DATA INTEGRATION AND ANALYSIS

• US 20120150587A1
• Filed: 11/18/2011
• Published: 06/14/2012
• Est. Priority Date: 11/19/2010
• Status: Active Grant

• Current Assignee: Information Resources Incorporated
• Original Assignee: Information Resources Incorporated
• Inventors: Kruger, Michael W., Wadhwani, Romesh
• Granted Patent: US 8,589,208 B2
• Time in Patent Office: Days
• US Class Current: 705/7.34
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration

Abstract

Uncorrelated data from a variety of sources, such as consumer panels or retailer points of sale, are combined with maximal coverage of a universal data set for a population in a manner that permits useful inferences about behaviorial propensities for the population at an individual or household level.

Claims

1. A computer program product embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:

identifying a universal data set enumerating a population of consumers within a geographic area;

identifying a plurality of ancillary data sources that each provide ancillary data describing commercial behavior of a corresponding subset of consumers at the respective ancillary data source;

partitioning the geographic area into a plurality of sectors;

enumerating the plurality of sectors;

identifying a sample of the plurality of sectors;

extracting data from each of the ancillary data sources in an order consistent with an enumerated order of the cells, until meeting data thresholds corresponding to each of the respective ancillary data sources; and

combining the extracted data with panel data from a panel data source.

2. The computer program product of claim 1, wherein the ancillary data includes point of sale data.

3. The computer program product of claim 1, wherein the ancillary data includes shipping data.

4. The computer program product of claim 1, wherein the ancillary data includes media delivery data.

5. The computer program product of claim 1, wherein the ancillary data includes credit card data.

6. The computer program product of claim 1, wherein the ancillary data includes clickstream data.

7. The computer program product of claim 1, wherein enumerating the plurality of sectors includes identifying coordinates corresponding to each sector and interleaving digits of the coordinates, thereby producing an integer.

8. A computer program product embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:

identifying a data set including;

characteristics of a population of consumers within a geographic area partitioned into sectors;

ancillary data from at least two sources describing, on a sector-by-sector basis, consumer behaviors within the geographic area, wherein one of the sources is a panel data source;

identifying a first propensity of consumers in a first sector to engage in a specified behavior with a first data source, by computing a ratio of a number consumers in the first sector who engage in the specified behavior to a total number of consumers in the first sector;

identifying a modeled second propensity of consumers in the first sector to engage in the specified behavior with a second data source, wherein the data set does not include data sufficient to compute an actual second propensity corresponding to the modeled second propensity; and

using the first propensity and the modeled second propensity, identifying a third and fourth modeled propensities of consumers in a second sector to engage in the specified behavior with, respectively, the first and second data sources, wherein the data set does not include data sufficient to compute an actual third and forth propensities corresponding to the third and fourth modeled propensities.

9. The computer program product of claim 8, wherein identifying the modeled second propensity includes setting the second propensity equal to the first propensity.

10. The computer program product of claim 8, wherein identifying the modeled second propensity includes employing a shrinkage estimator.

11. The computer program product of claim 8, wherein identifying the modeled second propensity includes using an elasticity model describing propensity variation across data sources.

12. The computer program product of claim 8, wherein identifying the modeled second propensity includes using regression, imputation, projection, or similarity-based techniques.

13. The computer program product of claim 8, wherein the specified behavior includes buying a particular brand of goods or services.

14. The computer program product of claim 8, wherein the specified behavior includes consume media from a particular media outlet.

15. The computer program product of claim 8, wherein the specified behavior includes a purchasing a specified collection of goods or services.

16. The computer program product of claim 8, wherein the specified behavior includes purchasing at least a specified dollar amount worth of goods or services.

17. The computer program product of claim 8, wherein the specified behavior includes shopping at a particular store.

18. The computer program product of claim 8, wherein the specified behavior includes buying goods or services at a discount.

19. The computer program product of claim 8, wherein identifying the third and fourth modeled propensities includes regression, imputation, projection, or similarity-based techniques.

20. The computer program product of claim 19, wherein identifying the third and fourth modeled propensities includes verifying that a score for the third and fourth modeled propensities totals to a known value.

21-40. -40. (canceled)