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From Digital Attribution to Marketing Mix Modelling


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MeasureCamp Amsterdam 2018. We are good when it comes to measuring advertising but should you also thing what kind of effect other marketing P's have on sales?

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From Digital Attribution to Marketing Mix Modelling

  1. 1. From Digital Attribution to MMM #MeasureCampNL – April 21, 2018 @mertanen
  2. 2. Using machine learning for explaining and predicting user behavior from web analytics data. 2
  3. 3. Traditional Web Analytics is dying...
  4. 4. Optimizing Promotions 4
  5. 5. Cookie-based 1:1 attribution produces superior understanding of the conversion journey Tradional measurement: Customer journey: Time Value These clicks are ignored Time Value The last click gets all the credit
  6. 6. Assisted conversions
  7. 7. Attribution model comparison
  8. 8. Cookie-based 1:1 attribution produces superior understanding of the conversion journey Algorithmic attribution: Customer journey: Time Value Model estimates value of each touchpoint ValueTime
  9. 9. Attribution model comparison Organic search Paid search Email Social media Total conversion value - example First touch Last touch Linear Advanced Attribution
  10. 10. The 4-7 Ps of Marketing 10
  11. 11. The total effect of marketing actions over time Direct Buy Short Term Effect Create Curiosity, Seek online info Intermediate Effect Change attitude towards brand Long Term Effect Time Total Sales Effect + + = Campaign Digital Analytics Digital Analytics + Research Marketing Mix Modelling
  12. 12. What is MMM? Marketing Mix Modelling Media Mix Modelling Econometric Modelling Media Attribution Modelling
  13. 13. It is used to understand all drivers of business performance Offline Investment Brand image Market Dynamics Operational factors Digital media TV media Pricing / Promotions PR Competitors Business KPI SALES!
  14. 14. Typical Data Requirements KPI Sales / Bookings / Quotes Web visits / calls Regional Store level By source (e.g. retail vs online sales) Internal Pricing Promotions Store level info Launches / product changes Retention Media Offline media: spend/ratings by channel Online media: Impressions/clicks/spend by channel Social media: Facebook and Twitter; Likes/Clicks/Impressions Media spend for all competitors by channel DM / Email etc volumes Other Competitor info Weather CCI, RPI, Inflation etc. Legislation Brand metrics Data needs to cover a wide range of factors Data needs to be over a long enough period Data needs to be weekly for best results
  15. 15. Modelling projects follow a similar process Insights Debrief writing Results Delivery Kick Off Data Collection Data Processing Analysis / Modelling Pulling together results Several months
  16. 16. Typical questions MMM can answer How effective is our marketing and advertising investment overall? How important is pricing to my sales and what is the likely impact of future changes I might make? Do I need to be ‘always on’ or are there seasons when investment is more effective? How are my promotions performing and which ones deliver the most revenue? Which communication channels are most effective? Return on Investment? How do current events and market dynamics impact my KPIs? How does competitive media impact my business? Should I spend more? How many more sales would that give me?
  17. 17. Sales drivers - weekly basis What is exactly causing the sales? Degree of explanatory power: 58% -1,000 -500 0 500 1,000 1,500 2,000 2010-1 5 9 13 17 21 25 29 33 37 41 45 49 2011-1 5 9 13 17 21 25 29 33 37 41 45 49 SALES Base Seasonality Distribution Price TV Sales
  18. 18. 88% 8% 8% 6% 2% 0% -1% -1% -10% 857.447 79.646 75.566 61.520 22.250 -0 -6.000 -13.366 -102.223 974,841 0 200,000 400,000 600,000 800,000 1,000,000 1,200,000 BASE Price & Promotion Tracking Media Distribution & Launches Unexplained Seasonality Competitor - Media Competitor - Price & Promotion Total Revenue('000) Promotions are the biggest driver of sales. Negative impact from price increases Media investments drive almost as much sales as promotions Successful product launches have grown the brand Competitor price reductions and promotions have had the biggest negative impact Sales drivers - weekly basis What is exactly causing the sales?
  19. 19. Optimization recommendations Changes in media allocations TV Spot Web-TV Desktop Display Mobile Display Programmatic Display Programmatic Mobile Facebook Chart Title 2015 budget 2016 optimized budget Media Total effect TV ROI: Sales effect: 3,3  3,7 +2 500 000 € +20% -37% +20% +20% Change %Investment level Mobil Display Web-TV Programmatic Mobil Programmatic Display Facebook -100% +20% -100% 000’
  20. 20. What kind of results you can expect? +6% ROI/CPA 10 % of clients are making small changes on media. +12% ROI / CPA 50 % of clients are optimizing media mix and timings. They get benefits from media synergies. +28% ROI / CPA 40 % of clients makes significant strategic decisions regarding to marketing actions and media budgets.
  21. 21. Pros & Cons of MMM What’s good • We can quantify objectively & fairly - What is driving our KPI - When it affects sales (short/medium term) - How much it affects sales - Factors outside of your control • We can provide a starting point - For strategic planning purposes - For investment allocation • Explains and quantifies your historic KPI trend What’s difficult • Data Limitations - Incorrect/missing data - Lack of variation - Multi-collinearity: all media happens at the same time - Long data series required • We can’t always tell you a positive story • We can’t tell you the impact of something you haven’t done before - Or the impact of activity beyond levels of experience • Long project timeframe
  22. 22. Contact information Petri Mertanen Director, Digital Analytics Mobile: +358 400 792 616 @mertanen