Methods and apparatus to apply household-level weights to household-member level audience measurement data

Patent metadata

Field	Value
Publication number	US-2019057403-A1
Application number	US-201816168532-A
Country	US
Kind code	A1
Filing date	Oct 23, 2018
Priority date	Sep 25, 2015
Publication date	Feb 21, 2019
Grant date	—

Abstract

Methods and apparatus to apply household-level weights to audience measurement data at a household-member level are disclosed. An example method to determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population. First demographics of a first member of the first household are different than second demographics of a second member of the first household. The example method includes calculating a first household-level weight for the first household based on a demographics distribution of the sub-population and aggregate demographics of a population. The example method includes applying the first household-level weight to the first demographics of the first member, applying the first household-level weight to the second demographics of the second member, and estimating a demographics distribution of the population to measure a media audience of the population based on the weighted first demographics and the weighted second demographics.

First claim

1 .- 31 . (canceled)

32 . An apparatus to estimate a media audience size, the apparatus comprising:
a weight calculator to:
calculate a first household-level weight for a first household based on (a) a demographics distribution of a sub-population of the population and (b) a target value total constructed from aggregate demographics of the population, the weight calculator to calculate the first household-level weight by performing an iterative proportional fitting based on an initial weight for the first household, the target value total, and a constraint matrix; and
a population predictor to:
weight (1) first demographics of a first member of the first household and (2) second demographics of a second member of the first household using the first household level weight; and
reduce an amount of computations executed by a processor without calculating individual-level weights by estimating the media audience size based on the weighted first demographics and the weighted second demographics, wherein the weight calculator or the population predictor include a logic circuit.

33 . The apparatus as defined in claim 32 , wherein the weight calculator is to calculate a second household-level weight for a second household based on the demographics distribution of the sub-population and aggregate demographics of a population, the population predictor to weight (1) third demographics of a first member of the second household and (2) fourth demographics of a second member of the second household, the third demographics different from the fourth demographics, the population predictor to estimate the media audience size based on the weighted third demographics and the weighted fourth demographics.

34 . The apparatus as defined in claim 32 , wherein the first demographics of the first member of the first household includes a first demographic constraint associated with the first member, and the second demographics of the second member of the first household includes a second demographic constraint associated with the second member.

35 . The apparatus as defined in claim 32 , wherein the population predictor is to:
associate a tuning event of the first household with the first household-level weight; associate the tuning event with the first demographics of the first member and the second demographics of the second member; and scale up the first demographics and the second demographics by the first household-level weight to measure the media audience of the population for the tuning event.

36 . The apparatus as defined in claim 32 , wherein the population predictor is to estimate the constraint matrix based on the demographics of the members of the sub-population.

37 . The apparatus as defined in claim 36 , further including a sub-population determiner to construct the constraint matrix by:
assigning a map to the first household as a column of the constraint matrix; assigning a demographic constraint as a row of the constraint matrix; and inserting a value indicative of a quantity of members of the first household associated with the demographic constraint as an element in the column and the row of the constraint matrix.

38 . The apparatus as defined in claim 32 , wherein the weight calculator is to reduce an amount of computations executed by the processor by measuring an audience of the population by utilizing tuning data collected from the first household of the sub-population without collecting consumption data from the members of the sub-population.

39 . The apparatus as defined in claim 32 , wherein the population predictor is to:
weight the first demographics of the first member by multiplying the first demographics by the first household-level weight, the weighted first demographics representing a first quantity of members of the population having the first demographics; and weight the second demographics of the second member by multiplying the second demographics by the first household-level weight, the weighted second demographics representing a second quantity of members of the population having the second demographics.

40 . A non-transitory computer-readable storage medium comprising computer-readable instructions that, when executed, cause a processor to:
calculate a first household-level weight for a first household based on (a) a demographics distribution of a sub-population of a population and (b) a target value total constructed from aggregate demographics of the population, the calculating including performing an iterative proportional fitting based on an initial weight for the first household, the target value total, and a constraint matrix; weight (1) first demographics of a first member of the first household and (2) second demographics of a second member of the first household using the first household level weight; and reduce an amount of computations executed by the processor without calculating individual-level weights by estimating a media audience size based on the weighted first demographics and the weighted second demographics.

41 . The non-transitory computer-readable storage medium as defined in claim 40 , wherein the computer-readable instructions, when executed, further cause the processor to:
calculate a second household-level weight for a second household based on the demographics distribution of the sub-population and the aggregate demographics of the population; weight (1) third demographics of a first household member of the second household and (2) fourth demographics of a second household member of the second household, the third demographics different from the fourth demographics; and estimate the media audience size based on the weighted third demographics and the weighted fourth demographics.

42 . The non-transitory computer-readable storage medium as defined in claim 40 , wherein the first demographics of the first member of the first household include a first demographic constraint associated with the first member, and the second demographics of the second member of the first household include a second demographic constraint associated with the second member.

43 . The non-transitory computer-readable storage medium as defined in claim 40 , wherein the computer-readable instructions, when executed, further cause the processor to:
associate a tuning event of the first household with the first household-level weight; associate the tuning event with the first demographics of the first member and the second demographics of the second member; and scale up the first demographics and the second demographics by the first household-level weight to estimate the media audience size for the tuning event.

44 . The non-transitory computer-readable storage medium as defined in claim 40 , wherein to estimate the demographics distribution, the computer-readable instructions, when executed, further cause the processor to construct the constraint matrix based on the demographics of the members of the sub-population.

45 . The non-transitory computer-readable storage medium as defined in claim 44 , wherein to construct the constraint matrix, the computer-readable instructions, when executed, further cause the processor to:
assign the first household as a column of the constraint matrix; assign a demographic constraint as a row of the constraint matrix; and insert a value indicative of a quantity of members of the first household associated with the demographic constraint as an element in the column and the row of the constraint matrix.

46 . The non-transitory computer-readable storage medium as defined in claim 40 , wherein to reduce the amount

Assignees

• Nielsen Co Us Llc

Inventors

• Sheppard Michael
• Sullivan Jonathan
• Lipa Peter
• Terrazas Alejandro

Classifications

• G06Q30/0201 Primary

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

• H04N21/44213

  Monitoring of end-user related data (arrangements for monitoring the users' behaviour or opinions in broadcast systems H04H60/33) · CPC title

• H04N21/42684

  Client identification by a unique number or address, e.g. serial number, MAC address, socket ID (network arrangements, protocols or services for addressing or naming H04L61/00) · CPC title

• 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

• H04N21/258

  Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data {(arrangements for services using the result on the distributing side of broadcast systems H04H60/66; profiles in network data switching protocols H04L67/30)} · CPC title