Automated user evaluation and lifecycle management for digital products, services and content

• US 20050283394A1
• Filed: 05/12/2005
• Published: 12/22/2005
• Est. Priority Date: 06/21/2004
• Status: Abandoned Application

• Current Assignee: Autolytics Incorporated
• Original Assignee: Autolytics Incorporated
• Inventors: Rub, Leonardo, McGloin, Patricia, McGloin, Justin
• Application Number:
  US11/128,867
• Publication Number:
  US 20050283394A1
• Time in Patent Office: Days
• US Class Current: 705/7.32
• 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 30/0203 Market surveys; Market polls

Abstract

A user in an identified adoption group is periodically queried regarding use of a product. Results of the querying are received and evaluated. The evaluating includes aggregating the results by category, computing a proportion of total results for each category, and generating a first user emphasis vector based on the proportion of total results for each category. Based on the evaluating, a determination is made whether to incorporate the results of the querying into a representative result for an evaluation group.

Claims

1. A machine-implemented method comprising:

periodically querying a user in an identified adoption group regarding use of a product;

receiving results of the querying;

evaluating the results, the evaluating including

aggregating the results by category,

computing a proportion of total results for each category, and

generating a first user emphasis vector based on the proportion of total results for each category; and

based on the evaluating, determining whether to incorporate the results of the querying into a representative result for an evaluation group.

2. The method of claim 1, wherein evaluating the results further comprises:

correlating the first user emphasis vector with vectors for neighboring intervals of a lifecycle curve for the product.

3. The method of claim 2, further comprising:

selecting a vector for the neighboring intervals with a high correlation to the first user emphasis vector;

associating the first user emphasis vector with a first adoption status for the product, the first adoption status corresponding to the selected vector; and

estimating a first representative user emphasis vector for the first adoption status.

4. The method of claim 3, further comprising:

based on the first user emphasis vector, the first adoption status, and the first representative user emphasis vector, estimating a second representative user emphasis vector for a next adoption status for the product.

5. The method of claim 3, further comprising corroborating the first representative user emphasis vector with quantitative data of the identified adoption group.

6. An apparatus comprising:

means for periodically querying a user in an identified adoption group regarding use of a product;

means for receiving results of the querying;

means for evaluating the results, the evaluating including

means for aggregating the results by category,

means for computing a proportion of total results for each category, and

means for generating a first user emphasis vector based on the proportion of total results for each category; and

means for, based on the evaluating, determining whether to incorporate the results of the querying into a representative result for an evaluation group.

7. The apparatus of claim 6, wherein the means for evaluating the results further comprises:

means for correlating the first user emphasis vector with vectors for neighboring intervals of a lifecycle curve for the product.

8. The apparatus of claim 7, further comprising:

means for selecting a vector for the neighboring intervals with a high correlation to the first user emphasis vector;

means for associating the first user emphasis vector with a first adoption status for the product, the first adoption status corresponding to the selected vector; and

means for estimating a first representative user emphasis vector for the first adoption status.

9. The apparatus of claim 8, further comprising:

means for, based on the first user emphasis vector, the first adoption status, and the first representative user emphasis vector, estimating a second representative user emphasis vector for a next adoption status for the product.

10. The apparatus of claim 8, further comprising means for corroborating the first representative user emphasis vector with quantitative data of the identified adoption group.

11. A machine-readable medium having instructions to cause a machine to perform a machine-implemented method comprising:

periodically querying a user in an identified adoption group regarding use of a product;

receiving results of the querying;

evaluating the results, the evaluating including

aggregating the results by category,

computing a proportion of total results for each category, and

generating a first user emphasis vector based on the proportion of total results for each category; and

based on the evaluating, determining whether to incorporate the results of the querying into a representative result for an evaluation group.

12. The machine-readable medium of claim 11, wherein evaluating the results further comprises:

correlating the first user emphasis vector with vectors for neighboring intervals of a lifecycle curve for the product.

13. The machine-readable medium of claim 12, wherein the method further comprises:

selecting a vector for the neighboring intervals with a high correlation to the first user emphasis vector;

associating the first user emphasis vector with a first adoption status for the product, the first adoption status corresponding to the selected vector; and

estimating a first representative user emphasis vector for the first adoption status.

14. The machine-readable medium of claim 13, wherein the method further comprises:

based on the first user emphasis vector, the first adoption status, and the first representative user emphasis vector, estimating a second representative user emphasis vector for a next adoption status for the product.

15. The machine-readable medium of claim 13, wherein the method further comprises corroborating the first representative user emphasis vector with quantitative data of the identified adoption group.

16. A system comprising:

a processing unit coupled to a memory through a bus; and

a process executed from the memory by the processing unit to cause the processing unit to;

periodically query a user in an identified adoption group regarding use of a product;

receive results of the querying;

evaluate the results, the evaluating including

aggregating the results by category,

computing a proportion of total results for each category, and

generating a first user emphasis vector based on the proportion of total results for each category; and

based on the evaluating, determine whether to incorporate the results of the querying into a representative result for an evaluation group.

17. The system of claim 16, wherein evaluating the results further comprises:

correlating the first user emphasis vector with vectors for neighboring intervals of a lifecycle curve for the product.

18. The system of claim 17, wherein the process further causes the processing unit to:

select a vector for the neighboring intervals with a high correlation to the first user emphasis vector;

associate the first user emphasis vector with a first adoption status for the product, the first adoption status corresponding to the selected vector; and

estimate a first representative user emphasis vector for the first adoption status.

19. The system of claim 18, wherein the process further causes the processing unit to:

based on the first user emphasis vector, the first adoption status, and the first representative user emphasis vector, estimate a second representative user emphasis vector for a next adoption status for the product.

20. The system of claim 18, wherein the process further causes the processing unit to corroborate the first representative user emphasis vector with quantitative data of the identified adoption group.