Method and system for purchase-based segmentation

• US 20050177449A1
• Filed: 09/22/2004
• Published: 08/11/2005
• Est. Priority Date: 09/22/2003
• Status: Active Grant

• Current Assignee: Citicorp Credit Services Incorporated (Citigroup Incorporated)
• Original Assignee: Citicorp Credit Services Incorporated (Citigroup Incorporated)
• Inventors: Menai, Noor A., Newman, Alan B., Temares, Mark E.
• Granted Patent: US 7,328,169 B2
• Time in Patent Office: Days
• US Class Current: 705/26
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0224 based on user history
• CPC Class Codes: G06Q 30/0234 Rebates after completed purchase
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching

Abstract

A method and system for purchased-based segmentation of potential customers employs the use of actual, observed purchases instead of presumptions and correlations to improve the accuracy of segmentation and involves collecting empirical data for a client on actual purchasing behavior of a group of customers and applying statistical modeling techniques to the empirical purchasing behavior data to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics. Thereafter, the segments or clusters are further differentiated from one another according to other factors having a tendency to directly affect actual purchasing behavior of the customers within the segments or clusters, and potential customers are then identified according to a correlation with the segments or clusters for customized marketing.

Claims

1. A method for purchased-based segmentation of customers, comprising:

collecting empirical data by a service provider for a client on actual purchasing behavior of a group of customers;

applying statistical modeling techniques to the empirical purchasing behavior data to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics;

differentiating the segments or clusters according to other factors having a tendency to directly affect actual purchasing behavior of customers within the segments or clusters;

identifying potential customers for customized marketing according to a correlation with the segments or clusters.

2. The method of claim 1, wherein collecting empirical data further comprises collecting the empirical data on actual purchasing behavior of the customers as a byproduct of use of payment devices provided to the customers.

3. The method of claim 2, wherein collecting the empirical data further comprises collecting the empirical data as a byproduct of use of payment devices provided to the customers selected from a group consisting at least in part of credit cards, debit cards, stored value cards, and radio frequency identification devices.

4. The method of claim 2, wherein collecting the empirical data further comprises collecting the empirical data directly as a byproduct of use of payment devices provided to the customers by the client.

5. The method of claim 2, wherein collecting the empirical data further comprises collecting the empirical data indirectly as a byproduct of use of payment devices provided to the customers by a third party.

6. The method of claim 1, wherein collecting empirical data further comprises collecting the empirical data on actual purchasing behavior of the customers as a byproduct of use of benefit credentials provided to the customers.

7. The method of claim 6, wherein collecting the empirical data further comprises collecting the empirical data as a byproduct of use of benefit credentials selected from a group consisting at least in part of warranty cards, rebate forms, barcode scans, and proof of purchase data.

8. The method of claim 6, wherein collecting the empirical data further comprises collecting the empirical data directly as a byproduct of use of benefit credentials provided to the customers by the client.

9. The method of claim 6, wherein collecting the empirical data further comprises collecting the empirical data indirectly as a byproduct of use of benefit credentials provided to the customers by a third party.

10. The method of claim 1, wherein applying the statistical modeling techniques to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics further comprises applying the statistical modeling techniques to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics in terms of likelihood of future purchases.

11. The method of claim 10, wherein applying the statistical modeling techniques to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics further comprises applying the statistical modeling techniques to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics in terms of likelihood of future purchases from the client.

12. The method of claim 10, wherein applying the statistical modeling techniques to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics further comprises applying the statistical modeling techniques to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics in terms of likelihood of future purchases from a third party.

13. The method of claim 1, wherein differentiating the segments or clusters on the basis of other factors further comprises differentiating the segments or clusters on the basis of geodemographic and psychographic/lifestyle factors having a tendency to directly affect actual purchasing behavior of the customers within the segments or clusters.

14. The method of claim 1, wherein identifying potential customers for customized marketing further comprises identifying customers within the segments or clusters who are customers of the client for customized marketing by the client according to a correlation with the segments or clusters.

15. The method of claim 1, wherein identifying potential customers for customized marketing further comprises identifying customers within the segments or clusters who are customers of a third party for customized marketing by the client according to a correlation with the segments or clusters.

16. The method of claim 1, wherein identifying potential customers for customized marketing further comprises identifying potential customers for customized marketing according to a correlation with the segments or clusters via indexing.

17. A system for purchased-based segmentation of customers, comprising:

means for collecting empirical data by a service provider for a client on actual purchasing behavior of a group of customers;

means for applying statistical modeling techniques to the empirical purchasing behavior data to identify segments or clusters of the customers that exhibit similar purchasing propensity characteristics;

means for differentiating the segments or clusters according to other factors having a tendency to directly affect actual purchasing behavior of the customers within the clusters; and

means for identifying potential customers for customized marketing according to a correlation with the segments or clusters.