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MMA-MM-Overview (1).ppt
1.
© 2002 Marketing
Management Analytics – www.mma.com Marketing Mix Models
2.
Copyright © 2002
Marketing Management Analytics www.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.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.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, Rural 1 2 3 4
5.
Copyright © 2002
Marketing Management Analytics www.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.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 Weeks 3 Weeks 1 4 Weeks 3-5 Weeks 1
7.
Copyright © 2002
Marketing Management Analytics www.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 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.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.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.com Page:11 The models relate changes in sales to the changes in marketing support and other causal factors present during each week. 1 5 9 1 3 1 7 2 1 2 5 2 9 3 3 3 7 4 1 4 5 4 9 5 3 5 7 6 1 6 5 6 9 7 3 7 7 0 1 0 , 0 0 0 2 0 , 0 0 0 3 0 , 0 0 0 4 0 , 0 0 0 5 0 , 0 0 0 6 0 , 0 0 0 7 0 , 0 0 0 High Activity Low Activity Sales High Activity Week 1 13 22 33 41 49 58 67 70 78 TV GRPs - 214 142 - 50 - 89 284 65 - Radio GRPS - 100 - 60 - 40 - 40 - - In-Store Promotions 10 75 - 30 5 - - 20 - 25 Support
12.
Copyright © 2002
Marketing Management Analytics www.mma.com Page:12 Model Validation Face Validity Holdout Tests Model Stats Other - Signs - Volume Trends - Trade Contribution Holdout Errors & Patterns R-Square, Durbin Watson, Avg % Error, F-Stats, T-Stats, etc. Other validations against prior learnings or known relationships
13.
Copyright © 2002
Marketing Management Analytics www.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. Analyzed Market Aggregate 5/2/93 8/1/93 10/31/93 1/30/94 5/1/94 7/31/94 10/30/94 1/29/95 4/30/95 -100,000 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 Sales Fit Period Average Error: 2.3% Validation Period Average Error: 2.8% 104 Weeks Ending 4/95 Model Estimate Actual Sales Residuals 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.com Page:15 Incremental volume will be broken out into the various marketing elements. 23.6% 50.0% 7.5% 7.5% 3.8% 7.5% Prior Year Current Year Volume Contribution - Example Direct TV Base Promotions Print Radio Corp TV Total Volume 110.0 MM Total Volume 102.0 MM 7.8% 3.9% 4.9% 9.7% 54.2% 19.5%
16.
Copyright © 2002
Marketing Management Analytics www.mma.com Page:16 Comparing ROI efficiencies across vehicles shows that all TV and Trade spending is very efficient. $3.3 $2.6 $3.6 $3.8 $4.2 $3.0 TV Adv Trade SMF Print Radio Total Marketing Efficiencies - Example (Incremental $ Sales Per Marketing $)
17.
Copyright © 2002
Marketing Management Analytics www.mma.com Page:17 Changes in yearly support, resulting contribution to sales and efficiency will be reported. 1256 872 1.9% 2.2% $3.41 $2.69 Direct TV Advertising Performance - Summary (Example) Support TRPs % Contribution % of Total Brand Volume Efficiency Cost per Incr. Vol Prior Year Current Year
18.
Copyright © 2002
Marketing Management Analytics www.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 $0.42 $0.51 Prior Year - Copy A Current Year - Copy B Copy A Total Copy A = 7,535 7,458 7,987 8,586 All Other New Flavor Copy B
19.
Copyright © 2002
Marketing Management Analytics www.mma.com Page:19 ROI efficiencies can also be compared across categories by brand, department and marketing investment. 1.24 0.84 0.66 1.10 0.85 1.24 1.20 0.93 1.98 1.34 0.68 0.57 0.48 0.40 1.17 0.90 2.10 2.34 0.74 0.70 0.61 1.34 0.54 0.68 1.50 0.45 0.56 1.17 0.80 0.65 1.30 1.20 1.14 1.34 0.94 1.30 Brand 1 Brand 2 Brand 3 Brand 4 Brand 5 Brand 6 Brand 7 Brand 8 Brand 9 1.22 0.84 0.76 0.60 0.72 2.54 0.61 0.65 3.02 Profit per $1 Invested Total Mix TV Media Print In-store Cons. Promo.
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