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BBDO Connect Big Data

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Big data has been hyped so heavily that CMO’s are expecting it to be ‘the’ miracle solution in today’s complex marketing environment. However, what we’re actually seeing, is that most companies are already struggling with the small amount of data they already have accumulated. The trouble is most obvious on these three levels: companies don’t know how to manage the data, companies don’t know how to analyze the data so as to yield insights, companies don’t know how to act upon the new insights. Of course technology is needed. But even more so, a cultural shift in how CMO’s run their daily marketing operations is definitely required. The good news is that, once CMO’s have accomplished this cultural change, they usually don’t go back. Because they realize they now have a huge competitive advantage. Now, those forward-thinking CMO’s are able to use customer data to their advantage by delivering more targeted and relevant messages to people. During this session, you will discover how to embrace the power of data and turn it into gold for your company.

Published in: Data & Analytics, Marketing
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BBDO Connect Big Data

  1. Wifi: LivingTomorrow PW: #bbdoconnect
  2. +
  3. Tim Nagels, Business Lead Microsoft Dynamics
  4. Franky Willekens, Head of Data Analytics BBDO
  5. Forget about big data. Think big about any data.
  6. October 2012: Franky goes to Las Vegas
  7. Big Data. Customer Engagement. Marketing Accountability. DMA2012 Brings It All Together.
  8. Survey participants DMA2012
  9. 91% wants to 34% is able to
  10. What is the level of data maturity DATA in your company?
  11. The Data Maturity Stairway I consolidate customer data into one customer database I capture customer data across different touch points I deliver customized interactions at point of impact across touch points I know what type of offer, channel and time is best for different customer segments I analyze historical customer data (purchases, interactions, motivations) I uncover hidden patterns in customer data to predict what they are likely to do next Gather Data Aggregate Data Customer Insight Targeted Communications Predictive Modeling Real-time contextual interactions
  12. Today’s story
  13. Relevance + Utility =
  14. Customer Experience Leaders +43.0% S&P 500 Index +14.5% Customer Experience Laggards -33.9% Reason 1
  15. Reason 2 86% of customers are willing to pay more for a better customer experience
  16. Silos in the organization
  17. Data Silos Marketing Sales Customer Service Billing Dept.
  18. We live in the age of the customer. A 20-year business cycle in which the most successful enterprises will reinvent themselves to systematically understand and serve increasingly more powerful consumers. Forrester
  19. Bigger role for the CMO • Focus of the CMO should be on creating and safeguarding the customer experience! • Fueling innovation and new business models: CMO as firestarter... • Become owner of customer data that will guide and enable your company strategy.
  20. Overview Managing the data Understanding the data Acting on the data
  21. Managing the data Understanding the data Acting on the data
  22. Volume - Variety - Velocity - Value
  23. Value for Value • 47% of women would share their mobile phone location with a retailer in return for a $5 credit • 83% would do so for a $25 credit Research Now
  24. Value for value in data gathering Two different data sources: ‣ Own data Ask the customer (explicitly) Auto-populate data (implicitly) ‣ External data Paid Open Any data
  25. Managing the data Understanding the data Acting on the data
  26. Personas are a vivid description of your customer database records.
  27. Socio-demo Habits Attitudes Consumption Media Technology
  28. Socio-demo Habits Attitudes Consumption Media Technology
  29. Customer Behavior Data Research data Social listing data Media reports data Third party data … ANALYZE SYNTHESIZE
  30. Analyze Customer Data Registration Data Web Browsing Email Response User Actions
  31. Clustering Database Data Engagement level User action 1 User action 2 max min
  32. Third Party Data Shopper Panel data Socio-demographic & Lifestyle data
  33. Different who? Engaging Emily • X% in db population • Socio-demographic profile • Shopping attitudes • A-Brands • Coupon usage • P&G category spend • Lifestyle data Inactive Iris Different what? • Content and offers • Frequency
  34. Site engagement • Repeat visits x2 • Time on site x9 Sales • Double-digit growth with FlavorPrint users
  35. Predictive Analysis
  36. “We found that 74% of the time, our model could correctly predict the exact address.” Uber
  37. HISTORICAL CUSTOMER DATA CLIENT ID BIRTH DATE LOCATION … # TRANS JAN # TRANS FEB # TRANS MRCH 567678 25/11/1976 3400 8 2 0 566777 23/09/1987 3245 4 8 0 567789 11/08/1945 6700 6 8 6 445566 21/03/1967 9000 8 9 3 CURRENT CUSTOMER DATA CLIENT ID BIRTH DATE LOCATION … # TRANS APR # TRANS MAY # TRANS JUNE 567898 25/08/1956 2440 6 1 0 589777 13/09/1977 3000 4 8 0 467789 11/09/1969 2431 5 2 0 445578 12/05/1988 1000 8 9 2 TODAY CHURN FLAG YES NO NO NO T + X CHURN PREDICTION YES NO YES NO LEARN APPLY How it works
  38. What’s the most likely model of interest when repurchasing?
  39. Attributes Initial enquiry data (date, model, method, previous car…) Purchase data (date, model, engine type, options, …) Driver data (birthdate, location, dealer…) Satisfaction data (survey completion, …) Predicted Model of Interest
  40. DM pack Customized customer experience Email DM pack Es-mated Repurchase Date Targets within buying window Non-­‐responders Non-­‐converted Test Drivers A A B B C
  41. FMCG Company Which is the most likely coupon offer combination that will trigger redemption?
  42. Attributes Household data (family size, age, …) Online response data (email open/click behaviour,…) Profile data (brand consumption, …) Redemption data (coupon redemption, …)
  43. Democratization of data science
  44. Power to the marketeer
  45. Managing the data Understanding the data Acting on the data
  46. Relevance + Utility =
  47. Customer Journey Planning “A pre-planned series of integrated, targeted communications, content or services designed to deliver a personal experience for the consumer across all touch points.”
  48. From campaigns (ads) to customer moments (value) 1. What are the make or break moments? 2. How can this be a positive experience? 3. What data do we need to help deliver the experience?
  49. • Persona • Time • Place • Device • External Data Context {
  50. 5 golden rules for creating ‘contextual’ customer connections
  51. #1 - Make it easy to interact
  52. It’s CMR
  53. #2 - Combine data and collaborate
  54. Context creates new connections
  55. #3 - Create value, not campaigns
  56. "We are moving more and more toward service, personalization, [and] customization." Guive Balooch, global director of L'Oréal's Connected Beauty Incubator
  57. #4 - Make real-time data a reality
  58. Data and technology ‘yes’, adding creativity and imagination ‘woohoo’
  59. #5 - Think big about any data
  60. Key takeaways
  61. Requirements: • Data driven culture • People & Technology Relevance + Utility =
  62. Data-driven company culture Strategy Data Optimize + Innovate User Experience
  63. People & Technology
  64. Next 48 hours?
  65. 1. What’s your next move on the data maturity stairway? 2. Who in your own organisation will you address and involve in order to be able to move? 3. What value will you be offering beyond your product or service?
  66. Think big about any data
  67. Thank you!
  68. October 9th
  69. IAB ThinkData November 20th

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