PREDICTION OF CONSUMER BEHAVIOR DATA SETS USING PANEL DATA

• US 20130151311A1
• Filed: 11/15/2012
• Published: 06/13/2013
• Est. Priority Date: 11/15/2011
• Status: Abandoned Application

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Smallwood, Bradley Hopkins, Bruich, Sean Michael
• Application Number:
  US13/677,889
• Publication Number:
  US 20130151311A1
• 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 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Embodiments of the invention combine information from different data sets, such as social networks, vendor systems, and/or panels, each data set comprising statistics about past consumer behavior (e.g., product purchases). The result of the combination is a model that, when applied to statistics about purchases of a particular product, produces predicted consumer behavior statistics about the particular product that are more accurate than the data of any given one of the different data sets when taken in isolation.

Claims

1. A computer-implemented method comprising:

accessing panel data obtained from a surveying panel and comprising statistics corresponding to households of members;

accessing social networking data obtained from a social networking system and comprising statistics corresponding to individual users of the social networking system;

accessing purchasing data obtained from a vendor system and comprising transactional data related to products for sale; and

computing a prediction model using the panel data, the social networking data, and the purchasing data;

2. The computer-implemented method of claim 1, wherein the purchasing data comprises:

statistics on purchases of products.

3. The computer-implemented method of claim 1, wherein the panel data comprises:

statistics on purchases of products by the households; and

demographic data about ones of the households.

4. The computer-implemented method of claim 1, wherein the social networking data comprises, for each of a plurality of the individual users of the social networking system:

statistics on presentations of products to the user; and

user-specific information about the user specified by the user.

5. The computer-implemented method of claim 4, further comprising:

identifying, for the user, a portion of the user-specific information that other portions of the user-specific information indicate is inaccurate;

determining a probable value for the portion based on the other portions of the user-specific information; and

modifying the portion to the probable value, before deriving the hybrid data.

6. The computer-implemented method of claim 1, further comprising:

accessing first statistics for a product from the surveying panel, second statistics for the product from the social networking system, and third statistics for the product from the vendor system; and

computing predicted consumer behavior for the product at least in part by providing the first statistics, the second statistics, and the third statistics as input to the prediction model.

7. The computer-implemented method of claim 6, wherein the predicted consumer behavior comprise, for each of a plurality of demographic attributes, an estimated total sales value and an estimated frequency value for the product when presented to viewers having the demographic attribute.

8. The computer-implemented method of claim 6, wherein the predicted consumer behavior for the product comprises:

predicted statistics on purchases of the products by users of the social networking system; and

user-specific information about the users specified by the users.

9. A computer-implemented method comprising:

receiving a request for one or more predicted consumer actions for a product of a plurality of products for sale;

retrieving a prediction model using panel data from a surveying panel, social networking data from a social networking system, and purchasing data from a vendor to generate a plurality of prediction scores for a plurality of consumer actions for the product;

determining first statistics for the product from the surveying panel, second statistics for the product from the social networking system, and third statistics for the product from the vendor system;

determining a plurality of prediction scores for the plurality of consumer actions for the product using the prediction model based at least in part on the first statistics, the second statistics, and the third statistics;

selecting one or more consumer actions of the plurality of consumer actions as the one or more predicted consumer actions for the product based on the determined plurality of prediction scores; and

providing the selected one or more predicted consumer actions for the product responsive to the request.

10. The computer-implemented method of claim 9, wherein the panel data comprises a plurality of statistics corresponding to a plurality of households, the plurality of statistics comprising one or more purchase information items about the plurality of products, demographic information about the plurality of households, and identifying information of members of the plurality of households.

11. The computer-implemented method of claim 9, wherein the social networking data comprises a plurality of statistics corresponding to a plurality of users of the social networking system, the plurality of statistics comprising one or more advertisement presentation information items about the plurality of products, user-specified demographic information about the plurality of users of the social networking system, and identifying information of the plurality of users of the social networking system.

12. The computer-implemented method of claim 9, wherein the purchasing data comprises transactional data related to at least one of the plurality of products for sale.

13. The computer-implemented method of claim 9, wherein a predicted consumer action comprises an aggregated value of sales of the product.

14. The computer-implemented method of claim 9, wherein a predicted consumer action comprises an average frequency of purchase of the product for users of the social networking system.

15. The computer-implemented method of claim 9, wherein a predicted consumer action comprises an average frequency of purchasing the product through a web site for users of the social networking system.

16. The computer-implemented method of claim 9, wherein a predicted consumer action comprises an average frequency of purchasing the product at a vendor for users of the social networking system.

17. A computer-implemented method comprising:

maintaining panel data from a surveying panel, where the panel data comprises a first plurality of information items corresponding to a plurality of households;

maintaining social networking data from a social networking system, where the social networking data comprises a second plurality of information items corresponding to a plurality of users of the social networking system;

maintaining purchasing data from a vendor system, where the purchasing data comprises transactional data related to a plurality of products for sale;

determining a prediction model using the panel data, the social networking data, and the purchasing data;

receiving a request for a prediction of consumer behavior for a product of the plurality of products for sale;

retrieving first statistics for the product from the surveying panel, second statistics for the product from the social networking system, and third statistics for the product from the vendor system;

determining the prediction of consumer behavior for the product at least in part by providing the first statistics, the second statistics, and the third statistics as input to the prediction model; and

providing the prediction of consumer behavior for the product responsive to the request.

18. The computer-implemented method of claim 17, wherein a first plurality of information items comprises purchase information by one or more members of the plurality of households about at least one of the plurality of products for sale, wherein a second plurality of information items comprises a plurality of interests of the plurality of users of the social networking system, the method further comprising:

for each member of each household of the plurality of households,

determining one or more confidence scores for one or more users of the social networking system that the member matches the one or more users, and

matching the member to one of the one or more users based on the determined one or more confidence scores;

determining a plurality of interests of the matched users based on the second plurality of information items; and

further determining the prediction of consumer behavior for the product at least in part by providing the determined plurality of interests of the matched users as input to the prediction model.

19. The computer-implemented method of claim 18, wherein the prediction of consumer behavior for a product comprises predicted consumer purchase information filtered by a selected user interest.

20. The computer-implemented method of claim 18, wherein the prediction of consumer behavior for a product comprises consumer purchase information filtered by a selected user demographic.

21. The computer-implemented method of claim 18, wherein the prediction of consumer behavior for a product comprises consumer purchase information filtered by a selected user education level.

22. The computer-implemented method of claim 18, wherein the prediction of consumer behavior for a product comprises consumer purchase information filtered by one or more of a selected interest, a selected user demographic, and a selected user education level.

23. The computer-implemented method of claim 17, wherein the prediction of consumer behavior for a product comprises predicted consumer behavior filtered by user demographics.

24. The computer-implemented method of claim 17, wherein the prediction of consumer behavior for a product comprises predicted consumer behavior filtered by geographic location.

25. The computer-implemented method of claim 17, wherein the prediction of consumer behavior for a product comprises predicted consumer behavior filtered by one or more user attributes in the social networking system.