Marketing Analytics: 5 Things Every CMO Should Know

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Marketing Analytics: 5 Things Every CMO Should Know

  1. 1. Marketing Analytics: 5 Things CMOs Should Know Peter Krieg, President and CEO Thursday, June 27, 2013
  2. 2. The Home Stretch 2 weeks, 5 webcasts, improved marketing effectiveness
  3. 3. Series Schedule 1. Transformational Marketing Mix Optimization Using a Virtual Marketplace Presenter: Jeff Maloy, Senior Vice President and Chief Marketing Officer Available On Demand: brighttalk.com/webcast/1336/76329 2. Using a Virtual Marketplace to Evaluate Your Marketing Strategy Presenter: Eric Paquette, Senior Vice President „ Available On Demand: brighttalk.com/webcast/1336/76331 3. Optimizing Your Media Plan for the Bought-Owned-Earned World Presenter: Rolf Olsen, Vice President Available On Demand: brighttalk.com/webcast/1336/76333 4. Leveraging Marketing Investments with Marketing Mix Modeling Presenter: Irina Pessin, Managing Partner, Data2Decisions US Available On Demand: brighttalk.com/webcast/1336/76333 5. Marketing Analytics: 5 Things Every CMO Should Know Date: Thursday, June 27 Time: 1 pm EDT Presenter: Peter Krieg, President and CEO
  4. 4. For a PDF of this presentation and our advertorial on using big data for marketing planning… Email ami.bowen@copernicusmarketing.com
  5. 5. Who am ? Peter Krieg President and CEO Copernicus Marketing Consulting & Research Peter Krieg is a co-founder of Copernicus. With over 30 years of experience as a marketing and research consultant, he is responsible for many of the firm‟s largest accounts and spearheaded the company‟s expansion into Latin America and more recently Dubai, U.A.E. He has given many speeches at professional conferences in the U.S., Europe, Latin America and the U.A.E. and has written numerous articles in marketing and advertising journals and magazines. The topics have included: brand strategy, research methodology, more effective implementation of marketing programs, digital strategy and product/service optimization. He is the co-author of Counterintuitive Marketing: Achieve Great Results Using Uncommon Sense (Free Press, 2000), Market New Products Successfully (Lexington Books, 2006), and Your Gut is Not Smarter Than Your Head (Wiley, 2007). His latest work is a soon-to-be-published paper on the relationship between blogging engagement and cross- category personal influence, a study based on a Copernicus R&D investigation among 800 adult Americans.
  6. 6. The Marketing Analytics Spectrum Simple Correlations A/B Testing Advanced analytics Predictive analytics What I will focus on today
  7. 7. What are CMOs thinking about big data?  More than 70% of CMOs feel underprepared to deal with the data explosion (IBM Global CMO Study)  Less than 40% of CMOs "say they routinely gain insight from their analytics.” (MarketingSherpa)  Only slightly more than 20% claim to be highly effective at uncovering new insights to generate business value (IBM Marketing Exec Survey)
  8. 8. 5 Things Every CMO Should Know 1. Involve analytics team early and often 2. Turn big data into smart data 3. Organize around the customer 4. Take a forward view 5. Visualize it 6. Combine Art and Science
  9. 9. The Biggest Mistake Marketers Make….  “We’re not getting what we need.”  “We need something that will make the biggest difference to our business.”  “We need something that really makes sense of how our marketing works.” Picking the Tool Before Picking the Problem
  10. 10. 1. Involve Analytics Early and Often Starting out thinking about models is like:
  11. 11. “Analytics groups are not involved early enough in the process. We need to get ourselves more integrated up front.” - Mike Vitti COO, Copernicus To AdAge 1. Involve Analytics Early and Often
  12. 12. 1. Involve Analytics Early and Often All analytics projects should begin with a clear understanding of what is overall business strategy and what are the problems/challenges that need to be addressed?
  13. 13. Case in Point: Benefits of the Early Call
  14. 14. The Question of the Hour for CMOs…. How do you get from big data to generating insights that address business goals and problems?
  15. 15. 2. Turn Big Data Into Smart Data The outputs of any analytical tool are only as good as the inputs that go into it.
  16. 16. 2. Turn Big Data Into Smart Data How to turn “big data” into “smart data”?  Answer: 3W’s: When Where Why Volume Velocity Variety 3 V’s Economic Data Environ- mental Data Media Costs POS Data Price/ Promotion Data Competitive Data GPS/RFID Data Survey Data
  17. 17. 2. Turn Big Data Into Smart Data Leverage first party data to fullest extent, supplement with third party data as needed. FIRST BASE FIRST PARTY THIRD BASE THIRD PARTY Your data:  Website data  CRM data  Subscription data More accurate, and less costly Customer understanding Cross-selling and up-selling Owned by others and purchased:  Cookie data  Registration data  Modeled/Inferred data Scale and new audiences Market sizing Customer targeting and acquisition
  18. 18. 2. Turn Big Data Into Smart Data  Know what data matters  Know what data is good/valid  Know the limits of any data – Don‟t be afraid to say (or hear) “I don‟t know exactly”
  19. 19. IF YOU‟RE ON THE WRONG TRAIN, EVERY STOP IS THE WRONG STOP 3. Organize around the customer The “future of marketing,” isn‟t in the accumulation of big data. The future is in organizing it around the customer.
  20. 20. Requirements For Improving ROI All Along the Path To Purchase  Understanding of the customer – WHO? – WHY?  Understanding of the customer’s journey – WHAT? – WHEN? – WHERE?  Understanding of the synergistic effects of different media on customer behavior
  21. 21. 3. Organize around the customer Data is only powerful when organized and structured The consumer—and his/her journey—should be the organizing principle Inspiration Exploration Evaluation Transaction Reflection  Household purchase data  Paid media  Owned media Our Target (Segmentation Study)  Behavioral/ A&W data  Search data  Web data  Price/ Promotion data  Competitive data  Brand Health Tracker  POS Data  Social data  Loyalty card data Path-to-Purchase:
  22. 22. Models can be better informed with your existing customer research  Market Segmentation  Brand Advocates  Shopper Journey  Advertising Tests  Brand Tracking / Drivers Analysis  Creative / Message Tests
  23. 23. Your market segmentation provides a wealth of useful information Happy Families Struggling to Get By Always an Angle Simple & Settled Savvy Sophisticates # of U.S. Adults 38MM 38MM 48MM 32MM 44MM Annual Spend $133 $131 $98 $95 $71 % of Category Spending (Index) 26% (136) 24% (127) 21% (95) 14% (92) 15% (69) Current Share 27% 20% 16% 16% 14% % of Current Opportunity (Index) 37% (195) 22% (107) 19% (71) 10% (63) 10% (45) Different Demographics Different Media Behaviors Different in Needs/Motivations Different Buying Occasions Different Channel / Store Preferences
  24. 24. Map out the Customer Journey  What are the steps?  When are different media / touch points used?  What is sought?  Are there seasonal elements?  Does advertising reach people with the right message during the right moments and mindset?
  25. 25. Understanding the synergistic effects of B/O/E media 25
  26. 26. 4. Take a forward view Most analytics is backward-looking  Models the future based on the past We need tools/models that are more forward-looking In today‟s dynamic marketplace, this is no longer sufficient.
  27. 27. Experimentation is only an opportunity if you consider and test many different options “Big testing is often only valid if the customer experiences in which it’s executed are good. If you run a split-test of two concepts, say offer A (a price emphasis) and offer B (a quality emphasis), testing a hypothesis of which will motivate a particular customer segment more — but both experiences are kind of crappy — then the results of your test are useless.” Scott Brinker, Chief Marketing Technologist Blog
  28. 28.  A virtual market, based on behavioral “rules”  Allows us to simulate how consumers may react to: – Marketing and Media – Each other (networking effect) – Other “environmental” variables  Not bound by historical results 4. Take a forward view Agent-Based Modeling and Simulation (ABMS): Bought Owned Earned
  29. 29. 4. Take a forward view Allow us to test and evaluate new, unknown, experimental, and “stretch” marketing plans: What if… Go after young dudes (instead of their moms)? Double our digital budget? Dramatically improve “customer service”? Competitor loses their mind? The warm weather never gets here?
  30. 30. 5. Visualize It Within the data explosion, findings need to come alive in powerful visualization.  Word clouds  Info-graphics  Graphical User Interface (GUI) To:  Bar charts  Pie charts  Line graphs From:
  31. 31. 5. Visualize It Interactive dashboards allow for “real-time” accessibility—and visualization—of data at your fingertips.
  32. 32. 6. Combine the Art and Science “All models are wrong, but some are useful” George E. P. Box
  33. 33. 6. Combine the Art and Science “Now you have a marketing analytics shop and a market research shop. All of these groups are critical pieces to the puzzle. But they may not have worked together in the way you need them to in order to get the right decisions.” Matthew Jauchius CMO, Nationwide Insurance
  34. 34. 6. Combine the Art and Science Need to move from: Marketing Data to Marketing Intelligence to Marketing Decisions  Takes a diverse, talented team The What So What Now What Data and reporting Consumer Understanding and Insights Modeling & Simulation Marketing and Sales
  35. 35. 5 Things Every CMO Should Know 1. Involve analytics team early and often 2. Turn big data into smart data 3. Organize around the customer 4. Take a forward view 5. Visualize it 6. Combine Art and Science
  36. 36. For a PDF of this presentation and our advertorial on using big data for marketing planning… Email ami.bowen@copernicusmarketing.com
  37. 37. PETER KRIEG, President & CEO (203) 831-2373 peter.krieg@copernicusmarketing.com

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