Generating Retail Cohorts From Retail Data

• US 20100153174A1
• Filed: 12/12/2008
• Published: 06/17/2010
• Est. Priority Date: 12/12/2008
• Status: Abandoned Application

• Current Assignee: Toshiba Global Commerce Solutions Holdings Corporation (Toshiba Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: Kraemer, James R., Angell, Robert Lee, Friedlander, Robert R.
• Application Number:
  US12/333,319
• Publication Number:
  US 20100153174A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• 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

Abstract

The illustrative embodiments described herein provide a computer implemented method, apparatus, and computer program product for generating retail cohorts. In an illustrative embodiment, retail data derived from a population of retail customers is received and processed to form digital retail data. The digital retail data includes metadata describing a set of retail patterns associated with one or more customers in the population of retail customers. The set of retail patterns form a set of retail attributes for cohort generation. The digital retail data is analyzed using cohort criteria to identify a set of retail cohorts based on the set of retail attributes. The cohort criteria specify at least one retail attribute from the set of retail attributes for each cohort in the set of retail cohorts. Thereafter, a set of retail cohorts are generated. The retail cohorts have members selected from the population of retail customers, and have the at least one retail attribute in common.

Claims

1. A computer implemented method for generating retail cohorts, the computer implemented method comprising:

responsive to receiving retail data derived from a plurality of retail customers, processing the retail data to form digital retail data, wherein the digital retail data comprises metadata describing a set of retail patterns associated with one or more customers in the plurality of retail customers, and wherein the set of retail patterns form a set of retail attributes for cohort generation;

analyzing the digital retail data using cohort criteria to identify a set of retail cohorts based on the set of retail attributes, wherein the cohort criteria specifies at least one retail attribute from the set of retail attributes for each cohort in the set of retail cohorts; and

generating the set of retail cohorts, wherein each member of the set of retail cohorts is selected from the plurality of retail customers, wherein the each member of a cohort in the set of retail cohorts has the at least one retail attribute in common.

2. The computer implemented method of claim 1 further comprising:

identifying each member of the set of retail cohorts based on an analysis of the set of retail attributes.

3. The computer implemented method of claim 1, wherein analyzing the digital retail data comprises at least one of analyzing the digital retail data using historical retail patterns and analyzing the digital retail data with a set of data models.

4. The computer implemented method of claim 1, wherein processing the retail data further comprises:

generating the metadata describing the retail data, wherein the metadata are used for identifying the set of retail patterns.

5. The computer implemented method of claim 1 further comprising:

updating historical retail patterns with the set of retail patterns present in the retail data.

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

generating inferences based on the set of retail cohorts, wherein the inferences specify a selected set of retail attributes for achieving retail objectives.

7. The computer implemented method of claim 1, wherein the set of retail attributes comprises at least one of an action taken by the members of each retail cohort and a retail item associated with the members of the each retail cohort.

8. A computer program product for generating retail cohorts, the computer program product comprising:

a computer recordable-type medium;

first program instructions for processing retail data to form digital retail data in response to receiving the retail data derived from a plurality of retail customers, wherein the digital retail data comprises metadata describing a set of retail patterns associated with one or more customers in the plurality of retail customers, and wherein the set of retail patterns form a set of retail attributes for cohort generation;

second program instructions for analyzing the digital retail data using cohort criteria to identify a set of retail cohorts based on the set of retail attributes, wherein the cohort criteria specifies at least one retail attribute from the set of retail attributes for each cohort in the set of retail cohorts;

third program instructions for generating the set of retail cohorts comprising members selected from the plurality of retail customers, wherein each member of a cohort in the set of retail cohorts has the at least one retail attribute in common; and

wherein the first program instructions, the second program instructions, and the third program instructions are stored on the computer recordable-type medium.

9. The computer program product of claim 8, further comprising:

fourth program instructions for identifying each member of the set of retail cohorts based on the set of retail attributes, and wherein the fourth program instructions are stored on the computer recordable-type medium.

10. The computer program product of claim 8, wherein the second program instructions further comprises instructions for at least one of analyzing the digital retail data using historical retail patterns and analyzing the digital retail data with a set of data models.

11. The computer program product of claim 8, wherein the first program instructions further comprises instructions for generating the metadata describing the retail data, wherein the metadata are used for identifying the set of retail patterns.

12. The computer program product of claim 8 further comprising:

fifth program instructions for updating historical retail patterns with the set of retail patterns present in the retail data, and wherein the fifth program instructions are stored on the computer recordable-type medium.

13. The computer program product of claim 8 further comprising:

sixth program instructions for generating inferences based on the set of retail cohorts, wherein the inferences specify a selected set of retail attributes for achieving retail objectives, and wherein the sixth program instructions are stored on the computer recordable-type medium.

14. The computer program product of claim 8, wherein the set of retail attributes comprises at least one of an action taken by the members of each retail cohort and a retail item associated with the members of the each retail cohort.

15. An apparatus for generating retail cohorts, the apparatus comprising:

a bus system;

a memory connected to the bus system, wherein the memory includes computer usable program code; and

a processing unit connected to the bus system, wherein the processing unit executes the computer usable program code to process retail data to form digital retail data in response to receiving the retail data derived from a plurality of retail customers, wherein the digital retail data comprises metadata describing a set of retail patterns associated with one or more customers in the plurality of retail customers, and wherein the set of retail patterns form a set of retail attributes for cohort generation;

analyze the digital retail data using cohort criteria to identify a set of retail cohorts based on the set of retail attributes, wherein the cohort criteria specifies at least one retail attribute from the set of retail attributes for each cohort in the set of retail cohorts; and

generate the set of retail cohorts comprising members selected from the plurality of retail customers, wherein each member of a cohort in the set of retail cohorts has the at least one retail attribute in common.

16. The computer implemented method of claim 15, wherein the processing unit further executes the computer usable program code to analyze the digital retail data using at least one of historical retail patterns and a set of data models.

17. The computer implemented method of claim 15, wherein the processing unit further executes the computer usable program code to update historical retail patterns with the set of retail patterns present in the retail data.

18. The apparatus of claim 15, wherein the processing unit further executes the computer usable program code to generate inferences based on the set of retail cohorts, wherein the inferences specify the set of retail attributes for achieving retail objectives.

19. A system for generating retail cohorts, the system comprising:

a set of sensors, wherein the set of sensors captures retail data, and wherein the retail data comprises a set of retail patterns;

a retail pattern processing engine, wherein the retail pattern processing engine forms digital retail data from the retail data; and

a cohort generation engine, wherein the cohort generation engine generates a set of retail cohorts from the digital retail data, wherein each member in the set of retail cohorts share at least one retail attribute in common.

20. The system of claim 19, further comprising:

an inference engine, wherein the inference engine generates inferences based on the set of retail cohorts, wherein the inferences specify a selected set of retail attributes for achieving retail objectives.