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Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
Mobile Game In China 2013-2014
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Mobile Game In China 2013-2014

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  • 1. Mobile Games in China August 2013
  • 2. 2009~2014 China’s Market Size Of Mobile Game Source: iResearch Annual Data Report On Mobile Game 2012
  • 3. ?数据Q1-Q2 2013 Sum-up?
  • 4. Share of New Titles by Genre 38.92% 16.02% 9.34% 8.95% 8.14% Casual Strategy Card Battle Action Sport RPG Card Adventure Other Card battle titles became the new hot spot. While casual titles are still CP’s first choice for entry to market. Data Source: TalkingGame
  • 5. Revenue Share by Genre 36.8% 11.7% 16.2% 20.9% 4.7% 5.0% 2.2% 0.8% 1.7% 0% 10% 20% 30% 40% Card Battle Strategy MMORPG T-RPG Action Card Tower Def Casual Other Data Source: TalkingGame
  • 6. Main stream titles are quality challenged 0% 10% 20% 30% 40% Rating for main steam titles in China Homogenization of titles are overwhelming. Copycats everywhere right after the entry of new starred titles TalkingGame Matrix for Rating Metrics for Rating: TalkingData Analytics Mobile Game Evaluation Matrix Data Source: TalkingGame RevenueShare ARPDAU Retention Rate Day7 Retention % Day14 Retention% Day14 Retention% 15-day LTV Game Mechanic User Life time Organic Users UE Marketing Forces R&D Forces
  • 7. 35% 25% 22% 14% 3% 1% 0% 50% <¥1 ¥1~$2 ¥2~¥3 ¥3~¥5 ¥5~¥10 >¥10 Titles… Passing Line: LTV¥3 80% of all titles are Non-profitable 2.3 3.2 2013 Q1 2013 Q2 CPA nearly doubled from Q1 to Q2, 2013 60%+ 80% titles still unbalanced for a new user 30 days after the acquisition CPA¥3 Data Source: TalkingGame
  • 8. 盘点 !建议 User Behavior Changes ?
  • 9. Mobile game user playing time is fragmented 20.1 18.2 18.8 16.8 17.4 16.7 15.5 15.7 16.6 15.6 14.7 14.6 15.2 10 15 20 25 2012-6 2012-7 2012-8 2012-9 2012-10 2012-11 2012-12 2013-1 2013-2 2013-3 2013-4 2013-5 2013-6 3 4 5 6 每日游戏次数 每日游戏时长 Playing time per user spends on each game is dropping significantly from Q2, 2012 although total number of game sessions per user per day is keeping steady Mins Sessions Daily Game Sessions Daily Playing Time Data Source: TalkingGame
  • 10. Day1 Retention Trend For New Plays Q1-Q2, 2013 Too many options for users in the crowded market. Significant dropping trend of the Day1 retention for each individual title 30.6% 28.4% 28.8% 28.6% 28.7% 27.1% 26.5% 25.8% 26.4% 25.6% 25.1% 25.2% 24.7% 20% 25% 30% 35% 40% 2012.6 2012.8 2012.10 2012.12 2013.2 2013.4 2013.6 Competition is intense. The red sea is coming? Data Source: TalkingGame
  • 11. 盘点 !建议Q3-Q4 Outlook ?
  • 12. LTV still keeping down 1.9 2.4 2.8 3.0 1.8 2.3 2.7 2.8 0 1 2 3 4 3-Day LTV 7-Day LTV 14-DayLTV 30-Day LTV Q1 LTV(¥) Q2 LTV(¥) Compared with Q1,Q2 LTV fell down instead of rising up as expected LTV : Revenue contribution after certain days since acquisition per new user  Q1LTV boosted by the Spring Festival season  The massive market does not look optimistic Data Source: TalkingGame
  • 13. 0 1 2 3 4 LT-1 LT-3 LT-5 LT-7 LT-9 LT-11 LT-13 LT-15 LT-17 LT-19 LT-21 LT-23 LT-25 LT-27 LT-29 LT-35 LT-45 LT-55 LT-90 IAPs and campaigns only focus on short term, perform insufficiently for long term development. Revenue growth nearly stops after 2 weeks for new users since acquisition. 3d 1.3 7d 1.8 14d 2.7 30d 2.85 90d 2.95 Main stream titles operation is unhealthy UA-focused can not push effective monetization Data Source: TalkingGame
  • 14. 盘点 !建议 Operation for Chinese Market?
  • 15. UA Channels: Fragmented 3rd Party App Store Social Network Other Ad NetworkPlatform CPA:Android ¥3~6;iOS ¥5~20 Conversion%(click->install):Android 1%~3%;iOS 1%~5% Data Source: TalkingData Campaign
  • 16. 5% 30% 5% 10% 50% 0% 20% 40% 60% Background Relationship MarketManual Taste Data Key Factors For Evaluation • Background – CP’s branding awareness and background influence deeply on PR and promotion result • Relationship – This is must-have in China – Especially with special resources • Reference – Proven references from other platforms or the market add significant credit • Manual Taste – Manually test on genre, mechanic, art, compatibility, tutorial and every aspect is the most direct way to evaluate • Data – Test with trial promotion resources and the performance data will tell the truth Mobile Game Evaluation System For Publishing Platform
  • 17. Quick Key Metrics Evaluation System Key Metrics Questions Answered Calculation Reference Organic New Self-promotion & viral capability Avg. daily organic installs >200 Day1 Retention First time experience reflection Day1 retained user counts / Day0 new user counts 30% Day 7 Retention Sustaining activation of users Day7 retained user counts / Day0 new user counts 12% Monthly Paying Rate Ratio of paid users Monthly paid user counts / MAU Depends on genre 2~5% 14-day LTV Rev contribution after 14 days per user since acquisition Rev. within 14 days from new users / Daily new user counts ¥2.5 60-day LTV / 30- day LTV Long term monetization potential 60-day LTV / 30-day LTV 1.3 Data Source: TalkingGame
  • 18. Key Metrics Evaluation & Comparison 41.2% 3.7% 9.0% 28.4% 21.8% 10.9% 39.8% 8.5% 16.3% 31.2% 24.2% 12.1% 0% 10% 20% 30% 40% 50% One-day user% Day30 Retention% Day7 Retention% Day1 Retention% 30-day Active% 7-day Active% Card Battle Genre Avg. Total Avg. Data Source: TalkingGame
  • 19. 数据观察 Succeed with Data!
  • 20. Data-driven Success 20 Data-driven Success A A RR R • Metrics System • Tool to power up • Workflow
  • 21. TalkingData AARRR Metric System 21 Refer Revenue Retention Activation Acquisition Monetization Conversion Engagement Acquisition
  • 22. TalkingData AARRR Metric System 22 • Install / Sign-ups By campaign/channel CAC(Channel) Conversion (Channel) • Organic Users • Marketing Users • Click -to- Install -to- Sync • Fake Users • New User Perception Perception by Channel • DAU • MAU • Next Day Activities • Usage Login times Login length • Monthly Active Days • DAU/MAU • Retention 1 day/ 7day 30day • Engagement Monthly Logins per User Lifetime sessions 1~10-day activity after Install • User lifetime RetentionActivationAcquisition ACQ = F(Campaign,channel, Users,CAC, Conv%) ACT = F(First time Experience, Usage,Design/UX) RET = F(User guide, operation,task,alert) Players & Channels Engagement
  • 23. TalkingData AARRR Metric System 23 • ARPU(Monthly) • ARPPU(Avg. Revenue per Paying User • LTV (lifetime value) • Virtual currency purchased/spent By level/By date By types purchased • Paying users(%) • New paying users • Time/level of first charge • Whale Revenue Refer REV = F(Charge trap,whale, Conv%) • K-factor • Invites Per DAU Per who send invite • Invite accept(%) • Times By type Massages E-mail • Cohort by invitee Revenue ARPU REF = F(Excitation,UX) Monetization Viral
  • 24. TalkingData White Paper For Mobile Game Data Analysis 24 • Standard and unified definitions of all the Key metrics based on AARRR model system • Benchmarking enabled to help generate valuable insight of your data
  • 25. Key Metrics New Player Acquisition & Tutorial Activation & Retention Engagement & Behavior IAP Drill-down Player Segmentation Right Tool to Power up Real- time
  • 26. Best Practices Retention is KING! A Data-driven F2P Card Battle Game
  • 27. Red Infinity was established in 2010 and has rich experience in product development and publishing. The company has become one of the industry leaders in just one year. MAU 4,000,000 Data-driven Workflow
  • 28. Description ★ TouchArcade.com HOT NEW GAME ★ Versions Initial release:Sep 14, 2012 Enhanced version:Nov 1, 2012 F2P Puzzle + Battle + Collection
  • 29.  DAU/MAU  Day 1 retention  Day 7 retention  Conversions(%)  Virtual Expense Behavior KPIs Tracking Measure & Analysis Solution Optimize Testify
  • 30. The key metric to track during initial stage First time experience and impression Acceptance of the theme, content, visual quality, arts… Day 1 Retention 18.6% VSAvg. Day 1 Retention for card games ~30% Benchmark:
  • 31. Bad Day1 retention rate, but steady for Day2 and subsequence. Something must be wrong with the new player initialization stage!
  • 32. 34 Load Sign up Create Character Start Tutorial Finish Tutorial Conversion Funnel for initial stage
  • 33. Frequent Connectivity FailureTutorial suddenly lost
  • 34. Step 1 – Enhancement Move to more stable IDC Dedicated server for domestic players Simplify and enhance tutorial Polish UI to gain more visual attraction Solutions Step 2 – Optimization Localize to fulfill local players’ preference Theme Core UX Art
  • 35. Testify & Ongoing Optimization
  • 36. Result of daily incentive boost, e.g. Login bonus How are core players growing in game Acceptance of difficulty settings for gaming The key metric to reflect gameplay acceptance and performance of player engaging operations
  • 37. Plenty of incentive activities Mission complete bonus Daily login bonus Free cards offer Friends alliance ⋯⋯ But Day 7 Retention 9.2% VSAvg. Day 7 Retention for card games ~15% Benchmark:
  • 38. Significant player Drop off at the growing levels(16-30) Something wrong with the gameplay design at these levels Analysis by Churning Level Distribution
  • 39. Option1: Players Power-up Higher winning rate of powerful card lottery Stronger friend alliance for early stage players More chance to get enhancing virtual items Solutions Option2: Weaken Challenges Lower monster’s numbers to bring down mission completion difficulty Easier player advancing at growing stages Day 7 Retention 13.6%Avg. A/B Analysis & Ongoing Optimization
  • 40. Test in App store,Without Marketing.
  • 41. Thanks www.TalkingGame.com A A RR R

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