1. © 2002 Marketing Management Analytics – www.mma.com Marketing Mix Models

2. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:2 What is Marketing Mix Modeling?  An analytical approach which quantifies the sales effect of marketing activity and the financial return on that investment.  The output is used to simulate the effects of alternative marketing plans and forecast sales into the future.  All work, for all clients, is completely custom.

3. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:3 Why do marketers do Marketing Mix Analysis?  To get a true empirical relationship between marketing activity and sales.  To conduct Return on Investment analysis.  Benchmarking (are we the same / better / worse than we were last year?).  To find out how one business unit's marketing interacts (if at all) with another’s (media “halo”).  To learn upside potential and downside risk in changing marketing spend.

4. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:4 Issues that can be addressed...  How much should we spend?  What is the recommended level of spending?  How much is enough?  How should we spend it?  Which brands should receive support and how should our budget be allocated?  When should we spend it?  Before or after a price increase?  Immediately before a competitive launch?  Where should it be spent?  National vs. Local  Cites, Rural1234

5. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:5 Marketing Mix Elements Step 1 determine the contribution to incremental volume from each marketing mix element Marketing Spending Step 2 overlay marketing spending for each mix element to evaluate ROI Custom Software Step 3 utilize MMA’s custom software for optimization and simulation of marketing spending and advertising return Marketing Mix Modeling

6. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:6 Mix Modeling Timeline Data Collection & Validation Model Specification & Validation Analysis & Review 12-13 weeks Project Steps & Timing 4-5 Weeks Kick-Off Final Presentation 4 Weeks3 Weeks1 4 Weeks 3-5 Weeks1

7. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:7 Data Collection Media Nielsen CMR Agency Integrated Database Sales (Internal, Syndicated) Promotion Act Media Catalina Internal Shipments Web Promotion Financial 1 1 2 2 Data Analysis System The capability to integrate several disparate data sources The ability to identify what variables should be included in your model.

8. © 2002 Marketing Management Analytics – www.mma.com Marketing Mix Modeling (How is it Done?)

9. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:9 Modeling: What to measure? Start with a Dependent Variable: Sales, or Awareness, or New Customers or Brand Interest Sales by Segment (i.e. Heavy vs. Light)

10. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:10 Modeling: What are the Drivers Gather information on all variables that possibly influence your dependent variable Independent Variables: TV Print Radio Outdoor Internet Promotions PR Coupons Sampling Direct Mail Competitive Economic Environment/Weather Industry Trends Etc.

11. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:11 The models relate changes in sales to the changes in marketing support and other causal factors present during each week. High Activity Low Activity Sales High Activity Support

12. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:12 Model Validation

13. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:13 Models need to be able to predict volume in the near future. Model holdout validations can help evaluate a model’s predictiveness. The model should “explain” as much of the weekly variance in sales as possible. The R- Squared statistic quantifies a models fit. Model residuals should exhibit no patterns and significant weekly misses should be understood. Average errors and Durbin Watson statistics can help with these issues. 104 Weeks Ending 4/95 Model EstimateActual SalesResiduals Basic Model Stats & Holdout Validation

14. © 2002 Marketing Management Analytics – www.mma.com Marketing Mix Modeling What Does It Answer?

15. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:15 Incremental volume will be broken out into the various marketing elements. Prior Year Current Year Volume Contribution - Example Direct TV BasePromotionsPrintRadioCorp TV Total Volume 110.0 MM Total Volume 102.0 MM

16. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:16 Comparing ROI efficiencies across vehicles shows that all TV and Trade spending is very efficient. Return Per $ Marketing Marketing Efficiencies - Example (Incremental $ Sales Per Marketing $)

17. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:17 Changes in yearly support, resulting contribution to sales and efficiency will be reported. Direct TV Advertising Performance - Summary (Example) Support TRPs % Contribution % of Total Brand Volume Efficiency Cost per Incr. Vol Prior YearCurrent Year

18. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:18 Evaluation of Copy Effectiveness TV Advertising and Cost Efficiency Copy A vs Copy B Volume Effectiveness Volume Per MM Impressions Cost Efficiency* Cost Per Incremental Unit Copy A Total Copy A = 7,535

19. Copyright © 2002 Marketing Management Analytics ‌ www.mma.comwww.mma.com Page:19 ROI efficiencies can also be compared across categories by brand, department and marketing investment. Brand 1 Brand 2 Brand 3 Brand 4 Brand 5 Brand 6 Brand 7 Brand 8 Brand 9 Profit per $1 Invested Total MixTV MediaPrintIn-storeCons. Promo.