Applications of cluster analysis for cellular operators

• US 8,326,682 B2
• Filed: 12/31/2007
• Issued: 12/04/2012
• 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, Taglienti, Claudio, Irizarry, Michael, Saxena, Narothum
• Primary Examiner(s): Dixon, Thomas
• Assistant Examiner(s): Fields, Benjamin S
• Application Number:
  US11/968,008
• Publication Number:
  US 20090171717A1
• Time in Patent Office: 1,800 Days
• Field of Search: 705/7, 705/7.11
• US Class Current: 705/7.42
• 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 implemented by a computing device executing computer readable instructions causing the computing device to perform a plurality of steps comprising:

defining, for a subscriber, a call pattern as a cluster profile, the call pattern comprising a plurality of call origin locations of the subscriber;

creating a plurality of travel pattern archetypes and associating a price plan archetype, respectively, with each of the travel pattern archetypes;

associating, based on the cluster profile, the subscriber with a travel pattern archetype from the plurality of travel plan archetypes, the travel pattern archetype having an associated price plan archetype;

comparing, for the subscriber, the current price plan with the associated price plan archetype; and

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

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

3. The method according to claim 1, wherein the comparing the current price plan with the associated price plan archetype and constructing the micro-marketing strategy for the subscriber are executed in parallel.

4. The method according to claim 1, wherein the defining a call pattern as a cluster profile comprises:

selecting a sample of subscribers from a total population;

for each subscriber, from the sample of subscribers, plotting a location of a call origin for each subscriber call;

for each subscriber, from the sample of subscribers, employing cluster analysis to identify a number of clusters for the subscriber, wherein clusters are denoted by respective centroids and radii;

using statistical grouping, on the number of clusters for each subscriber, to identify one or more call pattern archetypes; and

establishing the cluster profile by associating the call pattern, for the subscriber, with one of the call pattern archetypes.

5. The method according to claim 4, wherein plotting a location comprises plotting a latitude and longitude of an originating tower.

6. The method according to claim 4, wherein the 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.

7. The method according to claim 4, wherein the plotting a location of a call origin for each call comprises determining whether the call origin is within a coverage space of a predetermined operator.

8. The method according to claim 4, wherein the employing cluster analysis to identify a number of clusters and respective centroids and radii is executed via a blind random sample of subscribers.

9. The method according to claim 4, wherein the employing cluster analysis to identify a number of clusters and respective centroids and radii is executed via a structured sample.

10. The method according to claim 4, further comprising:

defining a specific price plan for each travel pattern archetype;

associating a stereotypical role with each call pattern archetype; and

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

11. 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, for a subscriber, a call pattern as a cluster profile, the call pattern comprising a plurality of call origin locations of the subscriber;

creating a plurality of travel pattern archetypes and associating a price plan archetype, respectively, with each of the travel pattern archetypes;

associating, based on the cluster profile, the subscriber with a travel pattern archetype from the plurality of travel plan archetypes, the travel pattern archetype having an associated price plan archetype;

comparing, for the subscriber, the current price plan with the associated price plan archetype; and

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

12. The computer-readable medium according to claim 11, wherein the instructions for comparing the current price plan with the associated price plan archetype comprises instructions for executing a comparison based on profitability and net subscriber cost.

13. The computer-readable medium according to claim 11, wherein the instructions for comparing the current price plan with the associated price plan archetype and constructing the micro-marketing strategy for the subscriber are executed substantially in parallel.

14. The computer-readable medium according to claim 11, wherein the instructions for the defining a call pattern as a cluster profile comprises instructions for:

selecting a sample of subscribers from a total population;

plotting, for each subscriber from the sample of subscribers, a location of a call origin for each subscriber call;

employing, for each subscriber from the sample of subscribers, cluster analysis to identify a number of clusters for the subscriber, wherein clusters are denoted by respective centroids and radii for each subscriber;

using statistical grouping, on the number of clusters for each subscriber, to identify one or more call pattern archetypes; and

establishing the cluster profile by associating the call pattern, for the subscriber, with one of the call pattern archetypes.

15. The computer-readable medium according to claim 14, wherein the instructions for plotting a location comprise instructions for plotting a latitude and longitude of an originating tower.

16. The computer-readable medium according to claim 14, wherein the instructions for the 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.

17. The computer-readable medium according to claim 14, wherein the instructions for the plotting a location of a call origin for each call comprise instructions for determining whether the call origin is within a coverage space of a predetermined operator.

18. The computer-readable medium according to claim 14, wherein the instructions for the employing cluster analysis to identify a number of clusters and respective centroids and radii are executed via a blind random sample of subscribers.

19. The computer-readable medium according to claim 14, further comprising instructions for:

defining a specific price plan for each travel pattern archetype;

associating a stereotypical role with each call pattern archetype; and

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