Projecting person-level viewership from household-level tuning events

Patent metadata

Field	Value
Publication number	US-2016249098-A1
Application number	US-201514628106-A
Country	US
Kind code	A1
Filing date	Feb 20, 2015
Priority date	Feb 20, 2015
Publication date	Aug 25, 2016
Grant date	—

Abstract

The present disclosure describes techniques for projecting person-level viewership from household-level tuning events. One example method includes accessing tuning data representing television tuning events associated with particular households; accessing panelist viewing data representing television viewing events associated with panelists; and for at least one tuning event represented by the tuning data: accessing household member data associated with the tuning event; determining a member minutes value associated with each individual member of the particular household for the tuning event; and determining a fractional viewership value for each individual member of the particular household associated with the tuning event.

First claim

1 . A computer-implemented method comprising:
accessing tuning data representing television tuning events associated with particular households, each tuning event in the tuning data including an identification of a particular television program associated with the tuning event and a household minutes value representing a number of minutes the particular television program was played at a particular household in association with the tuning event; accessing panelist viewing data representing television viewing events associated with panelists, each viewing event in the viewing data including an identification of a particular television program associated with the viewing event and a panelist minutes value representing a number of minutes a panelist was exposed to the particular television program during the viewing event, each panelist associated with panelist information; and for at least one tuning event represented by the tuning data:
accessing household member data representing member information on individual members of a particular household associated with the tuning event, wherein the individual members are persons associated with the particular household;
determining a member minutes value associated with each individual member of the particular household for the tuning event, the member minutes value based at least in part on panelist minutes values for television viewing events from at least a portion of the panelist viewing data associated with members of panelist households whose panelist information matches at least a portion of the member information of the individual member;
determining a fractional viewership value for each individual member of the particular household associated with the tuning event, the fractional viewership value representing a probability that the individual member watched the television program associated with the tuning event, the fractional viewership value based at least in part on the portion of the panelist viewing data associated with members of panelist households whose panelist information matches at least a portion of the member information of the individual member.

2 . The method of claim 1 , further comprising:
before determining the member minutes values and fractional viewership values, applying a weighting factor to the panelist viewing data based on a distribution of demographic information associated with the members of panelist households.

3 . The method of claim 1 , wherein the panelist viewing data is based on monitoring viewing behavior of the members of panelist households.

4 . The method of claim 1 , wherein determining fractional viewership values for each individual member of the particular household for the tuning event comprises, for at least one of the individual members:
determining that a particular episode of a television program is associated with the tuning event; and determining a fraction of members of panelist households that watched the particular episode that have panelist information matching the member information for the individual member.

5 . The method of claim 1 , wherein determining fractional viewership values for each
individual member of the particular household for the tuning event comprises, for at least one of the individual members:
determining that a particular television network is associated with the tuning event; and
determining a fraction of members of panelist households that watched the particular television network that have panelist information matching the member information for the individual member.

6 . The method of claim 1 , wherein determining fractional viewership values for each individual member of the particular household for the tuning event comprises, for at least one of the individual members:
determining that a particular television entity is associated with the tuning event; and determining a fraction of members of panelist household that watched the particular television entity that have panelist information matching the member information for the individual member.

7 . The method of claim 1 , wherein:
the tuning data includes a time, date, and television network for each tuning event; and determining fractional viewership values for the individual members of the particular household comprises, for at least one of the individual members, determining a fraction of panelist members of other households with panelist information matching the member information for the individual member that watch the television network at the time and date associated with the tuning event.

8 . The method of claim 1 , wherein the member information includes one or more demographic groups to which the individual member belongs, and the panelist information includes one or more demographic groups to which the panelist member belongs.

9 . The method of claim 1 , wherein the member information includes a geographic area for the individual member, and the panelist information includes a geographic area for the panelist member.

10 . A computer-implemented method comprising:
accessing tuning data representing television tuning events associated with particular households, each tuning event in the tuning data including an identification of a television program played in association with the tuning event, and a household minutes value representing a number of minutes the television program was played at a particular household in association with the tuning event; accessing panelist viewing data representing television viewing events associated with panelists, each viewing event in the viewing data including an identification of a television program associated with the viewing event, and a panelist minutes value representing a number of minutes a particular panelist was exposed to the television program during the viewing event, each panelist associated with panelist information; identifying group subsets within the tuning data, each group subset including tuning data having matching values for a group criteria including attributes included in the tuning data and the panelist viewing data, wherein the group criteria includes at least one attribute of households associated with tuning data included in the group subset; identifying a particular television program for which to calculate unique viewers and person-level minutes; and for at least one particular group subset from the identified group subsets within the tuning data:
identifying matching panelist viewing data for the particular group subset, the matching panelist viewing data including panelist viewing data having matching values for the group criteria associated with the particular group subset;
calculating a unique viewers value for the particular group subset based on the matching panelist viewing data, wherein the unique viewers value represents an estimated number of individual members of households associated with the tuning data included in the group subset that watched the particular television program, and wherein the individual members are persons associated with the particular household;
calculating a person-level minutes value for the group subset based on the matching panelist viewing data, wherein the person-level minutes value represents an estimated number of minutes individual members of households associated with the tuning data included in the group subset watched the particular television program.

11 . The method of claim 10 , wherein the panelist viewing data includes observed viewing data obtained through monitoring viewing behavior of a plurality of panelists, and modeled viewing data obtained by applying statistical projections to household-level data.

12 . The method of claim

Assignees

• Comscore Inc

Inventors

• Pecjak Frank Eugene
• Nasr Ramzi Joseph
• Abraham Magid M
• Li Ying

Classifications

• H04N21/25883

  being end-user demographical data, e.g. age, family status or address (arrangements for identifying locations of users in broadcast systems H04H60/52) · CPC title

• H04N21/251

  Learning process for intelligent management, e.g. learning user preferences for recommending movies (details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08) · CPC title

• H04N21/2407

  Monitoring of transmitted content, e.g. distribution time, number of downloads (arrangements for monitoring programmes for broadcast or for distribution combined with broadcast H04H20/14) · CPC title

• H04N21/44218 Primary

  Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV programme (methods or arrangements for recognising human body or animal bodies or body parts G06V40/10; methods or arrangements for acquiring or recognising human faces, facial parts, facial sketches, facial expressions G06V40/16; methods or arrangements for recognising movements or behaviour G06V40/20; arrangements for identifying users in broadcast systems H04H60/45) · CPC title

• H04N21/44222 Primary

  Analytics of user selections, e.g. selection of programmes or purchase activity (monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33) · CPC title