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Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
Mindshare at DES: Programmatic: It's Not Really About Cheap Media
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Mindshare at DES: Programmatic: It's Not Really About Cheap Media

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  • 1. Perspectives on Big Data Digiday Exchange Summit The New Programmatic Advertising Economy Austin, September 19, 2013
  • 2. This document is confidential and proprietary to Mindshare. Do not distribute without permission.2 Source: Gartner By 2017, CMOs will spend more on technology then their counterpart CIOs
  • 3. This document is confidential and proprietary to Mindshare. Do not distribute without permission. A Few Observations 1. Programmatic and even Big Data are just ubiquitous industry terms. (What about DSP and DMP?) 2. Programmatic is not really about buying cheap media Regardless that 20% of US Display Spending will be Automated 3. Big Data has the potential to strategically solve complex problems driving actionable marketing and business intelligence to improve both efficiency and effectiveness 4. Big Data is more about connecting structured and unstructured data not about volume Zeta bytes or petabytes 3
  • 4. This document is confidential and proprietary to Mindshare. Do not distribute without permission. A Few Observations 1. Attribution of Big Data is driven by:  Variety : normalizing intelligent connections between structured and unstructured data types and sources  Velocity: Speed of Real-Time-Decisioning (addressing adaptive nature and responsiveness of data)  Volume : not about volume of data, but the right data 4
  • 5. Requires New Approach, Talent, Structures, Algorithms and Skill Sets Old Marketing New Marketing This document is confidential and proprietary to Mindshare. Do not distribute without permission.5
  • 6. Big Data Terroir 6 Identify Predictive Patterns Consumer as Patient Universe Surgical/Forensic Approach to Targeting Across all Media Connecting the Right Structured and Unstructured Data Sets This document is confidential and proprietary to Mindshare. Do not distribute without permission.
  • 7. It’s About Active Discovery and Metadata Actionable Insights come in all sizes (Sparks and Fuses) 7 DMP/Media Partners Predictive algorithms Dynamic/Fractional Optimizations This document is confidential and proprietary to Mindshare. Do not distribute without permission.
  • 8.  A flexible approach in which marketers respond quickly to their environment to align consumer and brand goals and maximize return on brand equity.  Achieved through the integrated use of fast- and slow-moving data sources to drive actionable insights to adapt product, pricing, distribution, and advertising. This document is confidential and proprietary to Mindshare. Do not distribute without permission.8
  • 9. How Marketers Are Using Big Data Netflix 9  Netflix used data to retain customers and has reduced churn to under 4%  Netflix tracks what customers watch, search, their ratings, time of day, day of week and device(s)  75% of viewer activity is driven by their personalization algorithm This document is confidential and proprietary to Mindshare. Do not distribute without permission.
  • 10. This document is confidential and proprietary to Mindshare. Do not distribute without permission. How Marketers Are Using Big Data 10  Target statistician Andrew Pole ran test after test, analyzing the data, and before long some useful patterns emerged:  Women on the baby registry were buying larger quantities of unscented lotion around the beginning of their second trimester.  In the first 20 weeks, pregnant women loaded up on supplements like calcium, magnesium and zinc.  Many shoppers purchase soap and cotton balls, but when someone suddenly starts buying lots of scent-free soap and extra-big bags of cotton balls, hand sanitizers and washcloths, it signals they could be getting close to their delivery date. Target assigns every customer a Guest ID number, tied to their credit card, name, or email address with a history of everything they’ve bought and any demo information
  • 11. This document is confidential and proprietary to Mindshare. Do not distribute without permission. Google Flu Tracker Crowd Sourcing Data 11  Google developed an predictive algorithm based on search trend data which was about two weeks faster than traditional CDC methods of tracking flu  This crowd source data enables CDC to be more responsive to distribution priorities of flu vaccines outbreak on a national and state level  The math works like this: people’s location + flu- related search queries on Google + some really smart algorithms = the number of people with the flu in the United States.  However the algorithm needed to be modified based on general interest and media which skewed data  Lyn Finelli, head of the CDC’s Influenza Surveillance and Outbreak Response Team, feels that such crowdsourcing techniques continue to evolve and show promise with other applications Flu Near You and GrippeNet.fr
  • 12. This document is confidential and proprietary to Mindshare. Do not distribute without permission. How Twitter is Using Big Data Social TV: Driving new Advertising Opportunities  Twitter acquired Bluefin and Trendrr both research companies focused on social TV data analytics and measuring Tweets Per Minutes (TPM).  Miley Cyrus’ performance at recent MTV VMAs generated over 300,000 TPM  If you tweet about a show while it’s airing on TV, chances are that you’re also seeing the ads  Media opportunity to target sponsored tweets to create digital extensions to the ads on TV 12 95% of the public social conversation around TV happens on Twitter.
  • 13. This document is confidential and proprietary to Mindshare. Do not distribute without permission. How Agencies Are Using Big Data In-view Attribution  Junior data analyst at Mindshare was working on some attribution research almost 3-years ago and discussed the concept of in-view attribution.  Mindshare contacted Adsafe and discussed creating the product.  Mindshare ran the first alpha test  Following this trend: comScore, DoubleClick, DoubleVerify, Moat, MediaMind 13
  • 14. This document is confidential and proprietary to Mindshare. Do not distribute without permission. FB Sources to Drive New Levels of Efficiencies and Opportunities How Agencies Are Using New Exchange Inventory 14 1. Beta test for FBX produced over 20% increase in conversion rates 2. FB API Partners identified other affinities by “Serial Likers”. What are the other brands categories that your target audience also “Like”.  This drove a series of affinity tests that demonstrated positive results Creating advanced hyper-targeted knowledge bases  Actively optimize results and identify pattern changes including scale and “Sustainability” over time
  • 15. 15 Sustainability  Most case studies reflect performance driven achievements, but are those results sustainable?
  • 16. Sustainability: Programmatic Challenges and Opportunities Requiring New Data Driven and Analytical Approaches 16 1. Demand for RTB inventory has greatly accelerated across all vertical including Automotive, Financial Services, CPG …  Project Higher media cost (more advertisers are bidding for same/similar inventory) What worked yesterday is not a guarantee of success tomorrow  “Complacency just doesn't work“ 3. Test, Test, Test: leveraging big data, small data, but  “Fail smart and fail quickly“  Apply existing learnings to testing new and re-explore challenged opportunities This document is confidential and proprietary to Mindshare. Do not distribute without permission.
  • 17. Sustainability: New Challenges and Opportunities 17 4. Be relentless about solving problems  Keep trying different approaches 5. Focus on new opportunities to leverage Clients’ first –party data 6. Re-targeting is overused and delivers limited scale This document is confidential and proprietary to Mindshare. Do not distribute without permission.
  • 18. Perspectives on Big Data Brian M. Decker Managing Director, Digital Client Leadership, Mindshare GroupM Sherpa Brian.decker@mindshareworld.com Twitter: briandecker6 18 This document is confidential and proprietary to Mindshare. Do not distribute without permission.
  • 19. 01110100011010000110000 10110111001101011001000 00011110010110111101110 1010000110100001010 (Thank you) This document is confidential and proprietary to Mindshare. Do not distribute without permission.

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