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Casual Connect iQU.com

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Casual Connect iQU.com

  1. 1. Online Marketing under Pressure How to work smarter, not harder in Free2Play online games
  2. 2. Structure • Who is Oliver Kern • Why is Online Marketing under pressure • What is big data • How can this help • How can I apply this to my small data 2
  3. 3. Who is Oliver Kern? http://bit.ly/oliverkern 3
  4. 4. Why is Online Marketing under pressure? 2011 vs. 2010 2011 vs. 2010 revenues revenues $ 2,571,000,000 +3% € 473,000,000 +13% P2P F2P P2P F2P 53% 47% 42% 58% players players 39,400,000 +3% 8,700,000 +11% payers payers 22,300,000 +6% 4,500,000 +13% $ / month € / month $ 9.61 -3% € 8.76 +1% 2011 vs 2010 2011 vs 2010 F2P spending F2P spending +24% +14% © NewZoo, 2011 4
  5. 5. Why is Online Marketing under pressure?
  6. 6. Why is Online Marketing under pressure? 6
  7. 7. Why is Online Marketing under pressure? Until today… • It’s becoming more and more challenging to find affordable traffic sources • Data has not (really) worked for you • You have been focussing on key traffic sources and tried to optimize the ROI 7
  8. 8. Why is Online Marketing under pressure? What to do? 1. Get a deep understanding of your user types 2. Use the benefits of online advertising 3. Diversify channel mix 8
  9. 9. In the world of marketing, targeting is king. And in the world of targeting, data rules! 9
  10. 10. What is big data? In IT, big data consists of datasets that grow so large that they become awkward to work with on-hand/manual data management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing 10
  11. 11. What is big data? Data Infrastructure Insights & Analysis Media Performance Gamer iQU Audience Insight 1st Party Data Audience Forecasting Data Management Platform - Behavioral Data - Conversion Events - Appended Data Decisioning Rules Engine Segment Builder Ad Optimization Predictive Optimization LP Optimization 3rd Party Data Secure and Private Environment Media Optimization - Numerous 3rd party Bidding Optimization data relationships 11
  12. 12. So how can big data help? 12
  13. 13. In the World of targeting, data rules This is Mae Santos, she is Australian, lives in the Netherlands and loves playing Thirst of Night (kabam). Thirst of Night (MMORTS) Target audience (2 properties): male, 18-38 What did the ad look like that brought her into the game? 13
  14. 14. In the World of targeting, data rules She viewed the ad on yahoo.co.au from the Netherlands Her sign-up time was 1.1 minutes She completed tutorial in 6.8 minutes Her first payment was after 27 days … 14
  15. 15. If demographic- and geo-targeting are not good enough anymore…. …how else do you build meaningful segments to target? 15
  16. 16. How to build meaningful segments
  17. 17. How to build meaningful segments
  18. 18. How to build meaningful segments
  19. 19. How to build meaningful segments
  20. 20. How to build meaningful segments
  21. 21. How to build meaningful segments
  22. 22. How to build meaningful segments
  23. 23. How to build meaningful segments
  24. 24. How to build meaningful segments
  25. 25. The look-a-like Strategy
  26. 26. I only have “small” data. Where can I start? 26
  27. 27. 5 steps to improve targeting Step 1: Create ads for 4 Segments plus a control group (broad appeal) Control Group
  28. 28. 5 steps to improve targeting Step 2: Verify Segments 28
  29. 29. 5 steps to improve targeting Step 3: Track behavior advert CPM CTR registration-rate return-rate CPRU CPPU* Killer1 $2,50 0,33% 17,95% 32,14% $13,13 $87,54 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 Achiever1 $2,50 0,65% 12,80% 44,90% $6,74 $44,96 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 Explorer1 $2,50 0,20% 18,65% 18,18% $37,81 $252,08 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 Socializer1 $2,50 0,17% 19,25% 14,17% $55,55 $370,31 control1 $2,50 0,42% 14,05% 20,03% $21,15 $141,01 *CPPU calculated with 15% conversion from active user 29
  30. 30. 5 steps to improve targeting Step 4: Evaluate Segments 1.61 3.13 1 0.38 0.56 30
  31. 31. 5 steps to improve targeting Step 5: Find look-a-like media 13% registration rate 45% return rate 15% customer rate* 18% registration rate 32% return rate 15% customer rate* 31
  32. 32. What to do? 1. Get a deep understanding of your user types (who is playing and how do they behave) 2. Use the benefits of online advertising (target and measure) 3. Diversify channel mix (find appropriate targets across all archetypes) 32
  33. 33. Thank You! E: oliver.kern@iqu.com T: @freewebgames 33

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