SYSTEMS AND METHODS TO UTILIZE SUBSCRIBER HISTORY FOR PREDICTIVE ANALYTICS AND TARGETING MARKETING

• US 20140379424A1
• Filed: 06/24/2014
• Published: 12/25/2014
• Est. Priority Date: 06/24/2013
• Status: Abandoned Application

• Current Assignee: Psychability Inc.
• Original Assignee: Psychability Inc.
• Inventors: Shroff, Pankaj
• Application Number:
  US14/313,229
• Publication Number:
  US 20140379424A1
• Time in Patent Office: Days
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0255 based on user history

Abstract

Embodiments of the invention relate to computer-implemented methods and systems for managing and analyzing subscriber history data present within a service provider infrastructure. The subscriber history data is free of personally identifiable information and is aggregated according to an anonymous attribute. A predictive model is used to rank a plurality of individuals or households according to one or more household attributes, such as media habits and/or media exposure. Advertisers are provided with access to the ranked data, such that the advertisers can improve marketing metrics for advertisements delivered to the households. Service providers may receive monetary compensation for providing access to the ranked data.

Claims

1. A computer-implemented method for managing and analyzing subscriber history data present within a service provider infrastructure, the method comprising:

removing elements from the subscriber history data that allow the data to be attributed to a household;

aggregating the subscriber history data by an anonymous attribute;

deriving a predictive model for a plurality of households;

ranking each household in the plurality of households relative to other households according to at least one household attribute;

in real-time, providing advertisers with access to the ranked data such that the advertisers can improve marketing metrics for advertisements delivered to the households; and

receiving monetary compensation for providing access to the ranked data.

2. The method of claim 1, wherein the service provider comprises at least one of a multiple service operator, a cable service provider, a telephone company, a mobile network operator, or a wireless service provider.

3. The method of claim 1, wherein the household comprises an individual subscriber.

4. The method of claim 1, wherein removing elements from the subscriber history data comprises removing personally identifiable information from the subscriber history data.

5. The method of claim 1, wherein the predictive model is configured to predict media habit and media exposure for at least one household.

6. The method of claim 1, wherein the at least one household attribute comprises at least one of a media habit and a media exposure.

7. The method of claim 1, wherein ranking each household relative to other households comprises assigning a formula to predict a household'"'"'s media habit and exposure.

8. The method of claim 1, wherein ranking each household relative to other households comprises assigning a household to at least one of a demographic segment and a group of lookalike households having similar media viewing habits.

9. A system comprising:

a computer readable medium having instructions stored thereon; and

a data processing apparatus configured to execute the instructions to perform operations comprising;

removing elements from the subscriber history data that allow the data to be attributed to a household;

aggregating the subscriber history data by an anonymous attribute;

deriving a predictive model for a plurality of households;

ranking each household in the plurality of households relative to other households according to at least one household attribute;

in real-time, providing advertisers with access to the ranked data such that the advertisers can improve marketing metrics for advertisements delivered to the households; and

receiving monetary compensation for providing access to the ranked data.

10. The system of claim 9, wherein the service provider comprises at least one of a multiple service operator, a cable service provider, a telephone company, a mobile network operator, or a wireless service provider.

11. The system of claim 9, wherein the household comprises an individual subscriber.

12. The system of claim 9, wherein removing elements from the subscriber history data comprises removing personally identifiable information from the subscriber history data.

13. The system of claim 9, wherein the predictive model is configured to predict media habit and media exposure for at least one household.

14. The system of claim 9, wherein the at least one household attribute comprises at least one of a media habit and a media exposure.

15. The system of claim 9, wherein ranking each household relative to other households comprises assigning a formula to predict a household'"'"'s media habit and exposure.

16. The system of claim 9, wherein ranking each household relative to other households comprises assigning a household to at least one of a demographic segment and a group of lookalike households having similar media viewing habits.

17. A computer program product stored in one or more storage media for controlling a processing mode of a data processing apparatus, the computer program product being executable by the data processing apparatus to cause the data processing apparatus to perform operations comprising:

removing elements from the subscriber history data that allow the data to be attributed to a household;

aggregating the subscriber history data by an anonymous attribute;

deriving a predictive model for a plurality of households;

ranking each household in the plurality of households relative to other households according to at least one household attribute;

in real-time, providing advertisers with access to the ranked data such that the advertisers can improve marketing metrics for advertisements delivered to the households; and

receiving monetary compensation for providing access to the ranked data.

18. The computer program product of claim 17, wherein the service provider comprises at least one of a multiple service operator, a cable service provider, a telephone company, a mobile network operator, or a wireless service provider.

19. The computer program product of claim 17, wherein the household comprises an individual subscriber.

20. The computer program product of claim 17, wherein removing elements from the subscriber history data comprises removing personally identifiable information from the subscriber history data.

21. The computer program product of claim 17, wherein the predictive model is configured to predict media habit and media exposure for at least one household.

22. The computer program product of claim 17, wherein the at least one household attribute comprises at least one of a media habit and a media exposure.

23. The computer program product of claim 17, wherein ranking each household relative to other households comprises assigning a formula to predict a household'"'"'s media habit and exposure.

24. The computer program product of claim 17, wherein ranking each household relative to other households comprises assigning a household to at least one of a demographic segment and a group of lookalike households having similar media viewing habits.