Habituation oriented product selection system

• US 8,055,546 B1
• Filed: 12/23/2008
• Issued: 11/08/2011
• Est. Priority Date: 12/23/2008
• Status: Expired due to Fees

• Current Assignee: Sprint Communications Company LP (Deutsche Telekom AG)
• Original Assignee: Sprint Communications Company LP (Deutsche Telekom AG)
• Inventors: Rossier, Douglas Michel, Cassone, Deandra T.
• Primary Examiner(s): Frenel; Vanel
• Application Number:
  US12/343,475
• Time in Patent Office: 1,050 Days
• Field of Search: 705 7- 10, 707/100, 707/102, 713/155
• US Class Current: 705/26
• 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

A processor-implemented method executing on a computer for using customer behavior to implement product design is provided. The method comprises the computer identifying a set of behavioral profiles that captures at least about sixty percent of a customer base, identifying products from a current offering that substantially match behavioral traits associated with each profile, and studying usage patterns of the products by customers, wherein the patterns are those of a plurality of customers using the products. The method also comprises the computer refining the profiles of the customers using the products, identifying underutilized features of the products based on patterns and one of discontinuing and repositioning the underutilized features, and identifying features indicated as desirable based on usage patterns and adding the features to the identified products; wherein the products comprise at least one of hardware, software executing on the hardware, and services associated with the use of the products.

Claims

1. A processor-implemented method executing on a computer system for using customer behavior to implement product design, comprising:

the computer system identifying a set of behavioral profiles that captures at least about sixty percent of a customer base;

the computer system identifying products from a current product offering that substantially match behavioral traits associated with the behavioral profiles;

the computer system studying usage patterns of the identified products by customers, wherein the usage patterns are those of a plurality of customers using the products;

the computer system refining the behavioral profiles using the usage patterns;

the computer system identifying underutilized features of the identified products based on the usage patterns and one of discontinuing and repositioning the underutilized features; and

the computer system identifying features indicated as desirable by customer behavior based on the usage patterns and adding the features to the identified products;

wherein the products comprise at least one of a consumer electronic device, software executing on the consumer electronic device, and services associated with the use of the consumer electronic device or software executing on the consumer electronic device.

2. The method of claim 1, wherein the consumer electronic devices comprise televisions, personal computers, and portable electronic devices.

3. The method of claim 1, wherein the identified products are mobile communications devices and subscription services associated with the mobile communications devices.

4. The method of claim 1, wherein behavioral profiles are based on traits indicated by customer usage patterns and habits.

5. The method of claim 4, wherein customer usage patterns and habits concern repeated behaviors by customers independent of a specific model of product and subscription service used.

6. The method of claim 4, wherein customer usage patterns and habits differ from tastes and preferences expressed by customers in questionnaire and survey input.

7. The method of claim 1, wherein between five and ten behavioral profiles are identified.

8. A processor-implemented method executing on a computer system, comprising:

the computer system identifying a set of behavioral profiles that captures at least about sixty percent of a customer base;

the computer system identifying products from a current product offering that substantially match behavioral traits associated with the behavioral profiles;

the computer system studying usage patterns of the products by customers, wherein usage patterns are those of a plurality of customers using the products;

the computer system refining the behavioral profiles using the usage patterns;

the computer system studying usage patterns of the identified products by customers not using the identified products that match their behavioral profile;

the computer system identifying features in products used by customers not using the products that match their behavioral profile, wherein the identified features are not present in the products that match their behavior profile;

the computer system studying the usage of the features; and

the computer system refining product offerings by adding some of the identified features to the products used by customers using the products that match their behavioral profile;

wherein the products comprise at least one of hardware, software executing on the hardware, and services associated with the use of the products.

9. The method of claim 8, wherein queries are submitted to customer usage databases to identify customers using products not matching their behavioral profiles.

10. The method of claim 8, wherein usage of products by customers associated with behavioral profiles not matching the products is studied for product upgrade and product evolution implications.

11. The method of claim 10, wherein features in products used by customers associated with behavioral profiles not matching the products are studied for feature upgrade and feature evolution implications.

12. The method of claim 8, wherein products are positioned to align directly with established customer usage habits without one of disrupting and changing established customer usage habits.

13. The method of claim 8, wherein a set of behavioral profiles is created based on observing patterns and habits of customer product usage.

14. The method of claim 8, wherein products and features are targeted at customers'"'"' established habitual usage behaviors.

15. A processor-implemented method executing on a computer system, comprising:

the computer system identifying a set of behavioral profiles that captures at least about sixty percent of a customer base;

the computer system identifying products from a current product offering that substantially match behavioral traits associated with the behavioral profiles;

the computer system studying usage patterns of the products by customers, wherein usage patterns are those of a plurality of customers using the products;

the computer system refining the behavioral profiles using the usage patterns;

the computer system identifying instances of potential product redundancy wherein at least two products from the current product offering are used by customers with the same behavioral profile;

the computer system identifying products that do not match behavioral profiles; and

the computer system refining product offerings by eliminating all but at least one of the products that redundantly serve the same behavioral profile and eliminating products determined to not align with a behavioral profile;

wherein the products comprise at least one of hardware, software executing on the hardware, and services associated with the use of the products.

16. The method of claim 15, wherein instances of product redundancy occur when at least two products from a product offering are used by customers associated with the same behavioral profile.

17. The method of claim 15, wherein product offerings aligned with behavioral profiles include subscription plans for services associated with the product offerings.

18. The method of claim 15, wherein subscription plans are associated with product pricing.

19. The method of claim 15, wherein the method aligns product functionality strengths with behavioral profiles.

20. The method of claim 15, further including designing products that align to customer usage habits based on behavioral profiles.