metrics driven design/ how to define just right kpi for mobile game

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Competition stiffens in mobile games sector today. Deeper data analytics becomes critical for game developers/publishers to understand details of their business operation and get maximum out of it. How to define reasonable KPIs for different types of games? And how to calculate all these metrics such as LTV, CAC, and 1-7-14-30 days Retention? How to read and analysis these metrics in different phases of a game's lifecycle? And how does these metrics play compared with industry benchmarks?Answers in this session.

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  • 大家早晨好,感谢大家放弃周末的休息时间,一大早来参加本次会议,也希望我以下的分享能够使大家有所收获。
  • metrics driven design/ how to define just right kpi for mobile game

    1. 1. How to Define Just Right KPIs for Game Operation TalkingData Leo Cui
    2. 2. TalkingData Product Line TalkingData TalkingData TalkingData Analytics Campaign Insight • Third-party mobile app • Mobile app campaign • Personalized statistical analysis tools monitoring and assessment recommendation engine/data platform mining service • Professional mobile app data analysis/consulting • iOS monitoring tool • Forecast model and service released in Jun, 2012 emulation service • Specialized product and • Currently tracking about 1 methodology for mobile million valid app activations • User attributes tagging and games per day in App Store preferences mining service “TalkingData is a professional data service platform for mobile applications, serving 2,500+ activeapps presently,with almost 1,000 apps are mobile games ”
    3. 3. • TalkingData Analytics is the fastest growing mobile data analysis platform, already covering over 5 millions devices 6 months after the official release. Monthly growth rate holds at above 100% TalkingData analytics official release published in May, 2012, the right timing to witness the high 30M growth of mobile Internet in China. 14M 7M 1M 3M 2012.5 2012.6 2012.7 2012.8 2012.9
    4. 4. Game developers needMobile game developers facing "data dilemma" continuous data analysis to enhance Operation based on products data through out the whole game life cycle Most developers dont have professional knowledge to analyze data systematically, and in the mean time, facing the Whale users Game balance Mobile game developer pressure of tight schedule, high costs of man power Paying player conversion Game release and hardware Virtual Economy Props purchase stats ... How many registrations? Player conversion/retention Data How about DAU、MAU ? Platform ……. Campaign result tracking Joint operation/release Game improvement App store tracking Player levels/progresses Marketing campaign players classified by their activeness
    5. 5. Game vendors favorite game types are changing Casual games are gradually falling out of favor evidenced by the number of games, while strategy and RPG games are becoming hotter since they are more suitable for revenue generating through IAP Data source: “Mobile App Data Analysis Q3 Report 2012 ", joint released by TalkingData and NetEase100%75%50%25% 0% Apr May Jun Jul Aug Casual RPG Strategy
    6. 6. New player day 10 retention of different types of games Desktop games excelling at retention, with more well polished products; more rough ones in other types of games, especially RPG, dragging down the whole average rate. Data source: “Mobile App Data Analysis Q3 Report 2012 ", joint released by TalkingData and NetEase100.0% 75.0% 50.0% 25.0% 0.0% New +1 +2 +3 +4 +5 +6 +7 +8 +9 +10 players Strategy Action RPG Casual Puzzle Desktop
    7. 7. Life time distribution of diff. types of games Hard core players usually have shorter life time, therefore need to be motivated by continuous flow of new contents. Desktop games have more well defined playing routes, but with lots of variations, and have higher player stickiness. Data source: “Mobile App Data Analysis Q3 Report 2012 ", joint released by TalkingData and NetEase60.00%50.00%40.00% Strategy30.00% Action RPG20.00% Casual10.00% Puzzle Desktop 0.00%
    8. 8. User preferences aggregation distribution research – hardcore player Data source: TalkingData data mining research team40.00%35.00% 战略30.00% 休闲 射击25.00% 体育 动作20.00% 益智 角色扮演15.00% 冒险 棋牌10.00% 养成 经营5.00% 模拟器 网游0.00% 角色扮演 射击游戏 动作游戏 战略游戏
    9. 9. KPI!=Superficial metrics• Superficial metrics – Cannot be changed – Non-executable Fine Superficial operation metric – Lack of benchmark• KPI – Focusing on commercial purpose – Approved by management – Executable – Benchmark available
    10. 10. CAC VS LTV?• Free• Virally• campaign Monetization (LTV) Customer Acquisition cost (CAC)
    11. 11. KPI needs standardized metrics definition Acquisition Activation RetentionACQ = F(Campaign,channel, ACT = F(First time RET = F(User guide,Users,CAC, Conv%) Experience, operation,task,alert) Usage,Design/UX)• Install / Sign-ups • DAU • DAU/MAU By campaign/channel • MAU • Retention CAC(Channel) • Next Day Activities 1 day/ Conversion (Channel) • Usage 7day• Organic Users Login times 30day• Marketing Users Login length •• Click -to- Install -to- Sync • Monthly Active Days Monthly Logins per User• Fake Users Lifetime sessions• New User Perception 1~10-day activity after Perception by Channel Install • User lifetime
    12. 12. KPI for AARRR Revenue ReferREV = F(Charge trap,whale, REF = F(Excitation,UX)Conv%) • ARPU(Monthly) • K-factor • ARPPU(Avg. Revenue per Paying • Invites User Per DAU • LTV (lifetime value) Per who send invite • • Invite accept(%) By level/By date • Times By type By types purchased Massages • Paying users(%) E-mail • New paying users • Cohort by invitee • Time/level of first charge Revenue • Whale ARPU
    13. 13. KPI Model- needs professional methodology • Ads/Campaigns• Social Networks • Publisher • PR/Forum/Download sites• Apps Store(New/update) • Traffic exchange • SEO/SEM• Lowest price promotion, Limited Free • EDM ACQUISITION • Excitation • Viral Emails & Guide 、 first Alerts time experience • User guide • Task Ads、IAP、 Freemium Degree of difficulty, time, inter ests
    14. 14. Red Infinity was established in 2010 andhas rich experience in productdevelopment and publishing. Thecompany has become one of the industryleaders in justmoney? Make one year. Metrics-driven designSNS,,SLG,Poker,PuzzleMAU 4,000,000
    15. 15. VersionsInitial release:Sep 14, 2012Current version:Nov 1, 2012Description★ TouchArcade.com HOTNEW GAME ★Puzzle + Battle+ Collection + EDU
    16. 16. Test in App store,Without Marketing.
    17. 17. KPI How to optimize? Dashboards and Alerts – Why did it Happen? – Advantage - Dashboards DAU Day 1 retention Day 7 retention Virtual income Marketing Users
    18. 18. The most Important Metric between Initial release.The first experienceWHY? It’s been relatively Low Day 1 Retention Alert Avg. 18.2%
    19. 19. Bad Day 1 retention,but kind of okay after day 2. Cause: new players Why ?
    20. 20. Sign up ConnectLoading
    21. 21. Bad Connetion Abruptly lost introduction
    22. 22. What can I do? Move to more reliable data center Consider domestic and overseas server distribution Simplify introduction, less steps Embellish introduction Advantage Polish pet UI to make it more attractive
    23. 23. Difficulty? Operation.Daily awardsKnow players progressPay attention to degree of difficulty of early levels
    24. 24.  Daily task Login bonus Scheduled copy Bonus pet Friends aidOnly 9 %,WHY?
    25. 25. Difficulty?
    26. 26. Make more money.A/B testDrill downWhale
    27. 27. What’s youropinions? Extra gems? Bonus pets?
    28. 28. Is it possible to let more players make purchase earlier? Compared to revenue graph, purchase isdistributed more balanced and forwarding
    29. 29. Talkingdata Game Analytics Standardized metrics Alarm monitoring Immense visual appeal – Premade PowerPoint Templates
    30. 30. 数据运营之路依然漫长!TalkingData Game Analytics Data mining • Statistics (regression analysis, association analysis) • Forecast model (revenue/active users) Data analysis • Pattern recognition (Probability of loss, probability of paying) • user segmentation (specific user group analysis) • multi-dimensional analysis (multiple dimensions combo analysis) • cohort analysis (time slice analysis)Data statistics • A/B Test (functional analysis) • Standard reports (something wrong with the game?) • Custom reports (find problem: when? where? who?) • Metrics monitoring (need any action?)
    31. 31. Sina micro-blog: Leo_CuiWeb: www.talkingdata.net Thank You

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