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How to define reasonable KPIs for mobile games


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Keynote speech at GDC China 2012, by Leo Cui, founder & CEO, TalkingData

How to define reasonable KPIs for mobile games

  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   recommendation  engine/ assessment  platform   data  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  million  valid  app   •  User  attributes  tagging   methodology  for  mobile   games   activations  per  day  in   and  preferences  mining   App  Store   service    “TalkingData  is  a  professional  data  service  platform  for  mobile  applications,  serving  2,500+  active  apps  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   30M   high  growth  of  mobile  Internet   in  China.   14M   7M   1M   3M   2012.5   2012.6   2012.7   2012.8   2012.9  
  4. 4. Game  developers  Mobile  game  developers  facing  "data  dilemma"   need  continuous  data   analysis  to  enhance   products   Operation  based  on    data  through  out  the Most  developers  dont    whole  game  life  cycle   have  professional   knowledge  to  analyze   data  systematically,  and   in  the  mean  time,  facing   Whale  users   Game  balance   Mobile  game the  pressure  of  tight    developer   schedule,  high  costs  of     Paying  player man  power  and    conversion   Virtual Game  release   hardware      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  NetEase  100%   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  NetEase  100.0%   75.0%   50.0%   25.0%   0.0%   New   +1   +2   +3   +4   +5   +6   +7   +8   +9   +10   players   Strategy   AcEon   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  NetEase  60.00%  50.00%  40.00%   Strategy  30.00%   Action   RPG  20.00%   Casual  10.00%   Puzzle   Desktop   0.00%  
  8. 8. User  preferences  aggregation  distribution  research  –  hard  core  player   Data  source:  TalkingData  data  mining  research  team  40.00%  35.00%   战略   休闲  30.00%   射击   体育  25.00%   动作   益智  20.00%   角色扮演   冒险  15.00%   棋牌   养成  10.00%   经营   模拟器   5.00%   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   –  Lack  of  benchmark   operation   metric  •  KPI   Downloads   –  Focusing  on  commercial   Cost/ purpose   Revenue   Registration   –  Approved  by   Conversion   management   rate   DAU   –  Executable   –  Benchmark  available  
  10. 10. CAC  VS  LTV?•  Free  •  Virally  •  campaign   Mone%za%on   (LTV)   Customer   Acquisi%on   cost   (CAC)  
  11. 11. KPI    needs  standardized  metrics  definition   Acquisition   Activation   Retention  ACQ = F(Campaign,channel, ACT = F(First time Experience, RET = F(User guide,Users,CAC, Conv%) Usage,Design/UX) operation,task,alert)•  Install  /  Sign-­‐ups   •  DAU   •  DAU/MAU   By  campaign/channel     •  MAU   •  RetenEon   CAC(Channel)   •  Next  Day  AcEviEes   1  day/   Conversion  (Channel)   •  Usage   7day  •  Organic  Users   Login  Emes   30day  •  MarkeEng  Users   Login  length   •  Engagement  •  Click  -­‐to-­‐  Install  -­‐to-­‐  Sync   •  Monthly  AcEve  Days   Monthly  Logins  per  User  •  Fake  Users     LifeEme  sessions  •  New  User  PercepEon   1~10-­‐day  acEvity  aer   PercepEon  by  Channel   Install     •  User  lifeEme    
  12. 12. KPI  for  AARRR   Revenue   Refer  REV = F(Charge trap,whale, REF = F(Excitation,UX)Conv%) •  ARPU(Monthly)   •  K-­‐factor   •  Invites   •  ARPPU(Avg.  Revenue  per  Paying   User   Per  DAU   •  LTV  (lifeEme  value)   Per  who  send  invite   •  Virtual currency purchased/spent   •  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   n tion Rete •  User  guide   •  Task   Ads、IAP、 Freemium   Degree  of   difficulty,  time,   interests  
  14. 14. Red  Infinity  was  established  in  2010  and  has  rich  experience  in  product  development  and  publishing.  The  company  has  become  one  of  the  industry   Make money?leaders  in  just  one  year.     Metrics-driven design SNS,,SLG,Poker,Puzzle MAU 4,000,000
  15. 15. Versions  IniEal  release:Sep  14,  2012  Current  version:Nov  1,  2012Descrip%on  ★  HOT  NEW  GAME  ★  Puzzle  +  BaCle    +  Collec%on  +  EDU  
  16. 16.   Test  in  App  store,Without  MarkeEng.
  17. 17. KPI How  to  op%mize? Dashboards and Alerts – Why did it Happen? – Advantage - Dashboardsn  DAUn  Day 1 retentionn  Day 7 retentionn  Virtual incomen  Marketing Users  
  18. 18. The most Important Metric between Initial release.n The first experience  n 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?n  Move to more reliable data centern  Consider domestic and overseas server distributionn  Simplify introduction, less stepsn  Embellish introduction Advantagen  Polish pet UI to make it more attractive  
  23. 23. Difficulty? Operation.n Daily awards  n Know players progress  n Pay attention to degree of difficulty of early levels  
  24. 24. n  Daily taskn  Login bonusn  Scheduled copyn  Bonus petn  Friends aid Only 9 %,WHY?
  25. 25. Difficulty?
  26. 26. Make more money.n A/B test  n Drill down  n 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  is  distributed  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_Cui    Web:   Thank  You