The Nielsen Comapny (us), LLC

Sabic Global Technologies B.v.

Shpp Global Technologies B.v.

Richard Peters

Jonathan Lee Sullivan

James Alan Mahood

David J Kurzynski

Molly Poppie

Balachander Shankar

Samantha M Mowrer

Pankaj Singh Gautam

Remy Spoentgen

Choongkoo Lee

Xiaoqi Cui

Ieok Hou Wong

Paul J Chimenti

Rachel Worth Olson

Denis Voytenko

William E Hollar, Jr

Thomas Hocker

Xuezhi Jin

Evelyn Pearson

Elisabeth Weber

Methods, apparatus, systems and articles of manufacture to impute media consumption behavior are disclosed. An example system includes one or more media meters to obtain tuning data, one or more people meters to obtain viewing data, and one or more servers to, in response to a determination that a difference satisfies a first threshold, determine that a first subset of the tuning data associated with first panelist households having tuned to first media in a first area exhibits local bias, determine that a second subset of the viewing data associated with second panelist households having viewed the first media in the second area represents heavy viewing, and impute the second subset of the viewing data for the first subset of the tuning data in response to the second subset of the viewing data representing heavy viewing.

Methods and apparatus to impute media consumption behavior

Methods, apparatus, systems and articles of manufacture to assign viewers to media meter data are disclosed. An apparatus includes processor circuitry to execute computer readable instructions to at least: identify a candidate household from a plurality of second households to associate with a first household based on an analysis of a first duration of time first media was presented by a first media presentation device and a second duration of time second media was presented by second media presentation devices; match different ones of first panelists of the first household with matching ones of second panelists of the candidate household; and impute respective portions of the first duration of time to the different ones of the first panelists based on portions of the second duration of time for which the matching ones of the second panelists of the candidate household were exposed to the second media.

Methods and apparatus to assign viewers to media meter data

Methods, apparatus, systems and articles of manufacture to assign viewers to media meter data are disclosed. An apparatus includes memory, and a processor to execute instructions to: determine first probabilities for first panelists in a first household based on a first number of minutes of first media presented by a first media presentation device monitored by a first meter, determine second probabilities for second panelists in a plurality of second households based on a second number of minutes of second media presented by second media presentation devices monitored by a plurality of second meters, compare the first probabilities and the second probabilities to identify a candidate household from the plurality of second households to associated with the first household, and impute respective portions of the first number of minutes to corresponding ones of the first panelists when monitored behavior of the candidate household matches monitored behavior of the first household.

Methods, apparatus, systems and articles of manufacture to build viewing sessions from ping-level data are disclosed herein. An example apparatus includes a threshold calculator to determine a threshold based on reference sessions represented in panel data obtained from panel meters. The example apparatus also includes a session partitioner to determine if a first ping from a device corresponds to a start ping of the session and a second ping from the device corresponds to an end ping of the session based on (i) the threshold, (ii) first payload data from the first ping, and (iii) second payload data from the second ping. The example apparatus includes the session partitioner to also determine a duration of the session based on a difference between a first time associated with the first ping and a second time associated with the second ping.

Methods and apparatus for session building from ping-level data

Methods, apparatus, systems and articles of manufacture to impute media consumption behavior are disclosed. An example apparatus includes a localized event engine implemented with hardware or at least one processor to, in response to a difference satisfying a first threshold, determine that a first subset of tuning data exhibits local bias, the difference to be between (i) a first percentage of exposure minutes determined from the tuning data, and (ii) a second percentage of exposure minutes determined from viewing data, determine that a second subset of the viewing data represents heavy viewing in response to (1) a first number of households satisfying a second threshold and (2) a third percentage of exposure minutes satisfying a third threshold, and a localized event selector implemented with hardware or the at least one processor to impute the second subset of the viewing data for the first subset of the tuning data.

Methods, apparatus, systems and articles of manufacture to assign viewers to media meter data are disclosed. An apparatus includes memory to store instructions, and a processor to execute the instructions to at least: determine first probabilities for first panelists in a media meter household during a first set of time periods, determine second probabilities for second panelists in a plurality of learning households during a second set of time periods, compare the first probabilities and the second probabilities to identify a candidate household from the plurality of learning households to associated with the media meter household, and impute ones of the first number of minutes to individual ones of the first panelists when second panelist behavior data associated with the candidate household indicates activity during one of the second set of time periods that matches activity in the media meter household during one of the first set of time periods.

Methods, apparatus, systems and articles of manufacture to impute media consumption behavior are disclosed. An example method includes calculating, by executing an instruction with a processor, first viewing probabilities for tuning panelists in a tuning household. The example method also includes calculating, by executing an instruction with the processor, second viewing probabilities for viewing panelists in a plurality of learning households having a same household size as the tuning household. The example method also includes identifying, by executing an instruction with the processor, a matching one of the plurality of learning households based on a difference between the first viewing probabilities and respective ones of the second viewing probabilities.

Methods, apparatus, systems and articles of manufacture to improve viewer assignment by adjusting for a localized event are disclosed. An example method includes identifying, by executing an instruction with a processor, heavy tuning data associated with panelists in a first area based on (1) a first number of households tuned to first media in the first area and (2) a first percentage of exposure minutes tuned to the first media in the first area. The example method also includes determining, by executing an instruction with the processor, if the heavy tuning data represents a local bias based on a second percentage of exposure minutes tuned to second media in a second area.

Methods and apparatus to improve viewer assignment by adjusting for a localized event

Methods, apparatus, systems and articles of manufacture are disclosed to assign viewers to media meter data. An example method includes calculating, with a processor, first viewing probabilities for tuning panelists in a tuning household during a first set of time periods, calculating, with the processor, second viewing probabilities for viewing panelists in a plurality of candidate viewing households during a second set of time periods, identifying, with the processor, a matching one of the plurality of candidate viewing households based on an absolute difference value between an average value of the first viewing probabilities and respective ones of average values of the second viewing probabilities, and reducing an imputation error by imputing, with the processor, tuning minutes of the tuning household as viewing minutes for the respective tuning panelists when the matching one of the plurality of candidate viewing households exhibits viewing activity during one of the second set of time periods that matches one of the first set of time periods.

Growing community of inventors

Gurnee, IL, United States of America

Richard Peters