members of the online community;

generating, on the computing device, an ordered list of the members of the online community based on the score for the first item and the plurality of other items; and

identifying, on the computing device, a first N members on the ordered list as trendsetter members.

2. The method of claim 1, wherein the score is scaled in accordance with an adoption rank achieved by a member.

3. The method of claim 1, wherein the ordered list of trendsetter members is published online for viewing by other members of the online community.

4. The method of claim 1, wherein the ordered list of trendsetter members identifies members based on rank within the ordered list of trendsetter members entitled to incentives and/or rewards from an operator of a website for the online community.

5. The method of claim 1, wherein the members of the online community can elect to subscribe to activities associated with selected trendsetter members, so that later adoptions by the identified trendsetter members are communicated to such members.

6. The method of claim 1, further comprising:

identifying, on the computing device, members based on rank within the ordered list of trendsetter members who are trend predictors.

7. The method of claim 6, further comprising:

measuring, on the computing device, a prevalence rate among the trend predictors for a newly introduced item.

8. The method of claim 7, further comprising:

measuring, on the computing device, a change in prevalence rate among the trendsetters for the newly introduced item.

9. The method of claim 7, further comprising:

generating, on the computing device, a popularity prediction rating for the newly introduced item.

10. The method of claim 1, further comprising:

determining items that are prevalent among the trendsetter members; and

automatically generating, on the computing device, a recommendation for at least one of the prevalent items to a member of the online community.

11. The method of claim 1, further comprising:

providing, on the computing device, a set of profiles for the trendsetter members to at least one of an e-commerce vendor and an advertiser.

12. The method of claim 1, further comprising:

monitoring, on the computing device, online viewing, query, and related interaction behavior exhibited by the trendsetter members.

13. The method of claim 1, further comprising:

providing, on the computing device, the ordered list of trendsetter members to a third party website, the third party website using the ordered list of trendsetter members to predict demand by a second online community.

14. The method of claim 13, further comprising:

generating, on the computing device, the ordered list of trendsetter members based on an analysis combining the online community with the second online community.

15. The method of claim 1, wherein the first item is a product, a service, or content.

16. The method of claim 1, wherein the first item is a security.

17. The method of claim 1, wherein members who are at the extremes of the adoption rankings cannot be trendsetters.

18. The method of claim 1, wherein the ordered list of trendsetter members is generated for a category of items.

19. The method of claim 1, wherein the ordered list of trendsetter members is generated for all items available to the online community.

20. A method, comprising:

identifying, on a computing device, adoptions of a first item made by members of an online community;

ranking, on the computing device, by time of adoption the adoptions of the first item by the members of the online community;

repeating the identifying and the ranking for a plurality of other items;

determining, on the computing device, a score by tallying the time of adoption of the first item adopted by the members of the online community with a number and the time of adoption of other items adopted by the members of the online community; and

generating, on the computing device, an ordered list of trend predictor members based on the results of the determining, the trend predictor members being those members who are among a first N members of the ordered list based on the score of a plurality of items including the first item and at least one of the plurality of other items.

21. The method of claim 20, wherein the trend predictor members are used to generate a prediction for adoption of a newly introduced item.

22. The method of claim 20, wherein the trend predictor members are derived from a set of first K members who in aggregate first adopted all of a set of M items.

23. The method of claim 21, wherein the prediction is based on measuring a prevalence rate for the newly introduced item at a first time after introduction of such item.

24. The method of claim 23, wherein the prediction is further based on studying a change in the prevalence rate at a second time after the first time.

25. The method of claim 20, further comprising:

generating, on the computing device, online advertising tailored to the trend predictor members.

26. The method of claim 20, further comprising:

generating, on the computing device, proxy accounts associated with the trend predictor members, and observing a behavior of websites towards the proxy accounts.

27. A method, comprising:

identifying, on a computing device, a behavior and/or action which is relatively prevalent within a subscriber population;

identifying, on the computing device, early adopters of the behavior and/or action within the subscriber population by monitoring their activities during an electronic data collection session and ranking the activities by time; and

repeating the identifying a behavior or action and the identifying early adopters to determine a score by tallying the time of adoption of the first behavior or action adopted by the subscriber population with a number and the time of adoption of other behaviors or actions adopted by the subscriber population to compile an ordered list of overall early adopters within the subscriber population for a plurality of behaviors or actions based at least in part on the score of each early adopter.

28. The method of claim 27, wherein the early adopters are subscribers to a content programming service.

29. The method of claim 27, wherein the early adopters are subscribers of a communications service provider.

30. The method of claim 27, wherein the early adopters are purchasers of a software product.

31. The method of claim 27, wherein the early adopters are purchasers of a media product, such as a book, a movie, or a song.

32. The method of claim 27, wherein the early adopters are bidders in an electronic auction.

33. The method of claim 27, wherein the early adopters are purchasers of a security traded in a public market.

34. The method of claim 27, wherein the early adopters are consumers of content presented at an online content service provider.

35. The method of claim 27, wherein the early adopters are online participants in an electronic auction.

36. A computer system, comprising:

a software module which is configured for;

identifying, on the computer system, adoptions of a first item made by members of an online community;

ranking, on the computer system, by time of adoption the adoptions of the first item by the members of the online community;

repeating the identifying and the ranking for a plurality of other items;

determining, on the computer system, a score by tallying the time of adoption of the first item adopted by the members of the online community with a number and the time of adoption of other items adopted by the members of the online community;

generating, on the computer system, an ordered list of the members of the online community based on the results of the score for the first item and the plurality of other items; and

identifying, on the computer system, a first N members on the ordered list as trendsetter members.