Granted Patent B1

US 8,448,057 · App. 12/498,628 · Granted May 21, 2013

Inventors: Charles Walsh Sugnet (San Francisco, CA); Joseph Harlan Shoop (Oakland, CA); Paul G Sutter (San Francisco, CA); Konrad S Feldman (San Francisco, CA)

Assignee: Quantcast Corporation

Abstract

Claims (69)

1. A computer-implemented method of selecting an audience segment from a pool of tracked entities based on a composite index indicating an aggregate similarity of the audience segment to an archetypical audience, the computer-implemented method comprising:

receiving user input indicating the archetypical audience, wherein the archetypical audience comprises tracked entities;

scoring tracked entities from the pool of tracked entities with a tracked entity score configured to indicate a similarity between the tracked entity and the archetypical audience, by building a model based at least in part on analyzing consumption histories for the tracked entities in the archetypical audience;

displaying on a device a graphical representation illustrating a distribution of the tracked entities with respect to the tracked entity scores;

receiving a second user input indicating the audience segment via a manipulation of the graphical representation;

determining a value for the composite index and a value for an audience segment size for the audience segment, based at least in part on the second user input; and

displaying the values for the composite index and audience segment size in association with the graphical representation.

2. The method of claim 1 further comprising:

receiving an adjustment user input indicating an adjusted audience segment via a manipulation of the graphical representation;

determining the values for the composite index and audience segment size for the adjusted audience segment, based at least in part on the adjustment user input; and

displaying the values for the composite index and audience segment size associated with the adjusted audience segment.

3. The method of claim 1 wherein:

the graphical representation comprises a graph with a curve indicating the distribution of tracked entities with respect to a similarity between the tracked entities in the pool and the archetypical audience.

4. The method of claim 3 wherein the manipulation of the graphical representation comprises positioning a cursor with respect to the curve.

5. The method of claim 1 wherein the composite index comprises a normalized composite index with the normalized composite index representing the aggregate similarity between the audience segment and the archetypical audience, normalized to a standard audience.

6. The method of claim 1 further comprising:

displaying on the device a selectable list of networked media content providers;

receiving a selection user input indicating the selection of one or more networked media content providers;

determining the values for the composite index and audience segment size for the adjusted audience segment, with the limitation that the audience segment must be selected from the audience comprising the selected networked media content providers; and

displaying the values for the composite index and audience segment size associated with the adjusted audience segment.

7. The method of claim 6 further comprising:

displaying on the device, a table of data for characterizing the networked media content providers;

determining the changes to the table of data as a result of the selection of one or more networked media content providers; and

displaying the table of data with updated data including the changes.

8. The method of claim 1 further comprising:

displaying on the device, a graphical selectable action mechanism for initiating a commercial action associated with the audience segment;

receiving a selectable action input indicating the selection of the commercial action; and

initiating the commercial action, responsive to the selectable action user input.

9. The method of claim 1 wherein the step of displaying comprises displaying on a device a graphical representation illustrating a cumulative distribution of tracked entities with respect to a similarity between the tracked entities in the pool and the archetypical audience.

10. The method of claim 1 wherein:

the composite index value comprises contributions from the tracked entity scores for a plurality of tracked entities in the audience segment.

11. A computer-implemented method of selecting an audience segment from a pool of tracked entities based on a composite index indicating an aggregate similarity of the audience segment to an archetypical audience, the computer-implemented method comprising:

receiving user input indicating the archetypical audience;

scoring tracked entities from the pool of tracked entities with a tracked entity score configured to indicate a similarity between the tracked entity and the archetypical audience;

displaying on a device a graphical representation illustrating a distribution of the tracked entities with respect to the tracked entity scores;

receiving a second user input indicating the audience segment via a manipulation of the graphical representation;

determining a value for the composite index and a value for an audience segment size for the audience segment, based at least in part on the second user input;

displaying the values for the composite index and audience segment size in association with the graphical representation;

displaying a graphical constraint selection mechanism for adjusting the audience segment by applying a constraint based on at least one attribute value to the audience segment;

receiving an audience segment constraint input indicating the selection of the constraint;

determining the value for the composite index and the value for the audience segment size for the adjusted audience segment, based at least in part on the audience segment constraint input; and

displaying the values for the composite index and audience segment size associated with the adjusted audience segment.

12. A computer-implemented method of selecting an audience segment from a pool of tracked entities based on a composite index indicating an aggregate similarity of the audience segment to an archetypical audience, the computer-implemented method comprising:

receiving user input indicating the archetypical audience;

scoring tracked entities from the pool of tracked entities with a tracked entity score configured to indicate a similarity between the tracked entity and the archetypical audience;

displaying on a device a graphical representation illustrating a distribution of the tracked entities with respect to the tracked entity scores;

receiving a second user input indicating the audience segment via a manipulation of the graphical representation;

determining a value for the composite index and a value for an audience segment size for the audience segment, based at least in part on the second user input;

displaying the values for the composite index and audience segment size in association with the graphical representation;

displaying a graphical constraint selection mechanism for adjusting the audience segment by applying a constraint based on at least one attribute value to the pool of tracked entities;

receiving a pool constraint input indicating the selection of the constraint;

determining the value for the composite index and the value for the audience segment size for the adjusted audience segment, based at least in part on the pool constraint input; and

displaying the values for the composite index and the audience segment size associated with the adjusted audience segment.

13. A non-transitory computer readable storage medium executing computer program instructions for selecting an audience segment from a pool of tracked entities based on a composite index indicating an aggregate similarity of the audience segment to an archetypical audience, the computer program instructions comprising instructions for:

receiving user input indicating the archetypical audience, wherein the archetypical audience comprises tracked entities;

scoring tracked entities from the pool of tracked entities with a tracked entity score configured to indicate a similarity between the tracked entity and the archetypical audience, by building a model based at least on part on analyzing consumption histories for the tracked entities in the archetypical audience;

displaying on a device a graphical representation illustrating a distribution of the tracked entities with respect to the tracked entity scores;

receiving a user input indicating the audience segment via a manipulation of the graphical representation;

determining a value for the composite index and a value for an audience segment size for the audience segment, based at least in part on the user input; and

displaying the values for the composite index and audience segment size in association with the graphical representation.

14. A system, comprising:

a processor; and

a computer readable storage medium storing processor-executable computer program instructions for selecting an audience segment from a pool of tracked entities based on a composite index indicating an aggregate similarity of the audience segment to an archetypical audience, the instructions comprising instructions for:

receiving user input indicating the archetypical audience, wherein the archetypical audience comprises tracked entities;

scoring tracked entities from the pool of tracked entities with a tracked entity score configured to indicate a similarity between the tracked entity and the archetypical audience, by building a model based at least in part on analyzing consumption histories for the tracked entities in the archetypical audience;

displaying on a device a graphical representation illustrating a distribution of the tracked entities with respect to the tracked entity scores;

receiving a user input indicating the audience segment via a manipulation of the graphical representation;

determining a value for the composite index and a value for an audience segment size for the audience segment, based at least in part on the user input; and

displaying the values for the composite index and audience segment size in association with the graphical representation.

Assignments (9)