The Nielsen Comapny (us), LLC

Christine Bourquin

Molly Poppie

David J Kurzynski

Peter Campbell Doe

Balachander Shankar

Jarrett Garcia

Lukasz Chmura

Huaxin You

Timothy Dolson

Jone Mary Burr

Samantha M Mowrer

Remy Spoentgen

Choongkoo Lee

Anthony P Venetucci

Xiaoqi Cui

Methods, apparatus, systems and articles of manufacture are disclosed to characterize households with media meter data. An example method includes identifying, with a processor, a power status and a first automatic gain control (AGC) value for an exposure minute from a panelist audience meter in a first household, the panelist audience meter comprising a power sensor, identifying a second AGC value and a daypart for a household tuning minute from a first media meter (MM) in the first household, the MM comprising microphones to collect audio data, and calculating model coefficients based on the exposure minute and the household tuning minute to be applied to data from a second MM in a second household, the model coefficients to facilitate a power status probability calculation in the second household devoid of the panelist audience meter having the power sensor.

Methods and apparatus to characterize households with media meter data

Methods, apparatus, systems and articles of manufacture are disclosed to characterize households with media meter data. An example method includes identifying, with a processor, a household minute credited to a station in a household by a first media meter (MM) device, the first MM device collecting only audio data, determining whether a panelist audience meter device is crediting the station at the same time in the household, when the panelist audience meter device is crediting the same station, associating the household minute with an ambient tuning status, identifying a first automatic gain control (AGC) value and a first code status of the household minute, calculating model coefficients based on the ambient tuning status, the first AGC value and the first code status, and calculating a probability of ambient tuning based on the model coefficients.

Methods, apparatus, systems and articles of manufacture are disclosed to characterize households with media meter data. An example method includes identifying, with a processor, a target set of household categories associated with a target research geography, when a quantity of households within the target research geography representing the target set of household categories does not satisfy a threshold value, generating a first subset of categories and a second subset of categories from the target set of household categories, identifying a first set of households representing the first subset of categories from the target set of household categories and identifying an associated total number of household tuning minutes and a total number of household exposure minutes associated therewith, for each category in the second subset of categories from the target set of household categories, calculating a household tuning proportion and an exposure proportion, the household tuning proportion and exposure proportion based on the total number of household tuning minutes and exposure minutes, respectively, and calculating the panelist behavior probability based on the exposure proportion and the household tuning proportion.

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Wheeling, IL, United States of America

Christine Bourquin