ARF Releases First DASH Study to Aid Big Data Audience Modelers

DASH stands for Device and Account Sharing The plan is to conduct DASH at least twice a year as the market structure continues to rapidly evolve away from analog to fully digital A study of the universe based on a probability sample and conducted under ARF supervision by NORC at the University of Chicago itamp8217s the highest quality level achievable for a survey ARF plans to seek MRC Accreditation The sample size of this first wave is 10452 adults and 410 teens 1317 The response rate was 12Seven companies are currently subscribing 605 Videoamp Innovid Experian Verizon Neustar and NPD Itamp8217s logical to expect that others who seek to compete with Nielsen also take advantage of this costeffective way of improving their own quality Nielsen of course gathers such information from its 100000person national peoplemeter probability sample including minutebyminute viewing by specific person device and room type using measurement rather than modeling Nielsen response rate is now about 30When I first developed settopbox data to research grade in the 3990s none of the problems that exist today existed then There was not mobile device sharing because there were very few mobile devices capable of receiving video There were no eCom subscriptions or streaming subscriptions When a settop box is hooked to a Connected TV a Smart TV or one that is enabled by a Roku or other such device and the viewer takes off into the internet to watch something the set top box acts as if the viewer is still watching the last channel it watched on its settop box Nielsen is able to see that and credit properly within the panel and when it uses big data it uses AI methods to inform the big data based on the quottellsquot it finds within the panel signals in big data associated with the switchover to internetNow the analytics companies aggregating big data on audiences are able by using DASH to create models which conform to known reality patterns that significantly affect the accuracy of raw big data These challenges as I say did not exist at the dawn of STB data but they exist now for STB data and for Smart TV dataTo give you an idea of the size of these problems ARF has put out a General Market Report of the first DASH study wave which is pretty much required reading by anyone who wishes to stay up on the vicissitudes of audience measurement Letamp8217s take a look at some of the findingsIn the report ARF also quotes other pertinent recent research such as a Truthset finding that in a recent big data set they scrubbed quotthe accuracy of education level was only 33 while pet ownership was 92quotThe rest of these stats from DASH itselfYesterday viewership of video on any nonTV device was around 50 for 1834 but only about 20 for 55The percent who share a nonTVset device with another household member is over 40 for NonHispanic and nearly 50 for Hispanic This means that any measured ad event involving such a device cannot be assumed to be making an impression on the main user of that device To whom then should it be credited probabilistically if you donamp8217t have a peoplemeter panel is the question that DASH answersAbout 13 share their Disney account with friends in other households and around 32 share Disney with relatives in other households The stats are similar for other streamers and DASH reports a number of them broken out individually for use in modelingIn order to provide parameters for modeling of coviewing the DASH General Market Report shows a grid of time of day by household size indicating how much coviewing is going on in each cell which the full DASH service granularizes by demographic groups and geographies This reflects a yesterday recall questionnaire Of the services studied Disney has highest coviewing in 4person households accounting for half of yesterday viewers of that serviceBy modeling using DASH a company can prove its model is working in the dimensions locked in as DASH parameters This does not guarantee that the programbyprogram audiences are all correct but it increases the probability of proximity to the truthItamp8217s interesting that todayamp8217s audience measurement replacements for Next Century Media and TRA consider themselves modeling companies as does the ARF I always considered my companies measurement companies and used a trivial amount of modeling where Experian demographics were missing in fewer than 8 of the sample Modeling dilutes measurement and so my preference is to use it as sparingly as possible However modeling is a must if one is using only big data and wishes to attribute impressions to human beings rather than to devices This is probably the bedrock upon which advertisers worldwide decided that panels and big data must always be used together in the World Federation of AdvertisersAssociation of National Advertisers requirements documents issued in 2020Click the social buttons to share this content 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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ARF Releases First DASH Study to Aid Big Data Audience Modelers

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