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Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
Game Monetization Analytics: How to use game metrics effectively
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Game Monetization Analytics: How to use game metrics effectively

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Presentation hold on Nov 19th in Frankfurt / Offenbach at the browsergames forum 2011. …

Presentation hold on Nov 19th in Frankfurt / Offenbach at the browsergames forum 2011.
It gives you a quick intro based on examples on HOW to use game analytics and metrics effectively.

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  • 1. Game Monetization Analytics: How to use game metrics effectivelyBrowsergames forum 2011 – Frankfurt-Offenbach19. November 2011Tom Sente, CEO - HoneyTracks GmbH
  • 2. Game Analytics Why it mattersGames portfolio monetization (example from 6Waves)* DAU vs ARPU 3,50 3,00 ARPUs vary 2,50 significantly within 2,00 GAME GENRES. ARPU Game analytics 1,50 can help you to make the most of 1,00 your game 0,50 0,00 -500.000 0 500.000 1.000.000 1.500.000 2.000.000 2.500.000 3.000.000 Management Gambling DAU (Daily Active User) Social RPG Mini-games Caretaking Copyright HoneyTracks * Source: 6waves.com/ 2
  • 3. Game AnalyticsMarket insiders view analytics as increasingly important “As more free-to-play games become the norm and selling virtual goods becomes the way to make money, game companies are relying more and more on a small fraction of players (typically 1 to 3 percent) paying to level up or for that shiny new virtual sword. Finding that 1 to 3 percent of players or getting more to pay for virtual goods can have a big impact on game revenues.” (TechCrunch, 6 April 2010) “Virtual economy optimization is now becoming a core competency as competition stiffens.” (Justin Smith, Inside Social Networks, Speech at Casual Connect 2010) Copyright HoneyTracks 3
  • 4. Game Analytics How to approach it right what matters in game analyticsMonitor the entire Layer by layer: It is an For themonetization funnel „peel the onion“ ongoing process whole companyEvery step matters: Aggregated metrics rarely Your game and its Each department / teamStarting with user tell the full story monetization changes has „their“ KPIsacqusition matter all the time Actionable insights are not Easy to use for everyone gained from aggregated metrics Over the lifetime of a game different metrics matter at a different point in time Copyright HoneyTracks 4
  • 5. Game Analytics Metrics along the entire monetization funnel Monetization Funnel User Virality Retention Conversion Revenue Generation • DAU • % viral signups • Churn-rate • Paying users • Revenue • MAU • K-factor 1-7 day • % paying users • ARPU • Sign-ups • Viral invites 1-3 mths • New paying • ARPPU • Organic • % invite accept • User lifetime users • User lifetime selected)Metrics (selected signups • Invites • DAU / MAU • # charges revenues • Mkting signups sent/DAU • User log-ins • Amount per • Virtual currency • Click-to-registr. • Viral invites by • Log-ins per charge purchased • Reg-to-active message user • Time to first • Virtual currency • Viral invites by • 3/5/10-day charge (days) spent message active users • Level of first • Virtual currency acceptance charge spent / DAU • Payment types • Virt. good types purchased Custom Metrics (your game specifics) • Track metrics along the entire monetization funnel • Both standard metrics and game-specific metrics matter Copyright HoneyTracks 5
  • 6. Game Analytics: Example I „Peel the onion“: ARPU cohort analysisScreenshot: ARPU cohort analysis Aggregate ARPU is 2 Euro Monthly cohorts show ... and we see that that ARPU actually ARPU improved from becomes 4 Euro! April to May cohort • Aggregate numbers don‘t tell the truth • As a next step we would dig deeper into the May-cohort to understand why it generated better ARPU Copyright HoneyTracks 6
  • 7. Game Analytics: Example II „Peel the onion“: Revenue & user conversionScreenshot: Revenue analysis by level Pretty effective at Majority of revenues monetizing advanced achieved in levels 20-30 users ... 0 10 20 30 40 50 0 10 20 30 40 ... but what about users in earlier levels? Can we push users into making purchases earlier? What are virtual goods that are useful at earlier levels? 0 10 20 30 40 50 Copyright HoneyTracks 7
  • 8. Game Analytics: Example III „Peel the onion“: Virtual goods economy At lower levels „food“ is being purchased relatively higher ... so this may be the virtual good, which converts users into „first time buyers“ ... even though „food“ doesn‘t play a major role in revenues We could improve the game:• Offering „food“ specials to users at lower levels• Try lower prices for food to generate more first time buyers Copyright HoneyTracks 8
  • 9. Game Analytics: Example IV „Peel the onion“: Marketing channelScreenshot: Channel profitability ... shows that Channel 1 has 50% of Channel 32 revenues despite having 2.5x in DAU Segmenting users by marketing channel ... 1 32 Marketing Channel 1 2 3 4 5 6 7 8 9 1 11 32 33 0 Marketing Channel Comparing payouts to „revenues“ shows that Channel 1 has more „lost revenue“, i.e. issues in the We could improve the game: payment process • Focus on user aquisition from ch32 • Double check payment type (SMS) and charge backs in ch1 • Switch off certain payment methods at special times 1 Marketing Channel 32 Copyright HoneyTracks 9
  • 10. Game Analytics: Example V „Peel the onion“: Whales Analysis What is her profile Who are my Whales? What, when and how much of each item works best for her? What paymentWe could improve the game does she use• See what works best for whales and offer higher variety of same type• Increase prices stepwise for new items and monitor closely• Try out special offers for items that work for other whales Different colors indicate different• Optimize payment options for her to feature/item types - “mouse over “shows details Copyright HoneyTracks 10
  • 11. Game AnalyticsAnalytics is an ongoing task • Your game changes • Monetization changes • Analytics help you to understand those ongoing changes and optimize the game effectively Copyright HoneyTracks 11
  • 12. Game AnalyticsMetrics matter for the entire company Metrics for each team Information at your fingertips • Product management • Metrics must be accessible at once • Marketing • Drill-down capability without having • Management to go back to tech-team every time • Investors • Others Easy to use Insights – not data-dumps • Every one must be able to use the • Insights that lead to action analytics system • Real time data not data-dumps • Graphical user interface • KPI and performance management Copyright HoneyTracks 12
  • 13. Game Analytics Makes fun and pays offhttp://www.penny-arcade.com/comic/2011/6/10 Copyright HoneyTracks 13
  • 14. Contact information Want to see HoneyTracks in action? Check out: www.honeytracks.com @HoneyTracksHoneyTracks GmbHSchellingstr. 3580799 München, Germany ts@honeytracks.com+49 (0)89 2872 3995 Copyright HoneyTracks 14

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