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Advanced attribution model

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Approaches for a data driver attribution model

Published in: Data & Analytics

Advanced attribution model

  1. 1. Advanced Attribution Model, Analytics Summit, November 13th , 2014 Aspa Lekka a.lekka@foodpanda.com
  2. 2. Foodpanda is a global online food delivery marketplace Company:  www.foodpanda.com  Founded in 2012  Present in more than 45 countries Business Intelligence & Analytics:  Google Analytics and Google Analytics Premium  Team of 8 people
  3. 3. TV Mobile App Ad SEM Conversion Customer Journey
  4. 4. Multiple channels: •SEM •Display •CRM •Affiliate •Radio •Price Comparison •….. Marketing budget allocation Get new visitors AWARENESS Maximize orders ACTION 0 50 100 150 200 250 Social Direct Display Affiliate Price comparison Search Last click- orders TOTAL: 503 0 20 40 60 80 100 120 140 160 180 Social Direct Display Affiliate Price comparison Search Last click - orders TOTAL: 438 Awareness Interest Desire Action Why attribution model?
  5. 5. Every channel gets attributed the correct orders
  6. 6. Calculating the CAC for Marketing Campaigns NEW CUSTOMERS ACQUIRED Campaign 1 BUDGET Monday Tuesday Wednesday Thursday Friday Saturday Sunday TOTAL Monday 1,000 € 13 13 Tuesday 1,100 € 21 21 Wednesday 900 € 22 22 Thuerday 1,000 € 25 25 Friday 850 € 23 23 Saturday 1,200 € 24 24 Sunday 1,000 € 26 26 CAC 77 € 52 € 41 € 40 € 37 € 50 € 38 €
  7. 7. How efficient was the Marketing Budget? NEW CUSTOMERS ACQUIRED Campaign 1 BUDGET Monday Tuesday Wednesday Thursday Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday TOTAL Monday 1,000 € 10.5 2.9 14.5 10.8 12.3 19.0 9.0 79.0 Tuesday 1,100 € 10.5 6.6 3.9 13.3 3.1 6.2 13.9 57.4 Wednesday 900 € 5.2 4.1 8.0 9.4 8.1 18.1 17.8 70.6 Thuerday 1,000 € 12.7 20.2 17.3 5.8 3.9 4.0 9.7 73.6 Friday 850 € 4.7 7.8 12.0 6.6 6.0 20.5 2.6 60.2 Saturday 1,200 € 19.4 16.7 7.6 17.6 19.0 6.1 16.1 102.4 Sunday 1,000 € 7.4 2.2 5.9 15.2 13.4 16.4 11.7 72.1 CAC* 13 € 17 € 14 € 14 € 17 € 10 € 14 €
  8. 8. Data Driven Models for Attribution 1. SHAPLEY VALUE 2. SURVIVAL ANALYSIS PATH ANALYSIS NETWORKS STRUCTURAL EQUATION MODELING 3.
  9. 9. The Shapley Value SHAPLEY VALUE
  10. 10. The Shapley Value The Shapley value is a way to assign credit among a group of “players” who cooperate for a certain end An example: • 3 players (2 with right glove and 1 with left glove) • Goal: Form a pair • Assign credit to each player after forming a pair There are two possible pairs that we can form and in both of them, Player 1 needs to be involved. Therefore, Player 1, is of more importance compared to Player 2 or Player 3. Consequently, when sharing the profits, he should get a bigger part compared to Player 2 (if we case 1 is true) or Player 3 (if case 2 is true)
  11. 11. • 3 channels • A click chain that consists of these 3 channels and led to 500 transactions • Evaluate the contribution of each channel to these 500 transactions 100 125 50 270 375 350 500 The Shapley Value
  12. 12. SEM 100 DISPLAY 270-100=170 SEO 100 500-270=230 125 50 270 375 350 500 SEM 100 SEO 375-100=275 DISPLAY 500-375=125 DISPLAY 125 SEM 270-125=145 SEO 500-270=230 DISPLAY 125 SEO 350-125=225 SEM 500-350=150 SEO 50 SEM 375-50=325 DISPLAY 500-375=125 SEO 50 DISPLAY 350-50=300 SEM 500-350=150 Calculating the Shapley Value
  13. 13. Calculating the Shapley Value SEM 100 DISPLAY 270-100=170 SEO 500-270=230 SEM 100 SEO 375-100=275 DISPLAY 500-375=125 DISPLAY 125 SEM 270-125=145 SEO 500-270=230 DISPLAY 125 SEO 350-125=225 SEM 500-350=150 SEO 50 SEM 375-50=325 DISPLAY 500-375=125 SEO 50 DISPLAY 350-50=300 SEM 500-350=150 SEM’s expected marginal contribution is: DISPLAY’s expected marginal contribution is: SEO’s expected marginal contribution is: SEM 162 (0.32) DISPLAY 162 (0.32) SEO 176 (0.36) 500 orders attributed to the three channels :
  14. 14. Survival Analysis SURVIVAL ANALYSIS
  15. 15. Target population Treatment 1 Dead Alive Treatment 2 Dead Alive Event Event TIME What is the patient’s probability to be still alive after 20 years? Survival Analysis
  16. 16. Visitors Channel 1 Event Conversion NO Conversion Channel 2 Conversion NO Conversion Event TIME What is the visitors’ probability to convert after 30 days or 5 visits? Survival Analysis
  17. 17. Day1 Day2 Day5 Day2 Day3 Day7 Day8 DAY 1 / VISIT 1 DAY 3 / VISIT 3 0 1 0 1 DAY 6 / VISIT 6 0 1 DAY 9 / VISIT 9 0 1 Survival Analysis
  18. 18. VISITORS TIME START END : censored observation : event (conversion) Censored observation: There is not “time to event” recorded because: •Loss of follow up  Drop out  Conversion due to a cause that is out of our interest •End of the study Survival Analysis
  19. 19. Survival Analysis Estimate time-to-event for a group of individuals, such as time until a visitor purchases To compare time-to-event between two or more groups, such as visitors that have clicked on a Display ad compared to visitors that have not clicked on a Display ad. To assess the relationship of co-variables to time-to-event, such as: does number of clicks, pages viewed, or time on site effect the decision to purchase?
  20. 20. DATA DRIVEN MODELS ADJUSTED TO EACH CASE LIMITED TUTORIALS ADJUST FORMULAS TO YOUR DATA (QUITE) EASY TO SET UP LINK ADS WITH ONSITE BEHAVOR FIND COST EFFICIENT CLICK CHAINS MERGE OFFLINE AND ONLINE DATA Evaluation & Suggestions
  21. 21. Thank you! Aspa Lekka a.lekka@foodpanda.com

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