The Dog Ate My Tracking: Practical Solutions for Valuing Mobile Traffic By Soren Ryherd

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SMX Advanced 2014 Session #SMX #23C - Attribution Success In The Age Of Mobile - The Dog Ate My Tracking: Practical Solutions For Valuing Mobile Traffic By Soren Ryherd Of Working Planet

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The Dog Ate My Tracking: Practical Solutions for Valuing Mobile Traffic By Soren Ryherd

  1. 1. The Dog Ate My Tracking Practical Solutions for Valuing Mobile Traffic Soren Ryherd Working Planet
  2. 2. #SMX 12 Jun 2014 Mobile Tracking Challenges Image property of FollowYu, Inc. Cross-Device Behavior Tracking Breaks • Javascript not supported on all phones • Cookie persistence varies • 90% of American adults have a cell phone • 58% of American adults have a smartphone • 32% of American adults own an e-reader • 42% of American adults own a tablet computer - 2014 Pew Charitable Trust Survey Data
  3. 3. #SMX 12 Jun 2014 Attribution Models – FAIL because touchpoints cross devices thus breaking connections Predictive Models (CPA based bidding) – FAIL because mobile actions may not be tied to marketing source Media Mix Models – SUCCEED may be more difficult to create because of quantitative assessment and holistic view required Traditional Modeling Breaks Down
  4. 4. #SMX 12 Jun 2014 Media Mix Modeling A Basic Media Mix Model Mix Models attempt to predict unknown sales based on known marketing and advertising activity U = C1*n1 + C2*n2 +C3*n3…+M U = “Unknown” Monthly Sales C = Known Channel Sales Activity n = Channel Influence M = Sales from additional sources (Word of Mouth, etc.) Goal: Determine Cause and Effect Relationships Mathematically Based on Variability in Underlying Data
  5. 5. #SMX 12 Jun 2014 Case Study Even when doing things right… • Responsive Design • Tablet Optimized • Clear Mobile Calls to Action • Multi-Touchpoint Tracking • Attribution Modeling • Profit-Driven Optimization • (No call-in sales to confuse channels) Mobile is still a challenge: Phone-based PPC provides 20% of traffic, but >3% of PPC sales
  6. 6. #SMX 12 Jun 2014 Traditional Metrics Don’t Reveal Issue 0% 10% 20% 30% 40% 50% 60% 70% 80% Unknown Link/SEO PPC Social 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Desktop Phone Tablet Traffic Orders By Device By Channel Data from Oct13 – Jan14 Traffic & Orders
  7. 7. #SMX 12 Jun 2014 Combination of Device/Channel 0% 10% 20% 30% 40% 50% 60% 70% Unknown Link/SEO PPC Social 0% 10% 20% 30% 40% 50% 60% 70% Unknown Link/SEO PPC Social Tablet Phone Desktop Predicted Actual Orders by Channel Data from Oct13 – Jan14
  8. 8. #SMX 12 Jun 2014 Forming Hypotheses Yes, it appears there is a problem in attributing mobile value Identifying Signs: • Over 76% of phone sales are not tied to any marketing source • Phone sales tied to marketing source only occur in single session • “Unknown” sales bucket is close to 30% of all orders despite multi- touchpoint tracking, with limited external traffic sources • Orders by device proportional to traffic, but not by channel Twin Hypotheses: Phone tracking is breaking across multiple sessions and Phone-initiated traffic is migrating to desktop/tablet to purchase …Interestingly, cookie and tracking preservation is better on tablets than desktop.
  9. 9. #SMX 12 Jun 2014 Understanding upper and lower limits: •Upper limit bound by sales numbers •Lower limits bound by performance Common Sense Predictions Felix Chien incorrectly-sourced phone orders cannot be more than 7.6% of total sales under current media mix Cross device sales (phone to desktop) are not likely to be more than that proportional to traffic by device – in this case a max of 20% of total orders Potential for testing: Phone-based traffic may be providing 3x more value in phone-based sales than currently tracked to media source, and up to an additional 4.2x in cross-device sales for 7.2x higher potential value than estimated by strict CPA-based bidding
  10. 10. #SMX 12 Jun 2014 Geographic test Pulse test Cause & Effect Testing Period 1 Period 2 Period 3 Period 4 Period 5 Period 6 Period 7 Period 8 Period 9 Period 10 Impressions
  11. 11. #SMX 12 Jun 2014 Adjusting for Time 0 5 10 15 Point of Investment Sales Per Day From Initial Investment 1 6 11 16 21 26 1 6 11 16 21 26 Pulse length must take into account sales cycle. If pulse is too short, it is difficult to determine trends because of overlapping “shoulder” data. 90% of sales in first 8 days 3 Day Pulse Cycle 7 Day Pulse Cycle
  12. 12. #SMX 12 Jun 2014 Results On Off On Off On Off Unknown Link/SEO PPC Social • 47% more mobile impressions were delivered during “On” pulses • “Unknown” sales increased by 28% during “On” pulses, PPC by 10.7% • Total sales increased by 16.7% for a total PPC spend increase of 6.3% (Data from Feb 17 – Jun 4 ’14; extrapolated for final period) Order Volume
  13. 13. #SMX 12 Jun 2014 Results: Valuing Mobile Before Phone-based traffic was 20.5% of total PPC clicks 2.5% of total orders were sourced back to phone-based PPC After Phone-based traffic is 30.2% of total PPC clicks Mix models predict phone-based PPC now responsible for 27% of total orders Phone-based PPC traffic was being undervalued by >10x
  14. 14. #SMX 12 Jun 2014 Thank you Soren Ryherd soren@workingplanet.com Working Planet 131 Wayland Avenue Providence, RI 02906 401-709-3123 WorkingPlanet.com @sorenryherd @workingplanet Thank You

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