When Less Is More and More Is Less: TV Big Data Measurement, Part 1

Central to these concerns is the data used in decisionmaking from basic counts of ad exposures for real people not botsamp160to the validity of consumer targeting data employedamp160and the methods for integrating these other data sources amp160Now as TV distribution becomes more like digital the opportunities and challenges associated with digital become relevant to the 74 billion TV ad businessAside from these current concerns data accuracy has always been a discussion in the industry amp160With billions of dollars being spent by advertisers in linear TV the data used to plan measureamp160and guarantee needs to be accurateConcern about US TV ratings surfaced as early as 1963 with the Harris Committee Hearings on Broadcast Ratings amp160The report led to the creation of the Media Rating Council MRC which still audits and accredits US audience measurement data to this dayThe difference now is that there are TV measurement data being made available from a multitude of returnpath sources including cable and satellite set top box data ACR data IPTVamp160and OTT what we might term quotTV big dataquot amp160These sources may be connected with consumer data from third party consumer databases or first party data sources enabling alternative ways to plan and transact TV campaigns and assess the effectiveness of advertising amp160The large numbers of observations in some cases tens of millions dwarfs traditional TV measurement panel samples and opens up the possibility of better targeting of ads and more detailed evaluation of the effectiveness of TV budgetsBut bigger isn39t always better amp160TV big data sets have potential gaps and inaccuracies amp160What follows are some questions to ask when it comes to TV big dataWhat technology is measured and what isn39tamp160 In most cases these large data sets have a surprisingly narrow focus returning data from devices that are technically geographicallyamp160and contractually able to provide data amp160This might mean ACR TV sets in homes that have not opted out of data measurement or data from a specific cable operator and within that the boxes that the operator has enabled for return path capabilityThe term quotcensus measurementquot is often used in these cases but the population definition of the census is often a very restrictive and ultimately meaningless one for an advertiser whose marketplace definition goes beyond that narrow population for which the quotcensus measurementquot is being touted amp160For example TV big data coverage bias may be undesirable to a massmarket advertiser if black and Hispanic households are underrepresented amp160Projection and weighting systems can be employed to address bias but these cannot completely make up for systematic exclusions of devices or homes and the accuracy of these solutions can only be properly assessed if a full measurement is available for comparisonWhat is a viewer amp160Most providers of TV big data will talk about viewers when discussing results but the reality is that these data measure device activity not human beings amp160In some cases that device activity may not even result in a picture on a screen eg cable boxes may remain on even when the TV is off and if there is a picture on the screen the data won39t tell you who39s actually watchingWhat metrics are reported and for which reporting categories amp160Are average audiences and ratings projected to defined populations in a consistent way over time amp160What content detail is available and at what level of granularity amp160programcommercialnetworkdaypart detail amp160Is there secondbysecond data for each device or aggregated resultsCan you trust the data amp160The funneling of data through various pipes and middleware providers to the end user means a loss in transparency and can mean a lack of fidelity in results with errors being difficult to detect amp160The extent to which any data provider is open to examination of its processes up to and including auditing and eventually MRC accreditation is a good indicator of the confidence you should have in the dataAn illustration of the opportunities and challenges is given by addressable advertising capabilities amp160Of 118 million TV households in the US there are approximately 70 million households with addressable capabilities source eMarketer Television Update H2 2017Advanced TVs Progress amp160For an advertiser with a national marketing objective an addressable campaign across these 70 million households could reduce the waste associated with conventional linear TV advertising and the data could potentially provide valuable feedback in terms of creative content placement and targeting effectiveness amp160However coordinating such a campaign would currently be very difficultEach addressable provider eg Altice ATT Comcast Cox DirecTV CharterSpectrum Verizon would need to be activated separately with separate data connections a complex and timeconsuming undertaking amp160Consideration would also need to be given to the balance of households without addressable capabilitiesamp160and the availability of inventory for addressable ads amp160At present these types of campaigns are likely to be more narrowly focused typically run as tests with individual MVPDsOver time more homes and more devices will have linear streaming capabilities and when ATSC30 becomes the broadcast standard more addressable gaps will be filled amp160It will be interesting to see how the industry evolvesamp160and how much advertisers can use their influence to make content providers and distributors cooperate to offer unified and comprehensive capabilities and how well personal identity and device activity can be resolved within technical and privacy constraintsClick the social buttons above or below to share this story with your friends and colleaguesThe opinions and points of view expressed in this content are exclusively the views of the author andor subjects and do not necessarily represent the views of MediaVillagecomMyersBizNet Inc management or associated writers

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When Less Is More and More Is Less: TV Big Data Measurement, Part 1

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Pete Doe

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When Less Is More and More Is Less: TV Big Data Measurement, Part 1

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