Systems and methods for creating and evaluating content and predicting responses to content

• US 7,383,243 B2
• Filed: 06/05/2002
• Issued: 06/03/2008
• Est. Priority Date: 01/13/2000
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Erinmedia
• Inventors: Conkwright, G. Colby, Foster, IV, Frank S., Vinson, Michael J.
• Primary Examiner(s): Colbert, Ella
• Application Number:
  US10/162,222
• Publication Number:
  US 20030055759A1
• Time in Patent Office: 2,190 Days
• Field of Search: 705/1, 705/10, 705/14, 705/26, 705/27, 725/2, 725/9, 725/10, 725/14, 725/34, 725/35, 725/116, 345/719, 709/224, 707/1
• US Class Current: 725/2
• 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
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 30/0277 Online advertisement
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: Y10S 707/99931 Database or file accessing

Abstract

A method of creating new content based on previously experienced content and content ratings, in which content attributes are obtained and analyzed against set-top box events collected as the content is experienced. Analysis includes determining effects of various content attributes on content ratings, content attribute order on content ratings, and determining a preferred content attribute set and content attribute presentation order. Also taught is a system and method of predicting future events given a proposed dataset, in which past events are monitored and correlated with a proposed dataset sharing at least one attribute with, and having a substantially similar structure to, the past events, and the results of the correlation are reported as a prediction of future events. The invention further includes a method of predicting behaviors of non-sampled demographic specifications based on sampled demographic specifications of a given level, in which past behavior is monitored and correlated with demographic characteristics.

Claims

1. A system for predicting future events based on a proposed dataset, consisting of:

a dataset of past events, wherein the dataset of past events includes set-top box event data that is collected without knowing individual-specific demographic information;

a known dataset sharing at least one attribute with the dataset of past events, and with substantially similar attributes to the proposed dataset;

a means of correlating the dataset of past events with the known dataset to form a new dataset; and

,

a means of correlating the new dataset to the proposed dataset.

2. The system of claim 1, wherein the known dataset of includes content attributes and content presentation data.

3. The system of claim 2, wherein the proposed dataset of includes a set of content attributes for proposed content.

4. A system of predicting future events for a given demographic segment, comprising:

a dataset of past events, wherein the dataset of past events includes set-top box event data that is collected without knowing individual-specific demographic information;

a demographic dataset sharing at least one attribute with the dataset of past events;

a means of correlating the dataset of past events with the demographic dataset and storing the result in an array;

a known dataset sharing at least one attribute with the demographic dataset, and with substantially similar attributes to the proposed dataset;

a means of correlating the array with the known dataset to form a new dataset; and

,

a means of correlating the new dataset to a proposed dataset.

5. The system of claim 4, wherein the demographic dataset shares at least one of a zip code and other geographic identifier with the set-top box data.

6. The system of claim 4, wherein the known dataset shares at least one of a zip code or other geographic identifier with the array.

7. The system of claim 4, wherein the proposed dataset comprised of includes proposed content and attributes corresponding thereto.

8. A system of predicting future events for a given demographic segment, comprising:

a dataset of past set-top box events, collected manner without knowing individual-specific demographic information;

a demographic dataset sharing at least one attribute with the dataset of past set-top box events, such as a zip code or other geographic identifier;

a means of correlating the dataset of past events with the demographic dataset and storing the result in an array;

a known dataset sharing at least one attribute, such as a zip code or other geographic identifier, with the demographic dataset and with substantially similar attributes to the proposed dataset;

a means of correlating the array with the known dataset to form a new dataset; and

,

a means of correlating the new dataset with a proposed dataset comprised of includes proposed content and attributes corresponding thereto.

9. A method of predicting future events for a given demographic based on a proposed dataset, comprising:

monitoring past events, wherein the dataset of past events includes set-top box events that are monitored without knowing individual-specific demographic information;

correlating the past events with a demographic dataset and storing the result in an array;

correlating the array with a dataset sharing at least one attribute with the array, and with a substantially similar structure to the proposed dataset, the results of such correlations ere being stored in an additional dataset;

correlating the additional dataset with the proposed dataset; and

reporting the results of such correlations as a prediction of future events.

10. The method of claim 9, which wherein the demographic dataset and the set-top box event dataset contain zip code attributes.

11. The method of claim 9, wherein the proposed dataset includes proposed content attributes.

12. The method of claim 9, wherein the past events include attributes of any content being experienced at the time of an event.

13. A method of predicting future events for a given demographic based on a proposed dataset, comprising:

monitoring past events, including set-top box events, a zip code associated with a set-top box, and attributes of content presented by the set-top box at the time the event occurs, manner without knowing individual-specific demographic information;

correlating the past events with a demographic dataset which includes at least one zip code, and storing the result in an array;

correlating the array with a dataset sharing at least one attribute with the array, and with a substantially similar structure to the proposed dataset, the results of such correlations ere being stored in an additional dataset;

correlating the additional dataset with a proposed dataset, comprised of that includes proposed content attributes; and

reporting the results of such correlations as a prediction of future events.