Abstract: A system and method are disclosed that measures audience engagement with a program based on the time a user spends viewing the program. A program's ability to retain viewers is referred to as the “stickiness” of the program. The viewership for a program is determined by the system and then compared to viewership of various other programs in order to assess the audience retention for the analyzed program as compared to the retention of the other programs. The system calculates a “stickiness index” for the program, which is a numerical representation of the analyzed program's stickiness as compared to the average of the other programs. The system may generate a report including the analyzed data and calculated stickiness index for advertisers, agencies, media sellers, or other parties that are interested in assessing viewership of the analyzed program.

Abstract: A system and method for cleaning television viewing behavior data collected from set top boxes by detecting and correcting various problems that can occur in the viewing data. Three problems that may be detected and corrected by the system include: overflows of memory buffers; inclusion of non-human generated tuning events; and presence of clock offsets. After cleaning the television viewing behavior data, the cleaned data may be used to analyze audience viewing behavior in a manner that achieves a higher degree of accuracy than can be achieved by using uncleaned television viewing behavior data.

Abstract: A system and methods to calculate ratings of television advertisements based on viewing data and to assess the effectiveness of the advertisements. In some embodiments, consumer viewing data is consolidated across a plurality of disparate channels through which content and advertisements are presented to viewers. Some of the channels may provide information directly to the system about which advertisements were presented to viewers. In some embodiments, the system may instead determine whether an advertisement was likely viewed based on scheduling data associated with the presentation of content and advertisements. The system may provide additional algorithms for rating advertisements based on the consolidated information. That is, the system may allow performance of advertisements to be compared against other advertisements across a desired population of viewers. Embodiments may further provide information for a graphical user interface to assess the ratings and results.

Abstract: A method and system for identifying tune data from set top boxes associated with televisions, video monitors, or other video playback devices that are likely powered off. In some embodiments, survival curves are constructed that predict a length of time before a video playback device is powered off after a tuning event. The survival curves are used to predict the likelihood that a video playback device is powered off. Viewership estimates made from tune data reported from set top boxes can be adjusted to take account of the video playback devices that are predicted to be powered off.

Abstract: Various embodiments disclose a system and methods for media content analysis based at least in part upon social media data. In some embodiments, a computer system may identify social media messages corresponding to televised content. For example, following the uploading of a television show (or advertisement) to an Internet website, or transmission across a television network, viewers and non-viewers of the show may begin commenting upon the show. The system may correlate the number of viewers of the show with the social media messages to generate one or more metrics describing relations between the show's viewership and the show's social media effects.

Abstract: A system and method for cleaning television viewing behavior data collected from set top boxes by detecting and correcting various problems that can occur in the viewing data. Three problems that may be detected and corrected by the system include: overflows of memory buffers; inclusion of non-human generated tuning events; and presence of clock offsets. After cleaning the television viewing behavior data, the cleaned data may be used to analyze audience viewing behavior in a manner that achieves a higher degree of accuracy than can be achieved by using uncleaned television viewing behavior data.

Abstract: A computing system is programmed to detect if program content is presented on a channel. A program signature is determined based on set-top box tune data from set-top boxes in a market in which it is known the program content was presented. The program signature can be compared to program signatures from other local markets or from the same market to determine if the same program content was presented. In some embodiments, the program signature represents the number of set-top boxes simultaneously tuned to the channel on which the program content is presented.

Abstract: A system and method that calibrates subject data for which a relationship to a target population is not known, so that the calibrated subject data can more accurately represent the target population. In many cases the calibration will involve the use of a differential weighting scheme applied to the data at the constituent level. The system and method allows the values of the observed variables in the subject data set to be weighted so that their incidence is equivalent to that of a reference population represented by a reference data set, even if the variables used in the reference data set to make estimates for the reference population were not collected or measured for the subject data set.

Abstract: Various systems and methods for generating and augmenting viewership datasets are disclosed. In particular, some embodiments prepare the datasets for further analysis by supplementing missing information based upon available data. The system may organize viewership data from disparate formats into a unified form to facilitate analysis and projection of non-reporting device data. In some embodiments, the projections may scale existing cumulative determinations based on information regarding the presence and character of non-reporting devices in different geographic markets.

Abstract: Various of the disclosed embodiments contemplate television viewing behavior data collected from a plurality of television set top boxes by using aggregation to detect an excess or a deficit in viewership for a group of television set top boxes. In some embodiments, a group of set top boxes can be associated with a particular television service provider, cable television head-end, or data warehouse. Additionally, some embodiments can clean television viewing behavior data by detecting and correcting aberrant viewership in a time series, e.g. based on a weekly or an approximately monthly frequency. In some embodiments, the aberrant viewership can be detected by calculating a minimum expected number of viewers for a day and comparing it to the actual number of households that reported viewers for that day.

Abstract: A system and methods to calculate ratings of television advertisements based on viewing data and to assess the effectiveness of the advertisements. In some embodiments, consumer viewing data is consolidated across a plurality of disparate channels through which content and advertisements are presented to viewers. Some of the channels may provide information directly to the system about which advertisements were presented to viewers. In some embodiments, the system may instead determine whether an advertisement was likely viewed based on scheduling data associated with the presentation of content and advertisements. The system may provide additional algorithms for rating advertisements based on the consolidated information. That is, the system may allow performance of advertisements to be compared against other advertisements across a desired population of viewers. Embodiments may further provide information for a graphical user interface to assess the ratings and results.

Abstract: A system and method to analyze the effectiveness of advertisements of presented content. The advertisements include advertisements for which the behavior desired by the advertiser is to drive a viewer to perform a certain action, such as to watch particular television program content. The system determines if an advertisement is effective by correlating exposure to presented advertisements with the subsequent presentation of content that was promoted in the advertisements. To perform the analysis, the system collects tune data from set top boxes, digital video recorders (DVRs), or other component capable of storing tune data related to the content presented on an associated display component.

Abstract: A system and method for cleaning television viewing behavior data collected from set top boxes by detecting and correcting various problems that can occur in the viewing data. Three problems that may be detected and corrected by the system include: overflows of memory buffers; inclusion of non-human generated tuning events; and presence of clock offsets. After cleaning the television viewing behavior data, the cleaned data may be used to analyze audience viewing behavior in a manner that achieves a higher degree of accuracy than can be achieved by using uncleaned television viewing behavior data.

Abstract: A system and method that calibrates subject data for which a relationship to a target population is not known, so that the calibrated subject data can more accurately represent the target population. In many cases the calibration will involve the use of a differential weighting scheme applied to the data at the constituent level. The system and method allows the values of the observed variables in the subject data set to be weighted so that their incidence is equivalent to that of a reference population represented by a reference data set, even if the variables used in the reference data set to make estimates for the reference population were not collected or measured for the subject data set.

Abstract: A system and method for analyzing the viewing behavior of end users that are viewing video content to determine the likely presence of one or more advertisements being viewed and to assess the viewers who stop viewing during the course of such advertisements. The system periodically or continuously receives tune data reflecting the viewing behavior of end users, analyzes the cumulative viewing behavior reflected by the received tune data, and delivers a report of the analysis to advertisers, agencies, media sellers, or other parties that are interested in measuring the effectiveness of advertisements on end users. The analysis by the system can be done over multiple different types of content-distribution platforms.

Abstract: A system and method are disclosed that measures audience engagement with a program based on the time a user spends viewing the program. A program's ability to retain viewers is referred to as the “stickiness” of the program. The viewership for a program is determined by the system and then compared to viewership of various other programs in order to assess the audience retention for the analyzed program as compared to the retention of the other programs. The system calculates a “stickiness index” for the program, which is a numerical representation of the analyzed program's stickiness as compared to the average of the other programs. The system may generate a report including the analyzed data and calculated stickiness index for advertisers, agencies, media sellers, or other parties that are interested in assessing viewership of the analyzed program.

Abstract: A system and method for cleaning television viewing behavior data collected from set top boxes by detecting and correcting various problems that can occur in the viewing data. Three problems that may be detected and corrected by the system include: overflows of memory buffers; inclusion of non-human generated tuning events; and presence of clock offsets. After cleaning the television viewing behavior data, the cleaned data may be used to analyze audience viewing behavior in a manner that achieves a higher degree of accuracy than can be achieved by using uncleaned television viewing behavior data.

Abstract: A system and method to measure the effectiveness of advertisements. The effectiveness of a particular target portion of an advertising campaign (e.g., related to an advertisement or advertisements appearing on a specific network, time of the day, program, etc.) is determined relative to exposures to other portions of the advertising campaign. To facilitate the measurement, the system constructs an exposure interaction matrix, which allows isolation of the effectiveness of one group of advertisement exposures while controlling for exposures across other groups. For each cell of the matrix, the system computes an index. The index indicates how much the target advertisements influenced the conversion decision, relative to the entire campaign. A plurality of exposure interaction matrices may be determined for a plurality of target portions and compared to one another in order to determine a desired advertising schedule.

Abstract: A method cleans television viewing behavior data collected from a plurality of television set top boxes by using aggregation to detect an excess or a deficit in viewership for a group of television set top boxes. In various aspects, the group of set top boxes may be associated with a particular television service provider, cable television head-end, or data warehouse. Additionally, the method can clean television viewing behavior data by detecting and correcting aberrant viewership in a time series, that is based on a weekly or an approximately monthly frequency. The aberrant viewership can be detected by calculating a minimum expected number of viewers for a day, and comparing it to the actual number of households that reported viewers for that day.

Abstract: A computing system is programmed to detect if program content is presented on a channel. A program signature is determined based on set-top box tune data from set-top boxes in a market in which it is known the program content was presented. The program signature can be compared to program signatures from other local markets or from the same market to determine if the same program content was presented. In some embodiments, the program signature represents the number of set-top boxes simultaneously tuned to the channel on which the program content is presented.