3. Learn how CVS Caremark has utilized their POS channel to deliver relevant offers and improve ROI

4. Behind-the-scenes analytic engine that drives differentiated offers to unique types of customers

5. Program evolution

8. Founded in 1999, with headquarters in Burlington, MA

9. Business problem solvers, skilled in analytics

10. Broad, practical experience across multiple industries

14. Recently opened 7,300th store

15. CVS fills more than 1 out of every 7 prescriptions in America

18. 70% of CVS transactions are on the card

19. ExtraCare customers visit the store every month, which is twice as often as the typical non-ExtraCare shopper

20. Every second, 32 ExtraCare cards are scanned in the US

22. Incremental Sales Potential Limit or Exclude from Discounting Strategy New Population - Test Offer Levels Best Offers “Best” customers are not always the same ones who drive campaign profitability Best Customers - Top Sales Promotion Sensitive, High Incremental Sales Response Model Lift Model

24. Model score provides a mechanism to target customer with the highest likelihood to deliver incremental sales

26. Optimization targets: maximum lift sales, program revenue, units, ROI, margin impact; minimum incentive cost

27. Optimization Constraints: budget, incentive cost, ROI hurdle, total sales

29. How do you do it? Start by asking: are you leveraging everything you know about your customer? Shopping Behavior Category Breadth Promotion History / Channel Preference Basket Profiles Digital Behavior Tenure Payment Type Demographics Employees / Non-Employees

30. POS Marketing at CVS

32. Primary Objective: Drive return visits

33. Customer data (what they buy, who they are) drives offer assignment

34. Offers: Product-Specific or “Open-Ended”

35. Open-Ended Offers

36. Discount on any non-Rx item in the store

37. Automated trigger program

38. Redeemable on next visit

39. Broader offers drive most sales lift and ROI

41. Evolution of POS Program Ongoing innovation and refinement has ensured lasting program success Step 5  Optimize Optimization System Step 4 Innovate Lift Modeling Step 3 Step 2 Refine Response, Modeling, Differentiation Step 1 Target and Execute R, F, M Build Fact Base Test and Learn We were here This could not be achieved without a commitment to test and learn

42. Campaign ROI The Catalyst: Declining ROI Response model targeting was beginning to be unprofitable – need for investigating drivers and potential solutions Key Question: Who drives incremental sales? 2009 2010

44. Promotion sensitivity and history, brand preferences, loyalty, demos

47. Redemption (8)

48. Sales (5)Customer Demographics $10 off $50 ROI

52. $4 coupon drove negative results

54. Refined and implemented models using more recent data

55. Tested alternative approaches

56. Model Based Targeting and Offer Assignment

59. Most challenging: predicting incremental sales dollars and ROI

60. There are several alternative modeling approaches

61. Focus on the right metrics, and be consistent with corporate KPIs

63. The next generation of marketing analytics is moving beyond traditional response modeling

64. Understand your success metrics and use analytic tools that focus directly on those metrics

65. Be aware of the challenges

67. Capture historical campaign data

68. Customer characteristics at time of execution

69. Response results

70. Ensure operational system infrastructure is in place