APPLICATIONS OF CLUSTER ANALYSIS FOR CELLULAR OPERATORS

• US 20090171717A1
• Filed: 12/31/2007
• Published: 07/02/2009
• Est. Priority Date: 12/31/2007
• Status: Active Grant

• Current Assignee: United States Cellular Corporation (Telephone & Data Systems, Inc.)
• Original Assignee: United States Cellular Corporation (Telephone & Data Systems, Inc.)
• Inventors: Redford, John, Saxena, Narothum, Irizarry, Michael, Taglienti, Claudio
• Granted Patent: US 8,326,682 B2
• Time in Patent Office: Days
• US Class Current: 705/7
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation

Abstract

Subscriber travel behavior is defined using cellular call location data. The defined travel behavior is used to segment the customer population. In a further aspect of the disclosed principles, a method to consolidate numerous of price plans is disclosed wherein price plans are grouped using cluster analysis. In the context of this disclosure, the term “cluster analysis” encompasses a number of different algorithms and methods for grouping objects of similar kind into respective categories to thus organize observed data into meaningful structures. In this context, cluster analysis is a data analysis process for sorting different objects into groups in a way that the degree of association between two objects is maximal if they belong to the same group and minimal otherwise.

Claims

1. A method for creating a customized marketing plan for a subscriber in a cellular network having a current price plan, the method comprising:

defining a subscriber'"'"'s call pattern as a cluster profile;

creating travel pattern archetypes and associated respective price plan archetypes;

associating the subscriber with a travel pattern archetype and its associated price plan archetype;

comparing the subscriber'"'"'s current price plan with the archetypal price plan; and

constructing a micro-marketing strategy for the subscriber based on the comparison.

2. The method according to claim 1, wherein comparing the subscriber'"'"'s current price plan with the archetypal price plan comprises executing a comparison based on profitability and net subscriber cost.

3. The method according to claim 1, wherein the method is executed automatically via the computer execution of computer-readable instructions and data.

4. The method according to claim 1, wherein the steps of comparing the subscriber'"'"'s current price plan with the archetypal price plan and constructing a micro-marketing strategy for the subscriber are executed in parallel.

5. The method according to claim 1, wherein defining a subscriber'"'"'s call pattern as a cluster profile comprises:

selecting a sample of subscribers from the total population;

for each subscriber plotting a location of a call origin for each call;

for each subscriber employing cluster analysis to identify a number of clusters and their respective centroids and radii;

using statistical grouping on the cluster profiles to identify one or more call pattern archetypes; and

associating each subscriber with their cluster profile'"'"'s archetype cluster profile.

6. The method according to claim 5, wherein plotting a location comprises plotting a latitude and longitude of an originating tower.

7. The method according to claim 5, wherein plotting a location of a call origin for each call comprises plotting a location of a call origin for each call in a specified time interval.

8. The method according to claim 5, wherein plotting a location of a call origin for each call further comprises determining whether the origin is within the coverage of a predetermined operator.

9. The method according to claim 5, wherein employing cluster analysis to identify a number of clusters and their respective centroids and radii is executed via a blind random sample of subscribers.

10. The method according to claim 5, wherein employing cluster analysis to identify a number of clusters and their respective centroids and radii is executed via a structured sample.

11. The method according to claim 5, further comprising:

defining specific price plans for each archetype;

associating stereotypical roles with the call pattern archetypes; and

associating each subscriber with a price plan by calculating their call pattern based on their call history.

12. A computer-readable medium having thereon computer-executable instructions for creating a customized marketing plan for a subscriber in a cellular network having a current price plan, the computer-executable instructions comprising:

instructions for defining a subscriber'"'"'s call pattern as a cluster profile;

instructions for creating travel pattern archetypes and associated respective price plan archetypes;

associating the subscriber with a travel pattern archetype and its associated price plan archetype;

instructions for comparing the subscribers current price plan with the archetypal price plan; and

instructions for constructing a micro-marketing strategy for the subscriber based on the comparison.

13. The computer-readable medium according to claim 12, wherein the instructions for comparing the subscriber'"'"'s current price plan with the archetypal price plan comprises instructions for executing a comparison based on profitability and net subscriber cost.

14. The computer-readable medium according to claim 12, wherein the instructions for comparing the subscribers current price plan with the archetypal price plan and constructing a micro-marketing strategy for the subscriber are executed substantially in parallel.

15. The computer-readable medium according to claim 12, wherein the instructions for defining a subscriber'"'"'s call pattern as a cluster profile comprises:

instructions for selecting a sample of subscribers from the total population;

instructions for plotting a location of a call origin for each call for each subscriber;

instructions for employing cluster analysis to identify a number of clusters and their respective centroids and radii for each subscriber;

instructions for using statistical grouping on the cluster profiles to identify one or more call pattern archetypes; and

instructions for associating each subscriber with their cluster profile'"'"'s archetype cluster profile.

16. The computer-readable medium according to claim 15, wherein the instructions for plotting a location comprise instructions for plotting a latitude and longitude of an originating tower.

17. The computer-readable medium according to claim 15, wherein the instructions for plotting a location of a call origin for each call comprise instructions for plotting a location of a call origin for each call in a specified time interval.

18. The computer-readable medium according to claim 15, wherein the instructions for plotting a location of a call origin for each call further comprise instructions for determining whether the origin is within the coverage of a predetermined operator.

19. The computer-readable medium according to claim 15, wherein the instructions for employing cluster analysis to identify a number of clusters and their respective centroids and radii are executed via a blind random sample of subscribers.

20. The computer-readable medium according to claim 15, further comprising:

instructions for defining specific price plans for each archetype;

instructions for associating stereotypical roles with the call pattern archetypes; and

instructions for associating each subscriber with a price plan by calculating their call pattern based on their call history.