The Nielsen Comapny (US), LLC

Kamer Toker Yildiz

Kumar Nagaraja Rao

Mimi Zhang

Jennifer Haskell

Cristina Ion

Methods and apparatus to correct errors in measuring audiences of over-the-top media are disclosed. In some examples, the methods and apparatus identify a first set of data from a first data source, the first set of data different from a second set of data from a second data source. In some examples, the methods and apparatus generate a third set of data based on the second set of data from the second data source. In some examples, the methods and apparatus generate a model based on a difference between the first set of data and the third set of data. In some examples, the methods and apparatus apply the model to the first set. In some examples, the methods and apparatus assign viewership to an impression associated with the first set of data by imputing viewership associated with the second set of data to the first set of data.

Methods and apparatus to correct errors in audience measurements for media accessed using over-the-top devices

An example system comprising at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to obtain first time information corresponding to one or more first times that a panelist accessed first media via a television, obtain second time information corresponding to one or more second times that a household accessed second media via an over-the-top device, the second time information matching the first time information and associated with corrected demographic information of members of the household, determine that a first genre of the first media matches a second genre of the second media, determine that a member of the household accessed the second media via the over-the-top device based on historical media access events of the panelist, and attribute the access of the second media to the member of the household to create a corrected demographic impression record.

An example to predict demographics for impressions includes a prediction manager to: determine that first demographic data corresponding to a first database proprietor subscriber does not match second demographic data corresponding to a media delivery device, both the first and second demographic data corresponding to an impression; obtain third demographic data corresponding to an Internet protocol address, the third demographic data obtained from a second database proprietor; and generate matched demographic data based on comparing the third demographic data to the first demographic data; and a modeler to generate a prediction model based on the matched demographic data, the prediction model to predict fourth demographic data for the impression.

Methods and apparatus to correct errors in audience measurements for media accessed using over the top devices

Methods and apparatus to predict demographics are disclosed. An example apparatus includes a prediction manager to access matched demographic impression data when a database proprietor subscriber does not match user data corresponding to a media delivery device, the matched demographic impression data including first demographic data stored by a database proprietor; a linear scaler to linearly scale the matched demographic impression data when the matched demographic impression data covers all demographic categories under consideration; a differential scaler to differentially scale the matched demographic impression data when the matched demographic impression data does not cover at least one of the demographic categories; and a modeler to: generate a model representative of the matched demographic impression data linearly scaled or the matched demographic impression data differentially scaled; and generate predicted demographic impression data by applying the model to second impression data to correct for the database proprietor not storing second demographic data.

Methods and apparatus to correct errors in measuring audiences of over the top media are disclosed. An example apparatus includes a demographic corrector to identify first impression data received from a computer, the first impression data including demographic data of users, the computer producing a misattribution error in the first impression data, and the misattribution error corresponding to a difference between reported demographics in the first impression data and actual demographics corresponding to the first impression data. The example demographic corrector further is to generate a model based on a difference between the first impression data and second data and generate corrected demographic data by applying the model to the first impression data. In addition, the example apparatus includes a viewership assigner to correct the misattribution error produced by the computer by assigning viewership to an impression associated with the first impression data using the corrected demographic data, at least one of the demographic corrector or the viewership assigner is a logic circuit.

Methods and apparatus to correct errors in measuring audiences of over-the-top media are disclosed. In some examples, the methods and apparatus identify a first set of data from a first data source, the first set of data different from a second set of data from a second data source. In some examples, the methods and apparatus generate a third set of data based on the second set of data from the second data source. In some examples, the methods and apparatus generate a model based on a difference between the first set of data and the third set of data. In some examples, the methods and apparatus apply the model to the first set of data. In some examples, the methods and apparatus assign viewership to an impression associated with the first set of data by imputing viewership associated with the second set of data to the first set of data.

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Campbell, CA, United States of America

Kamer Toker Yildiz