Visualizing Audience Metrics

Patent metadata

Field	Value
Publication number	US-2016140609-A1
Application number	US-201414542389-A
Country	US
Kind code	A1
Filing date	Nov 14, 2014
Priority date	Nov 14, 2014
Publication date	May 19, 2016
Grant date	—

Abstract

A social networking system receives a selection of user characteristics defining a benchmark audience and a target audience, and generates audience metrics that compare the audiences across a set of user characteristics. These user characteristics include demographics, interests, purchasing activity, and actions on the social networking system. The audience metrics are provided to an advertiser who may select additional user characteristics to refine the benchmark or target audiences. The audience metrics may include an affinity score that compares the audience metrics for a particular type of interaction, and may normalize the frequency of interactions relative to interactions of the audience as a whole. Advertisers may use the defined audiences to establish targeting criteria for an advertisement, and may use existing targeting criteria to seed the selection of an audience.

First claim

What is claimed is:

1 . A method comprising:
identifying a set of benchmark users of an online system; receiving, from a user of the online system, a selection of target user characteristics defining a set of target audience users of the online system; identifying a measured user characteristic for generating an audience metric describing the comparative differences in the measured user characteristic for the benchmark users and target audience users; determining a benchmark frequency of the measured user characteristic for the set of benchmark users; determining a target frequency of the measured user characteristic for the set of target audience users; computing the audience metric by comparing the target frequency with the benchmark frequency; and providing one or more audience metrics for display to the user, the one or more audience metrics sent for display including the computed audience metric.

2 . The method of claim 1 , further comprising:
receiving, from the user, a selection of an additional user characteristic included in the one or more audience metrics sent for display; adding the additional user characteristic to the selection of target user characteristics thereby defining an updated set of target audience users; determining an updated target frequency of the measured user characteristic for the updated set of target audience users; computing an updated audience metric by comparing the updated target frequency with the benchmark frequency; and providing the updated audience metric for display to the user.

3 . The method of claim 1 , wherein the set of audience users is a subset of the set of benchmark users.

4 . The method of claim 1 , wherein the set of audience users is a subset of the set of benchmark users that like a page associated with an advertiser.

5 . The method of claim 1 , wherein the user characteristics describe demographics data of the users.

6 . The method of claim 5 , wherein the demographics data is selected from a group consisting of: gender, age, income, profession, education level, relationship status, and any combination thereof.

7 . The method of claim 1 , wherein the user characteristics describe an action of a user.

8 . The method of claim 7 , wherein the action is selected from a group consisting of: liking a page on a social network; interacting with a page; subscribing to an event, purchasing a product; receiving an advertising impression; performing a conversion action for an advertisement, and any combination thereof.

9 . A non-transitory computer-readable medium comprising instructions that when executed by a processor cause the processor to perform steps of:
identifying a set of benchmark users of an online system; receiving, from a user of the online system, a selection of target user characteristics defining a set of target audience users of the online system; calculating an audience metric describing a comparative frequency that the set of target audience users is associated with a measured user characteristic relative to a frequency that the set of benchmark users is associated with the measured user characteristic; and providing the audience metrics for display to the user.

10 . The non-transitory computer-readable medium of claim 9 , further comprising:
receiving, from the user, a selection of an additional user characteristic included in the audience metrics sent for display; adding the additional user characteristic to the selection of target user characteristics thereby defining an updated set of target audience users; calculating updated audience metrics describing the comparative frequency that the updated set of target audience users is associated with the measured user characteristics relative to the frequency that the set of benchmark users is associated with the measured user characteristics; and providing the updated audience metrics for display to the user.

11 . The non-transitory computer-readable medium of claim 9 , wherein the set of audience users is a subset of the set of benchmark users.

12 . The non-transitory computer-readable medium of claim 9 , wherein the set of audience users is a subset of the set of benchmark users that like a page associated with an advertiser.

13 . The non-transitory computer-readable medium of claim 9 , wherein the user characteristics describe demographics data of the users.

14 . The non-transitory computer-readable medium of claim 13 , wherein the demographics data is selected from a group consisting of: gender, age, income, profession, education level, relationship status, and any combination thereof.

15 . The non-transitory computer-readable medium of claim 9 , wherein the user characteristics describe an action of a user.

16 . The non-transitory computer-readable medium of claim 15 , wherein the action is selected from a group consisting of: liking a page on a social network; interacting with a page; subscribing to an event, purchasing a product; receiving an advertising impression; performing a conversion action for an advertisement, and any combination thereof.

Assignees

• Facebook Inc

Inventors

• Demir Deniz
• Pinkowish Michael Desmond
• He Liang
• Gao Yingsheng
• Abdelrahman Islam Farid Hamed
• Krakaris Alexandra Louise
• Frank Ajoy Joseph
• Gershbein Reid Steven
• Ayyar Srikant Ramakrishna
• Arpat Guven Burc
• Develin Michael Lee
• Hudack Michael Nicholas
• SOKOLOV Maxim
• Zhao Wenrui
• Shottan Jonathan
• Glemann Aaron Ted
• Timonina Ksenia

Classifications

• G06F16/9038

  Presentation of query results · CPC title

• G06Q30/0251 Primary

  Targeted advertisements · CPC title

• G06F16/26

  Visual data mining; Browsing structured data · CPC title

• G06Q30/0201

  Market modelling; Market analysis; Collecting market data · CPC title

• G06F16/248

  Presentation of query results · CPC title