What to Expect from This Session<br /><ul><li>Explore the fundamentals and benefits of Lift Modeling and Constraint-Based ...
Learn how CVS Caremark has utilized their POS channel to deliver relevant offers and improve ROI
Behind-the-scenes analytic engine that drives differentiated offers to unique types of customers
Program evolution
Lessons learned</li></li></ul><li>Introductions<br />
Who We Are<br /><ul><li>Consulting firm specializing in information-based marketing and customer intelligence
Founded in 1999, with headquarters in Burlington, MA
Business problem solvers, skilled in analytics
Broad, practical experience across multiple industries
Outcomes driven - strive to deliver work that produces significant bottom line impact</li></li></ul><li>What We Do<br />Cu...
CVS<br /><ul><li>What does CVS stand for?</li></ul>Consumer Value Stores<br />Caroline, Vanessa, Sophie<br />Convenience, ...
CVS<br /><ul><li>Nation’s largest retail pharmacy chain
Recently opened 7,300th store
CVS fills more than 1 out of every 7 prescriptions in America
ExtraCare is the largest and most successful retail loyalty program in the country</li></li></ul><li>ExtraCare Loyalty Pro...
Do you have your ExtraCare Card? <br /><ul><li>68 MM active ExtraCare cardholders
70% of CVS transactions are on the card
ExtraCare customers visit the store every month, which is twice as often as the typical non-ExtraCare shopper
Every second, 32 ExtraCare cards are scanned in the US
The very next day, these transactions can be transformed into customer insights</li></li></ul><li>Lift Modeling and Optimi...
 Incremental Sales Potential<br />Limit or Exclude from Discounting Strategy<br />New Population - Test Offer Levels<br />...
Lift Modeling<br />Focus directly on the consumer behavior that drives ROI<br /><ul><li>Predicts incremental response rath...
Model score provides a mechanism to target customer with the highest likelihood to deliver incremental sales
The challenge:  incremental sales is an aggregate measure, while modeling and targeting must be done at the individual lev...
Optimization targets:  maximum lift sales, program revenue, units, ROI, margin impact; minimum incentive cost
Optimization Constraints:  budget, incentive cost, ROI hurdle, total sales
Flexibility is a key benefit</li></li></ul><li>Optimization in Action<br />
How do you do it?<br />Start by asking:  are you leveraging everything you know about your customer?<br />Shopping Behavio...
POS Marketing<br /> at CVS<br />
POS Coupons - Overview<br />Sophisticated targeting engine drives delivery of POS Coupons<br /><ul><li>Printed at Bottom o...
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The Paradigm: From Sales to Profits Using Optimization Analytics

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The Paradigm: From Sales to Profits Using Optimization Analytics

  1. 1.
  2. 2. What to Expect from This Session<br /><ul><li>Explore the fundamentals and benefits of Lift Modeling and Constraint-Based Optimization Analytics
  3. 3. Learn how CVS Caremark has utilized their POS channel to deliver relevant offers and improve ROI
  4. 4. Behind-the-scenes analytic engine that drives differentiated offers to unique types of customers
  5. 5. Program evolution
  6. 6. Lessons learned</li></li></ul><li>Introductions<br />
  7. 7. Who We Are<br /><ul><li>Consulting firm specializing in information-based marketing and customer intelligence
  8. 8. Founded in 1999, with headquarters in Burlington, MA
  9. 9. Business problem solvers, skilled in analytics
  10. 10. Broad, practical experience across multiple industries
  11. 11. Outcomes driven - strive to deliver work that produces significant bottom line impact</li></li></ul><li>What We Do<br />Customer Intelligence and Reporting<br />Support Business Decision Making / Processes<br />Multi-media Marketing Effectiveness<br />Predictive Analytics and Scoring<br />Increase Business Growth and Profitability<br />Campaign Planning and Measurement<br />Customer Acquisition and Development<br />Optimize Marketing Spending<br /> Loyalty Program Strategy<br />
  12. 12. CVS<br /><ul><li>What does CVS stand for?</li></ul>Consumer Value Stores<br />Caroline, Vanessa, Sophie<br />Convenience, Value, Service<br />Computer Vision Syndrome<br />
  13. 13. CVS<br /><ul><li>Nation’s largest retail pharmacy chain
  14. 14. Recently opened 7,300th store
  15. 15. CVS fills more than 1 out of every 7 prescriptions in America
  16. 16. ExtraCare is the largest and most successful retail loyalty program in the country</li></li></ul><li>ExtraCare Loyalty Program<br />(brief video)<br />
  17. 17. Do you have your ExtraCare Card? <br /><ul><li>68 MM active ExtraCare cardholders
  18. 18. 70% of CVS transactions are on the card
  19. 19. ExtraCare customers visit the store every month, which is twice as often as the typical non-ExtraCare shopper
  20. 20. Every second, 32 ExtraCare cards are scanned in the US
  21. 21. The very next day, these transactions can be transformed into customer insights</li></li></ul><li>Lift Modeling and Optimization<br />
  22. 22. Incremental Sales Potential<br />Limit or Exclude from Discounting Strategy<br />New Population - Test Offer Levels<br />Best Offers<br />“Best” customers are not always the same ones who drive campaign profitability<br />Best Customers - Top Sales<br />Promotion Sensitive, High Incremental Sales<br />Response Model<br />Lift Model<br />
  23. 23. Lift Modeling<br />Focus directly on the consumer behavior that drives ROI<br /><ul><li>Predicts incremental response rather than total response
  24. 24. Model score provides a mechanism to target customer with the highest likelihood to deliver incremental sales
  25. 25. The challenge: incremental sales is an aggregate measure, while modeling and targeting must be done at the individual level</li></li></ul><li>Offer Optimization Engine<br />Objective:<br />Determine the optimal offer assignment for each customer given certain goals and constraints<br /><ul><li>Automated approach to offer assignment; allows quick evaluation of numerous scenarios
  26. 26. Optimization targets: maximum lift sales, program revenue, units, ROI, margin impact; minimum incentive cost
  27. 27. Optimization Constraints: budget, incentive cost, ROI hurdle, total sales
  28. 28. Flexibility is a key benefit</li></li></ul><li>Optimization in Action<br />
  29. 29. How do you do it?<br />Start by asking: are you leveraging everything you know about your customer?<br />Shopping Behavior<br />Category Breadth<br />Promotion History / Channel Preference<br />Basket Profiles<br />Digital Behavior<br />Tenure<br />Payment Type<br />Demographics<br />Employees /<br />Non-Employees<br />
  30. 30. POS Marketing<br /> at CVS<br />
  31. 31. POS Coupons - Overview<br />Sophisticated targeting engine drives delivery of POS Coupons<br /><ul><li>Printed at Bottom of Cash Register Receipt
  32. 32. Primary Objective: Drive return visits
  33. 33. Customer data (what they buy, who they are) drives offer assignment
  34. 34. Offers: Product-Specific or “Open-Ended”
  35. 35. Open-Ended Offers
  36. 36. Discount on any non-Rx item in the store
  37. 37. Automated trigger program
  38. 38. Redeemable on next visit
  39. 39. Broader offers drive most sales lift and ROI
  40. 40. Largest CVS-funded incentive program</li></li></ul><li>CVS Approach – Trigger Offers<br />Customized and Dynamic Targeted Offers<br />Illustrative<br />ExtraCare/coupon<br />John Smith <br />Save $4 on any $20 purchase. <br />(UP TO $4.00 VALUE)<br />EXPIRES 11/4/2011<br />ExtraCare® Card #*******8047<br />*EXTRACARE CARD MUST BE PRESENTED TO GET THESE SAVINGS.  EXCLUDES TOBACCO, ALCOHOL, AND PRESCRIPTIONS.  NO CASH BACK.  TAX CHARGED ON PRE-COUPON PRICE WHERE REQUIRED.<br />LIMIT ONE PER CUSTOMER.<br />3363805547<br />Customer 1:<br />Spends $12.50 per trip, visits 3x Qtr<br />Customer 2:<br />Spends $22 per trip and, visits 4x Month<br />Customer 3:<br />Spend $15 per trip and, visits 5x Qtr<br />Offer Configuration and Cadence determined<br />quarterly by mining millions of data Points:<br />Category<br />Shopped<br />Demos<br />Past <br />Offers<br />Profit<br />Level<br />Promos<br />Rx<br />Freq<br />Customer 1<br />Matched up to $3 off $15 offer<br />Customer 2:<br />Matched up to $10 off $50 offer<br />Customer 3:<br />Matched up to $4 off $20 offer<br />
  41. 41. Evolution of POS Program <br />Ongoing innovation and refinement has ensured lasting program success<br />Step 5<br /><br />Optimize<br />Optimization System<br />Step 4<br />Innovate<br />Lift Modeling<br />Step 3<br />Step 2<br />Refine<br />Response, Modeling, Differentiation<br />Step 1<br />Target and Execute<br />R, F, M<br />Build Fact Base<br />Test and Learn<br />We were here<br />This could not be achieved without a commitment to test and learn<br />
  42. 42. Campaign ROI<br />The Catalyst: Declining ROI<br />Response model targeting was beginning to be unprofitable – need for investigating drivers and potential solutions<br />Key Question: Who drives incremental sales?<br />2009<br />2010<br />
  43. 43. Modeling Approach<br /><ul><li>Explore a wide range of variables to capture key customer behaviors
  44. 44. Promotion sensitivity and history, brand preferences, loyalty, demos
  45. 45. Create multiple predictive models for each step in the coupon redemption process</li></ul>Print<br />visit, purchase<br />Redeem<br />visit, purchase<br />Spend<br />basket size<br /><ul><li>Estimate a wide range of success metrics
  46. 46. Optimize offer assignment, unique to each customer, given predicted behavior in response to each offer scenario </li></li></ul><li>Program Structure<br />Econometric Modeling<br />Business Metrics<br />Data Inputs<br />Optimization<br />The final solution involves multiple models that capture the profit dynamics<br />Sales<br />No Offer<br />Shopping Behavior / Loyalty<br />$3 off $10<br />Sales Lift<br />Price & Promotional Sensitivity<br />Predictive Models (14)<br />$4 off $20<br />Cost<br />Coupon Usage<br />$5 off $25<br />Category Patterns<br />Margin Lift<br /><ul><li>Qualifier (1)
  47. 47. Redemption (8)
  48. 48. Sales (5)</li></ul>Customer Demographics<br />$10 off $50<br />ROI<br />
  49. 49. Old Target<br />New Target<br />Don’t Target <br />Recommended Target Changes<br />Significant changes to targeting and offer assignment were recommended<br />Add <br />Drop<br />Keep <br /><ul><li>Higher incremental sales
  50. 50. Stronger ROI</li></li></ul><li>The Test<br />A test was implemented to compare the new approach to the old<br />Eligible Customers<br />New Strategy - Lift Modeling and <br />Optimization Based<br />Existing Strategy - Response Model Based<br />Control Group<br />Control Group<br />
  51. 51. Test Results<br />It didn’t work!<br /><ul><li>$3 and $10 coupon worked well
  52. 52. $4 coupon drove negative results
  53. 53. Identified disconnect in success metrics</li></li></ul><li>If At First You Don’t Succeed…<br /><ul><li>Granted another opportunity to “split” the eligible population in a head-to-head test
  54. 54. Refined and implemented models using more recent data
  55. 55. Tested alternative approaches
  56. 56. Model Based Targeting and Offer Assignment
  57. 57. “Strategy-Based” approach – art plus science</li></li></ul><li>Art + Science Wins!<br />
  58. 58. Lessons Learned<br /><ul><li>Lift Modeling is not straight forward – be open to testing
  59. 59. Most challenging: predicting incremental sales dollars and ROI
  60. 60. There are several alternative modeling approaches
  61. 61. Focus on the right metrics, and be consistent with corporate KPIs
  62. 62. Optimization is likely to require human intervention – solid business understanding and good intuition</li></li></ul><li>In Conclusion<br /><ul><li>Leverage as much data and customer insight as you can to maximize
  63. 63. The next generation of marketing analytics is moving beyond traditional response modeling
  64. 64. Understand your success metrics and use analytic tools that focus directly on those metrics
  65. 65. Be aware of the challenges
  66. 66. The best solution requires a balance of technique and business knowledge</li></li></ul><li>Getting Started<br /><ul><li>Set up randomized testing with appropriate treated / control quantities
  67. 67. Capture historical campaign data
  68. 68. Customer characteristics at time of execution
  69. 69. Response results
  70. 70. Ensure operational system infrastructure is in place
  71. 71. Identify resource to develop solution</li></li></ul><li>ANALYTIC VISION. BUSINESS IMPACT.<br />Thank You!<br />Marcy Riordan<br />Michael Parduhn<br />For more information contact: mriordan@iknowtion.com(781) 494-9989<br />

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