System & method for predicting demand for items

• US 20040260600A1
• Filed: 06/07/2004
• Published: 12/23/2004
• 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.
• Granted Patent: US 7,885,849 B2
• Time in Patent Office: Days
• US Class Current: 705/7.31
• 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 30/0202 Market predictions or forecasting for commercial activities

Abstract

A system and method for determining and identifying demand for items based on observing behavior of trendsetters within a member population, such as an online community. The trendsetters are determined by studying historical adoption behavior of a group within the member population.

Claims

1. A method of identifying demand by an online community for a particular item, the method comprising the steps of:

(a) identifying early adopter members of the online community, which early adopter members are characterized by a demand behavior for items which leads and is imitated by other members of the online community;

(b) measuring an acceptance value for the particular item by such early adopter members of the online community.

2. The method of claim 1, further including a step:

generating a demand score identifying a predicted overall remaining demand for the particular item.

3. The method of claim 2, wherein said demand score reflects a predicted overall remaining demand for consumers of the particular item outside of the online community.

4. A method of identifying demand by an online community for a particular item, the method comprising the steps of:

(a) identifying late adopter members of the online community, which late adopter members are characterized by a demand behavior for the particular item which lags other members of the online community;

(b) measuring an acceptance value for the particular item by such late adopter members of the online community;

(c) generating a demand score identifying a predicted overall remaining demand for the particular item.

5. The method of claim 4, wherein said demand score reflects a predicted overall remaining demand for consumers of the particular item outside of the online community.

6. A method of identifying predicted demand for an item, the method comprising the steps of:

(a) identifying a group of trend predictor members within an electronic online community;

(b) identifying one or more items rejected by said group of trend predictor members, by monitoring their activities during electronic data collection sessions;

(c) compiling a list of said one more rejected items.

7. The method of claim 6, further including a step (d):

identifying trend rejecter members within said electronic community, said trend rejecters being characterized as members who have adopted a substantial number of said one or more rejected items.

8. The method of claim 7, further including a step (d):

calculating an item rejection prevalence rate among said trend predictor members for each of said one or more items.

9. The method of claim 8, further including a step (e):

disseminating advertising to said trend predictor members for at least one selected rejected item; and

a step (f);

measuring any change in an item rejection prevalence rate for said at least one selected rejected item.

10. A method of identifying potential demand for a new product and/or new service within a market, the method comprising the steps of:

(a) identifying one or more products and/or services which are characterized as having achieved substantial economic success within the market;

(b) identifying early adopters of said one or more products and/or services within an electronic community;

(c) monitoring the activities of said early adopters during electronic data collection sessions, to determine a prevalence rating of their collective impressions of the new product and/or new service.

11. The method of claim 10, wherein step (c) is performed before the new product and/or new service is introduced into the market.

12. The method of claim 10, further including a step (d):

presenting advertising materials to said early adopters, and measuring a change in said prevalence rating.

13. A method of identifying trend predictor items within a set of items available to an online community, the method comprising the steps of:

(a) identifying a first item having a relatively high adoption rate;

(b) calculating a correlation between said first item and one or more second items which have a relatively low adoption rate;

(c) identifying at least one second item which is highly correlated to said first item, and not highly correlated to other of said one or more second items;

(d) repeating steps (b) and (c) to identify a first set of first items which have relatively high adoption rates, and a second set of second items which are highly correlated to said first set of first items.

14. The method of claim 13, further including a step:

(e);

measuring a correlation of said second set of items to a newly introduced item to generate a prediction of a demand for said newly introduced item.

15. A system for identifying demand by an online community for a particular item, the system comprising:

(a) a first software module executing on first computing device, said first software module being configured for;

i) identifying early adopter members of the online community;

wherein said early adopter members are characterized by a demand behavior for items which leads and is imitated by other members of the online community;

ii) storing profiles for said early adopter members in a trendsetter database;

iii) measuring an acceptance value for the particular item by such early adopter members of the online community.

16. The system of claim 15, wherein said first computing device is an Internet based sever supporting a website maintained by an e-commerce operator.

17. The system of claim 15, wherein the particular item is a product.

18. The system of claim 15, wherein the early adopter members are represented by web pages.

19. The system of claim 15, wherein the early adopter members are extracted from purchasing records of individuals having a common geographic demographic.

20. The system of claim 15, wherein the members of the online community are ranked by adoption date for items to identify said early adopter members.