4A’s Transformation 2013 - March 12 - Mobilewalla - Dr. Anindya Datta
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4A’s Transformation 2013 - March 12 - Mobilewalla - Dr. Anindya Datta

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Executive Summary of Original Research Conducted by Flurry, Machinima, and comScore, and Mobilewalla ...

Executive Summary of Original Research Conducted by Flurry, Machinima, and comScore, and Mobilewalla

Long Ellis, VP Direct Media, Flurry
Cassandra Nuttall, VP, Trade Marketing, Machinima
Dr. Anindya Datta, CEO, Mobilewalla
Moderated by: Bob DeSena, CEO, Engagement Marketing

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  • The Churn in the TV shows is also because of one time broadcasts like The Presidential Debate; Grammy’s, Oscars etcAdd timeline…Panels don’t work to come at the end…Add source
  • Step 1 and Step 3 – ground break big data techniques – add!

Transcript

  • 1. Why is audience measurement difficult inmobile apps? Anindya Datta, CEO Mobilewalla
  • 2. Mobilewalla• Seattle-based, venture funded company founded and run by leaders in the big-data and advertising technology space• Pioneering audience measurement in mobile apps• Applying ground breaking data science techniques to the largest volumetric database of mobile app market data
  • 3. Traditional audience measurement relies on panels! Instrument “Gateway Devices” (Cable Box, Browser) to record user behavior Extrapolation to wider audience! Panel limitations well-known Ireland – Total TV Universe 4,205,000  Not enough people on the panels  Panels not harmonised  Doesn’t reflect all populations & lifestyles Audience measurement panel size 2500 (0.06%!) *Source: Nielsen Television Audience Measurement 2012 RTE Television media Sales - Oct 2012
  • 4. Had to throw in my favorite Extrapolation cartoon Source: xkdc.com
  • 5. Panels & Popularity Persistence Fundamental to panel driven measurement Idea of popularity persistence Large pool 99 – 1 rule “small” set of of options popular choices Objects popular today  popular 30-60-90 days from today • Panel can be assumed to eventually gravitate towards the persistent popular set
  • 6. App Popularities do not Persist 0 day 30 day 90 day 0 day 30 day 90 day Majority of churn due to one timespecial broadcasts like the PresidentialDebates, Oscar’s,17 Grammy’s & 13 Sporting 10 1 20 55 Events 0 App Popularities are highly5 transient! Regular broadcast TV shows hardly demonstrate any Panels don’t work for Apps popularity churn ChurnTop 20 US TV 30 day Churn 90 day Top 100 30 day Churn 90 day Churn programs 15% 35% Apps 45% 85% Top 20 US TV Progams over 90 days Top 100 Apps over 90 days Source: Programs - Nielsen Television (TV) Ratings for Network Primetime Series Apps - mobilewalla
  • 7. Volatility – Ranks! 18-24 Jun 2012 16-22 July 2012 13-19 Aug 2012 17-23 Sep 2012 15-22 Oct 2012 12-18 Nov 2012 17-23 Dec 2012 050100150200 TV Programs250300350400 The Big Bang Theory 60 Minutes Two and a Half Men NCIS* 0 50 100 150 200 250 300 350 Apps 400 Link The Gugl (Games) MailBox (Overall) Draw Something Free (Overall) Go To Meeting (Business) Source: Programs - Nielsen Television (TV) Ratings for Network Primetime Series Apps – mobilewalla; *Note: NCIS was not aired in the week of 15-22 Oct
  • 8. Mobilewalla Pioneers Audience Measurement for Mobile Apps Audience data delivered in two ways Rule Based Refinement  Given an App 3 Step  Output indexed audience Approach demographics (like Quantcast)  Given a target demographic Reference Based Estimation  Output apps that provide reach into that demographic Ground breaking big data techniques • Ability to cross-referenceAudience Based Clustering audience with popularity • Provide data in real-time Use Cases Rapid Adoption in the Mobile Ad ● Campaign targeting Industry ● Supply enrichment in RTBs ● Publisher Prospecting
  • 9. In Summary• One of the greatest impediments towards the widespread adoption of advertising in mobile has been the unavailability of reliable audience data for apps• It turns out that audience measurement in mobile is difficult – The inapplicability of traditional panel based measurement techniques is a major reason• Mobilewalla has invented techniques, based on ground- breaking big-data science, to reliably estimate app audiences and is powering targeted campaigns as well as supply enrichment at major ad technology companies