The Nielsen Comapny (us), LLC

Clypd, Inc.

Peter Campbell Doe

Michael R Sheppard

Jonathan Lee Sullivan

Paul Donato

Peter Lipa

Peng Fei Yi

Matthew B Reid

Scott John Sereday

Jingsong Cui

James R Oliver

Herbert F Stackhouse

Qian Tang

Michelle Ha

Molly Poppie

David J Kurzynski

Balachander Shankar

Edmond Wong

Jarrett Garcia

Lukasz Chmura

Huaxin You

Christine Bourquin

Timothy Dolson

Jone Mary Burr

Candy Tang

David N Wong

Samantha M Mowrer

Kumar Nagaraja Rao

Mainak Mazumdar

Remy Spoentgen

Seema Varma Srivastava

Xiaoqi Cui

Choongkoo Lee

Anthony P Venetucci

Jason M Burke

Joel C Melby

Methods, apparatus, systems and articles of manufacture are disclosed to project ratings for future broadcasts of media. Disclosed example methods include normalizing, with a processor, audience measurement data corresponding to media exposure data, social media exposure data and programming information associated with a future quarter to determine normalized audience measurement data. Disclosed example methods also include classifying a media asset based on the programming information to determine a media asset classification. Disclosed example methods also include building, with the processor, a projection model based on a first subset of the normalized audience measurement data, the first subset of the normalized audience measurement data associated with a first time frame relative to the future quarter, the first subset of the normalized audience measurement data based on the media asset classification, and applying, with the processor, the programming information to the projection model to project ratings for the media asset.

Methods and apparatus to project ratings for future broadcasts of media

Methods and apparatus to determine probabilistic media viewing metrics are disclosed herein. An example apparatus includes memory including machine reachable instructions; and processor circuitry to execute the instructions to calculate a first probability for respective ones of a plurality of panelists as having viewed media based on viewing data, the viewing data including incomplete viewing data for one or more of the panelists relative to the media; identify respective ones of a plurality of panelists as included in a demographic subgroup based on demographic data for the panelists; assign a sampling weight to the respective ones of the plurality of panelists based on the demographic data; and calculate a second probability of the demographic subgroup having viewed the media based on the first probabilities and the sampling weights for the respective ones of the plurality of panelists in the demographic subgroup.

Methods and apparatus to determine probabilistic media viewing metrics

Disclosed examples determine a unique audience exposed to media while reducing memory resources of a computing device. Example instructions program programmable circuitry to log a plurality of impressions corresponding to media accessed at client devices; generate a first value based on a count of the impressions and a count of users of a database proprietor that accessed the media; generate a second value based on the first value and a count of demographic impressions logged by the database proprietor; and determine a unique audience size based on the second value.

Methods and apparatus for estimating total unique audiences

Disclosed example audience measurement apparatus determine a first audience metric based on set-top box return path tuning data obtained from set-top boxes located in a first geographic area; determine a second audience metric from a portion of audience measurement data corresponding to a second geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the set-top boxes located in the first geographic area; determine ratios of (i) respective first audience metrics determined for respective demographic stratifications to (ii) corresponding second audience metrics determined for the respective demographic stratifications; and combine the ratios after multiplication with third audience metrics determined, for the respective demographic stratifications, from the audience measurement data to determine an audience exposure metric that estimates exposure to media in the first geographic area.

Methods, apparatus and articles of manufacture to estimate local market audiences of media content

Methods, apparatus, systems to determine a conditional probability based on audience member probability distributions for media audience measurement are disclosed. Disclosed example methods for media audience measurement include determining a first audience probability distribution for a first member of a household and determining a second audience probability distribution for a second member of the household. Disclosed example methods also include calculating probabilities for audience combinations of the first member and the second member of the household based on the first audience probability distribution and the second audience probability distribution. Disclosed example methods further include determining a household audience characteristic probability based on the calculated probabilities of the audience combinations of the household. The household audience characteristic indicates likelihoods of different possible audience compositions of the household for a media event.

Methods and apparatus to determine a conditional probability based on audience member probability distributions for media audience measurement

Methods and apparatus to monitor media content at a content display site are described. An example apparatus includes processor circuitry to execute computer readable instructions to: estimate a first audience size associated with unmeasured locations based on distributed census-based page views and a measured panel data; generate a virtual panel based on the first audience size to enable more accurate estimation of traffic from the unmeasured locations by weighting second panelists associated with the unmeasured locations and reweighting a subset of the second panelists; and determine additional activity not represented by the measure panel data; and calculate an online audience based on a measured location audience, the virtual panel, and the additional activity.

Systems, methods, and articles of manufacture to measure online audiences

Example methods disclosed herein include accessing a query requesting a metric associated with a number of unique members of an audience of media over an aggregate monitoring interval corresponding to a plurality of component monitoring intervals. Disclosed example methods also include determining respective aggregate interval probability distributions modeling likelihoods of respective monitored individuals being exposed to the media during the aggregate monitoring interval, a first one of the aggregate interval probability distributions for a first one of the monitored individuals being determined by combining parameters of respective component interval probability distributions modeling likelihoods of the first one of the monitored individuals being exposed to the media during respective ones of the component monitoring intervals. Disclosed example methods further include evaluating an audience-level probability distribution determined from the aggregate interval probability distributions to determine the metric to transmit to the computing device in response to the query.

Determining metrics characterizing numbers of unique members of media audiences

Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. An example apparatus includes memory; instructions in the apparatus; and processor circuitry to execute the instruction to, based on impression requests from a plurality of client devices via a network, log a plurality of impressions corresponding to media accessed at the client devices; generate a product by multiplying a count of the impressions by a square of a count of registered users of a database proprietor exposed to the media; generate a quotient by dividing the product by a count of demographic impressions logged by the database proprietor; and determine a unique audience size based on a square root of the quotient.

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Ridgewood, NJ, United States of America

Peter Campbell Doe