XCMO 2013: Online & Offline Analytics Convergence (Peanut Butter & Chocolate)


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For most brands, digital marketing lives in its own world, yet we know there are a multitude of offline marketing and external factors than impact results. Adometry's Tim McDonough provides a road-map and examples of bringing media mix modeling together with digital marketing attribution to better understand real results.

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XCMO 2013: Online & Offline Analytics Convergence (Peanut Butter & Chocolate)

  1. 1. Peanut Butter & Chocolate Online & Offline Analytics Convergence October 10, 2013 #xcmo13
  2. 2. Marketing Research #xcmo13
  3. 3. Marketing Research How we got here › For more than a century marketing research had been done mainly with surveys – 1879 - N. W. Ayer conducts custom research in an attempt to win the advertising business of Nichols-Shepard Co., a manufacturer of agricultural machinery. – 1911 can be considered the year marketing research becomes an industry. That year, J. George Frederick leaves his position as editor of Printer’s Ink to begin his research company, the Business Bourse. – Also in 1911, Kellogg's ad manager, R. O. Eastman creates the Association of National Advertisers which is now known as the Association of National Advertising Managers. The group’s first project is a postcard questionnaire to determine magazine readership. #xcmo13
  4. 4. Marketing Research How we got here – 1915, J. Walter Thompson establishes a Research Department – 1922, Dr. Daniel Starch tests reader recognition levels of magazine and newspaper advertisements and editorial content. – 1923, Dr. George Gallup begins measuring advertising readership. – Also in 1923, Arthur Charles Nielsen founds the ACNielsen company to conduct marketing research. › 1942, Nielsen inaugurates a National Radio Index for broadcasters and advertisers. › 1950, Nielsen begins their television ratings service. – The 1960s usher in the era of qualitative focus groups and sociologist Daniel Yankelovich assembles MONITOR, a large longitudinal panel that has been tracked continuously since its inception. #xcmo13
  5. 5. Marketing Research How we got here – In the 1970s computers collect and store historically massive amounts of data and the discipline of database analytics emerges. – The 1980s bring behavioral psychology to the arena of brand research and cable TV revolutionizes broadcast media. – In the 1990s trends in in-market tracking include a greater focus on the multimedia nature of entire advertising campaigns. CRM emerges. – The 21st century opens with a decade of global reach with the dawn of the Internet age. The dichotomy of digital and traditional advertising emerges. – Now in the second decade of the century attention returns to the complete marketing ecology. Online and offline brand engagement blurs into a continuum. – 2007, JWT establishes its Marketing Science practice in Dallas. Recruiters from the traditional full service agencies are all now seeking “marketing scientists”. #xcmo13
  6. 6. State of the Advertising Industry #xcmo13
  7. 7. US Advertising Media Market Sizes 2012 90 2017 81.6 80 70 69.4 63.8 $Billion 60 50 40 30 20 10 36.6 22.8 18.4 16.1 17.3 16.4 15.2 14.1 11.9 7.5 9.6 0.8 1.5 0.7 0.9 0 Source: PricewaterhouseCoopers #xcmo13
  8. 8. US Advertising Media Market Share 2012 2017 40.0% 35.7%36.1% 35.0% 30.7% 30.0% 25.0% 20.5% 20.0% 15.0% 12.8% 10.0% 8.1% 9.0% 7.7% 9.2% 6.7% 7.9% 5.3% 5.0% 4.2% 4.3% 0.4% 0.7% 0.4% 0.4% Video games Theaters 0.0% TV Internet Newspaper Radio Magazine B2B OOH Source: PricewaterhouseCoopers #xcmo13
  9. 9. Agency Revenues 18 16 15.6 14.3 14 $Billion 12 10 7.7 8 6.7 6 4 3.1 1.8 2 1.2 0 WPP (London) Omnicom (NY) Publicis (Paris) Interpublic (NY) Dentsu (Tokyo) Havas (Paris) Hakuhodo (Tokyo) Source: Rediff #xcmo13
  10. 10. Marketing/Advertising Agencies It’s a jungle out there › Full service agencies › Creative agencies › Specialized agencies – – – JWT Demographic segments Industry specific Single client agencies › Digital agencies – – – Web and social property design SEO Social › Research agencies – – – – Primary research (surveys & focus groups) Database Online analytics Marketing analytics › Media buyers #xcmo13
  11. 11. Digital Divide #xcmo13
  12. 12. Digital Divide Meet in the middle › The Internet has enabled us to track individual consumer behavior from first ad exposure to conversion and has created opportunities to engage consumers with brands interactively as never before. › This has spawned a new category of research agencies devoted to analyzing the start to end online journey. › Until recently, this behavior was described and modeled as something independent of exposure to all other marketing treatments. › Clients have pushed back with business questions about how the conversion behavior is influenced by the marketing ecology as a whole. #xcmo13
  13. 13. CMO Wish List #xcmo13
  14. 14. Digital Divide 1+1=3 › Agencies have responded to this pressure. › Traditional marketing agencies are in a mad scramble to acquire or organically grow digital expertise. › Digital agencies are doing the same with traditional marketing. #xcmo13
  15. 15. The Digital Agency Challenge N ˆ S ( 1 ,  2 )   ( yi  y i )2 i 1 N   ( yi i 1  1   2 x )2 #xcmo13
  16. 16. The Traditional Agency Challenge To increase his chances of getting a job with a big brand agency with his degree in Advertising, Arnold enrolls in Machine Learning 101. #xcmo13
  17. 17. Playing Together #xcmo13
  18. 18. Holistic Model Solution #xcmo13
  19. 19. Channel Level Overlay #xcmo13
  20. 20. Symbiosis Two-way information flow › The key to success in connecting top-down aggregate data models that operate at the channel level and user-level data models is to use information from each to augment the other. › Top to bottom – – Top-down aggregate econometric models provide the view of the ecology at the channel level. This information can be used to scale the results of bottom-up models to the rest of the channels to provide absolute attribution to the user-level aggregates. › Bottom to top – – Bottom-up machine learning processes can provide noise reduction to the econometric models in the form of refined variable specifications. This noise reduction enhances the discrimination power of all channel variables in the model. #xcmo13
  21. 21. Econometric Models are Here to Stay Long history of success › Since the advent of the computer in the late 1950s econometrics has transformed the business landscape. › Many techniques dating back to the dawn of the applied economics age are still successfully employed in today’s markets. – Single equation models – Simultaneous equation models – Time-series models › Lag models › Vector autoregressive (VAR) models › ARIMA with transfer functions › The machine learning community needs to become comfortable with their new colleagues who come to them from the social sciences. #xcmo13
  22. 22. Artificial Intelligence Short but solid history of success › Machine learning is a mature discipline. › Supervised and unsupervised data mining and modeling techniques have proved their worth. › Social scientists need to learn how to become comfortable with their new computer science colleagues. #xcmo13
  23. 23. Who can say no? #xcmo13