Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a probability distribution of actual durations of first tuning segments, the first tuning segments representative of lengths of time during which panelists accessed first media; modify the lengths associated with ones of the first tuning segments to generate second tuning segments having second durations; and estimate a time when a media device associated with a return path data (RPD) device is powered on based on (i) the probability distribution, (ii) the second tuning segments, and (iii) a third tuning segment during which the RPD device accessed second media, the third tuning segment reported from the RPD device.

Abstract: Disclosed examples obtain an overlap multiplier as a ratio of (1) a first product of a panel duplication reach and a did-not-view reach and (2) a second product of a television panel reach and a digital panel reach, the panel duplication reach based on a duplicated audience size and a panelist population, the did-not-view reach based on a television audience size, a digital audience size, the duplicated audience size, and the panelist population, the television panel reach corresponding to the television audience size, the digital panel reach corresponding to the digital audience size; and determine a total audience for a media item based on a television audience reach, a digital audience reach, and a duplication factor, the duplication factor based on the television audience reach, the digital audience reach, and the overlap multiplier, the television audience reach corresponding to television media, the digital audience reach corresponding to digital media.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a probability distribution of actual durations of first tuning segments, the first tuning segments representative of lengths of time during which panelists accessed first media; modify the lengths associated with ones of the first tuning segments to generate second tuning segments having second durations; and estimate a time when a media device associated with a return path data (RPD) device is powered on based on (i) the probability distribution, (ii) the second tuning segments, and (iii) a third tuning segment during which the RPD device accessed second media, the third tuning segment reported from the RPD device.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Disclosed examples determine a duplicated audience size representative of panelists exposed to television media and digital media; determine a panel duplication reach based on the duplicated audience size and a panelist population; determine a did-not-view reach based on a television audience size, a digital audience size, the duplicated audience size, and the panelist population; obtain an overlap multiplier as a ratio of (1) a product of the panel duplication reach and the did-not-view reach and (2) a product of a television panel reach and a digital panel reach; determine a duplication factor for a media item based on a television audience reach, a digital audience reach, and the overlap multiplier; and determine a total audience for the media item based on the television audience reach, the digital audience reach, and the duplication factor.

Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a first probability distribution indicative of actual durations of panel tuning segments, the panel tuning segments corresponding to time periods during which panelists were exposed to first media; generate a second probability distribution indicative of modelled durations of modelled tuning segments, the modelled tuning segments corresponding to modified lengths of the panel tuning segments; and estimate a set-on time for a media set associated with an RPD device based on RPD tuning information and the first and second probability distributions, the RPD tuning information reported from the RPD device, the RPD tuning information indicative of a reported RPD tuning segment during which the RPD device was accessing second media.

Abstract: Disclosed examples determine a duplicated audience size representative of panelists exposed to television media and digital media; determine a panel duplication reach based on the duplicated audience size and a panelist population; determine a did-not-view reach based on a television audience size, a digital audience size, the duplicated audience size, and the panelist population; obtain an overlap multiplier as a ratio of (1) a product of the panel duplication reach and the did-not-view reach and (2) a product of a television panel reach and a digital panel reach; determine a duplication factor for a media item based on a television audience reach, a digital audience reach, and the overlap multiplier; and determine a total audience for the media item based on the television audience reach, the digital audience reach, and the duplication factor.

Abstract: Example methods and apparatus disclosed herein include campaign mapping for total audience measurement. An example apparatus includes processor circuitry to train a machine learning model to determine first and second estimated duplication factors for respective first and second reference media campaigns; and determine, using the machine learning model, third estimated duplication factors for a query media campaign based on total exposure metrics associated with individual ones of media platforms for the query media campaign. The processor circuitry to select one of the first and second reference media campaigns based on a comparison of the third estimated duplication factors with each of the first and second estimated duplication factors; and determine fourth estimated duplication factors for the query media campaign based on (a) the respective first or second estimated duplication factors associated with the selected one of the first and second reference media campaigns and (b) the total exposure metrics.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Example methods and apparatus disclosed herein include campaign mapping for total audience measurement.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Abstract: Disclosed examples determine a duplicated audience size representative of panelists exposed to television media and digital media; determine a panel duplication reach based on the duplicated audience size and a panelist population; determine a did-not-view reach based on a television audience size, a digital audience size, the duplicated audience size, and the panelist population; obtain an overlap multiplier as a ratio of (1) a product of the panel duplication reach and the did-not-view reach and (2) a product of a television panel reach and a digital panel reach; determine a duplication factor for a media item based on a television audience reach, a digital audience reach, and the overlap multiplier; and determine a total audience for the media item based on the television audience reach, the digital audience reach, and the duplication factor.

Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a memory and processor circuitry to execute instructions stored in the memory to: generate a first probability distribution indicative of actual durations of panel tuning segments, the panel tuning segments corresponding to time periods during which panelists were exposed to first media; generate a second probability distribution indicative of modelled durations of modelled tuning segments, the modelled tuning segments corresponding to modified lengths of the panel tuning segments; and estimate a set-on time for a media set associated with an RPD device based on RPD tuning information and the first and second probability distributions, the RPD tuning information reported from the RPD device, the RPD tuning information indicative of a reported RPD tuning segment during which the RPD device was accessing second media.

Abstract: An example metrics manager determines a first audience reach for a television audience, the television audience representative of audience members exposed to a media campaign via television media delivery, determine a second audience reach for a digital audience, the digital audience representative of audience members exposed to the media campaign via digital media delivery. An example deduplicator obtains an overlap multiplier based on the media campaign, the overlap multiplier is a ratio of (1) a product of a panel duplication reach and a did-not-view reach and (2) a product of a television panel reach and a digital panel reach, and determine a duplication factor for the media campaign based on the first audience reach, the second audience reach and the overlap multiplier. An example audience manager determines a total audience for the media campaign based on the first audience reach, the second audience reach and the duplication factor.

Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a distribution generator to: generate a first cumulative probability distribution indicative of actual durations of panel tuning segments; and generate a second cumulative probability distribution indicative of modeled durations of modeled tuning segments, the modeled tuning segments corresponding to modified lengths of the panel tuning segments. The apparatus also includes an RPD tuning information analyzer to analyze RPD tuning information reported from an RPD device. The apparatus further includes a set-on time calculator to estimate a set-on time for a media set associated with the RPD device, the set-on time indicative of a period of time when the media set is powered on, the set-on time estimated based on the RPD tuning information and the first and second cumulative probability distributions.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An apparatus includes a distribution generator to: generate a first cumulative probability distribution indicative of actual durations of panel tuning segments; and generate a second cumulative probability distribution indicative of modeled durations of modeled tuning segments, the modeled tuning segments corresponding to modified lengths of the panel tuning segments. The apparatus also includes an RPD tuning information analyzer to analyze RPD tuning information reported from an RPD device. The apparatus further includes a set-on time calculator to estimate a set-on time for a media set associated with the RPD device, the set-on time indicative of a period of time when the media set is powered on, the set-on time estimated based on the RPD tuning information and the first and second cumulative probability distributions.

Abstract: Methods and apparatus to model on/off states of media presentation devices based on return path data are disclosed. An example method includes generating a modelled tuning segment distribution indicative of modelled durations of modelled tuning segments. The modelled tuning segments is based on panel tuning segments during which panelists were exposed to first media. The example method further includes obtaining return path data (RPD) tuning information reported from an RPD device. The RPD tuning information is indicative of a reported RPD tuning segment during which the RPD device was accessing second media. The example method also includes estimating a set-on time for a media set associated with the RPD device based on the RPD tuning information and the modelled tuning segment distribution. The set-on time is indicative of a period of time when the media set is powered on.