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eMarketer Webinar: Making Attribution Work in the Age of Big Data

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eMarketer Webinar: Making Attribution Work in the Age of Big Data

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There are a number of challenges keeping marketers from taking a more holistic, cross-platform approach to attribution, and big data is the biggest. Topics in this webinar include: What approaches are marketers taking to attribution? How are marketers organizing their data to facilitate attribution? What can marketers do to get closer to a single customer view? How are some marketers putting the pieces together to gain a more cross-platform picture?

There are a number of challenges keeping marketers from taking a more holistic, cross-platform approach to attribution, and big data is the biggest. Topics in this webinar include: What approaches are marketers taking to attribution? How are marketers organizing their data to facilitate attribution? What can marketers do to get closer to a single customer view? How are some marketers putting the pieces together to gain a more cross-platform picture?

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eMarketer Webinar: Making Attribution Work in the Age of Big Data

  1. 1. © 2015 eMarketer Inc. Made possible by Making Attribution Work in the Age of Big Data Lauren T. Fisher Analyst October 22, 2015
  2. 2. © 2015 eMarketer Inc. Agenda  Why attribution: The challenges created by big data  The current state of attribution  The challenges of moving to a more cross-platform approach  Examples for dealing with today’s shortcomings
  3. 3. © 2015 eMarketer Inc. What is attribution?  A method of assigning credit to a particular marketing- or advertising-driven action or other brand-imposed touchpoint Company Level Is my advertising/marketing successful? Department Level Was this campaign successful? Team Level Was this tactic successful?
  4. 4. © 2015 eMarketer Inc. Big data is a top attribution challenge, but it’s not the only one
  5. 5. © 2015 eMarketer Inc. Attribution is the simple answer to big data woes, but its implementation is anything but “The need for cross-platform attribution is completely clear, but also unbelievably complex at the same time. Everybody sees the potential power of data to understand the contribution of every device to an ultimate action. But understanding how to track all the data in a truly holistic way is a whole other ballgame.” —Cindy Gustafson, Managing Director, Invention Studio, Mindshare North America
  6. 6. © 2015 eMarketer Inc. Attribution Today
  7. 7. © 2015 eMarketer Inc. Given the confusion around attribution, there’s little alignment on which approach to attribution to take
  8. 8. © 2015 eMarketer Inc. But by 2017, half of all US digital marketers will transition to multitouch approaches
  9. 9. © 2015 eMarketer Inc. Moving to a multitouch model is a must to see the interplay between channels and tactics  Most multitouch models are built using either a top-down or bottom-up approach
  10. 10. © 2015 eMarketer Inc. Two distinct attribution approaches: Top Down  Branding, traditional media (print, TV, etc.)  Econometrics, marketing mix modeling  Uses GRPs/impressions, spend, sales data, external data to model attribution  Budget allocation and media planning Bottom Up  Native to digital  Path analysis  Uses cookies and other web data to analyze actual activity  Optimization, performance
  11. 11. © 2015 eMarketer Inc. To answer the ultimate question, most acknowledge a blend of both is required Company Level Is my advertising/marketing successful? Department Level Was this campaign successful? Team Level Was this tactic successful?
  12. 12. © 2015 eMarketer Inc. But combining top-down and bottom-up approaches isn’t a simple matching game “Organizations just have too many systems in place. Attribution is still very technical and requires too many people and too many hands in the pot. I think that’s one of the reasons the top-down and bottom-up approaches have yet to meet in the middle somewhere elegant.” —Aaron McLean, Partner at Stuzo
  13. 13. © 2015 eMarketer Inc. The same big data challenges that demand attribution are the ones that hinder it  Accounting for all the disparate data sets, channels and reports  Arriving at a single audience view (universal identifier)  Reaping actionable insights from the data
  14. 14. © 2015 eMarketer Inc. Challenge #1: Organizing Disparate Data Sets
  15. 15. © 2015 eMarketer Inc. Identifying and gaining access to all the necessary data can be an onerous task
  16. 16. © 2015 eMarketer Inc. Making sense of that data can cause even more frustration
  17. 17. © 2015 eMarketer Inc. What companies need is a single receptacle for collecting, storing and normalizing all that data  Today, one of the most common solutions is a data management platform (DMP)
  18. 18. © 2015 eMarketer Inc. The utility of a DMP extends well beyond organizing and normalizing data
  19. 19. © 2015 eMarketer Inc. Challenge #2: Lack of a Universal Identifier
  20. 20. © 2015 eMarketer Inc. Attribution can be done without identity matching, but bottom-up models really demand it “Yes, you can look at some correlations and make some assumptions. But if you don’t know it’s all one consumer, the data starts to degrade in usefulness pretty quickly because you’re only attributing on a portion of someone’s daily life, not the entirety of it.” —Nick Jordan, SVP, Global Strategy, Tapad
  21. 21. © 2015 eMarketer Inc. But so few have that kind of insight into their data
  22. 22. © 2015 eMarketer Inc. Furthermore, obtaining a single, universal view of one’s audience and data is hardly a standardized practice
  23. 23. © 2015 eMarketer Inc. Most companies today use one or both of the following identifying methods:  Deterministic identification  Probabilistic identification
  24. 24. © 2015 eMarketer Inc. Deterministic Identification  How it works: Relies on known-user information to recognize, with near-certain confidence, an individual on each of his or her internet-connected devices.  Examples of data used: Anonymized login data, CRM-level data, email address or customer ID.  Companies taking a deterministic approach: Facebook, Google, AOL, Amazon.com, The Weather Company, eBay, etc.
  25. 25. © 2015 eMarketer Inc. Probabilistic Identification  How it works: Uses a mix of publicly available ad-serving data to assess the statistical probability that a specific device belongs to a particular individual.  Examples of data used: IP address, browser version, operating system data, device type, browsing behavior, content consumption patterns, location-based data and time of day.
  26. 26. © 2015 eMarketer Inc. Example: OEM uses DMP to tie digital influence back to car dealership sales  The goal: To understand how a digital advertising campaign is driving actual sales at the dealership  Data in: website activity, search, social, email, display, mobile, cross-device IDs, third-party data, dealership data  The result: Ability to tie dealership sales back to digital touchpoints (cross-device) to find influence of each exposure and channel on the sale  Added benefit: Improved customer service experience at dealer; knowledge of channel influence is used to optimize customer experience
  27. 27. © 2015 eMarketer Inc. Challenge #3: Gaining More Real-Time Insights
  28. 28. © 2015 eMarketer Inc. Looking ahead, it’s not just about attributing, but taking more real-time action on that info
  29. 29. © 2015 eMarketer Inc. The real aim of attribution is to move from something like this: To this: Company Level Is my advertising/marketing successful? Department Level Was this campaign successful? Team Level Was this tactic successful? Company Level Is my advertising/marketing successful? Department Level Was this campaign successful? Team Level Was this tactic successful?
  30. 30. © 2015 eMarketer Inc. The shift to more real-time use of attribution will continue, though it will never be complete “It’s unrealistic to expect 100% of all channels will be optimized in real time.” —Allegra Kadet, Managing Director, neo@Ogilvy
  31. 31. © 2015 eMarketer Inc. Example: Taking a more “real time” approach to TV advertising to drive in-store sales  The goal: Mindshare working with national advertiser looking to drive in-store sales in an eight-week window  Data in: Marketing and advertising data (digital, traditional, etc.), in-store purchase data, competitive data  Model used: Primarily top down (marketing mix model) enhanced with digital and competitive data  Benefits of this approach: Ability to optimize in near real time, even TV
  32. 32. © 2015 eMarketer Inc. Key Takeaways:  Big data is causing big problems for companies tracking advertising and marketing success  Attribution is the answer, but transitioning to a holistic approach is not without difficulties  DMPs are critical to organizing and normalizing data  Gaining a single customer view is critical for a bottom-up approach, but it’s still a work in progress  Looking ahead, attribution will be just as much about influencing success as it will be about measuring it
  33. 33. NEEDS Leverage & own your data to market with precision Bridge online & offline worlds and personalize your dialogue Analyze & optimize across channels and devices SOLUTIONS Onboarding Market Analytics & Segmentation Targeting Measurement Customer Interaction Management Attribution NEUSTAR’S INTEGRATED MARKETING SUITE HELPS YOU MEASURE WITH PRECISION ACROSS CHANNELS & DEVICES Copyright © 2015 Neustar, Inc. All Rights Reserved NEUSTAR IDENTITY Scale Depth Accuracy
  34. 34. © 2015 eMarketer Inc. Learn more about digital marketing with an eMarketer corporate subscription Around 200 eMarketer reports are published each year. Here are some recent reports you may be interested in: Q&A Session Made possible by You will receive an email tomorrow with a link to view the deck and webinar recording. To learn more: www.emarketer.com/products 800-405-0844 or webinars@emarketer.com Lauren T. Fisher Cross-Platform Attribution: Overcoming Big Data Challenges  Cross-Platform Attribution 2015: Device Identification, Big Data Pose Continued Challenges  The Mobile Attribution Gap: Five Missing Links in Mobile That Makes Attribution Harder  The State of US Digital Advertising 2015: Mobile Trumps Desktop, People Trump Devices  Digital Display Advertising: Nine Things to Know for 2015  Cross-Device Targeting: Success Hinges on Device Identification Methods

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