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Free2Play 
Obtaining tangible results 
through action-oriented 
analytics 
Maxime Montasheri 
Director of Publishing 
Playsoft 
October 2014
About Playsoft 
Key facts: 
• Funded in 2004 
• Around 100 employees on 2 locations (Paris France, Gdansk Poland) 
• Game development studio and porting house 
Games services 
World class games creation 
and postproduction services 
Publishing 
We produce and publish AAA 
and casual mobile games 
Gaming agency 
We help you promote your 
brand through gaming
Free2Play
Virality 
Free2Play system 
Monetization 
Engagement 
AUDIENCE 
Acquisition 
Retention 
Building success: 
1. Retention through 
engagement 
2. Virality 
3. Monetization & 
Acquisition
Making money with Free2Play 
Acquisition cost 
Player 
Lifetime value 
Engagement 
Oh my god! The Balance is 
positive, let’s pour in the 
MILLIONS!! 
retention 
monetization 
License 
Store 
support 
Virality 
PR
Free2Play fundamentals 
If all this is unfamiliar… here is a reading recommendation 
Free-to-Play: Making money from games 
you give away 
By Will Lutton 
This book is a quick overview of the reason 
why Free2Play works, and what are the 
most important aspects you should 
consider when trying to build a successful 
free2play game.
Analytics
Free2Play use of analytics 
1. Monitor business 
performance 
2. Optimize business 
performance by guiding 
production efforts
Analytics in the real world – common pitfalls 
o Poor implementation of tagging plans 
o Lack of trust in results 
o Can’t get useful information 
o No action is taken
Common (bad) approach observed in the trenches 
Tagging Launching Thinking 
- List events 
- Find things to track 
- Implements tags 
- Access data you can get easily 
- Try to build a graphic 
- Ooops!! we can’t get/display 
this interesting info we need 
- Ooops!! tags have been 
implemented incorrectly and 
data is incorrect
Analytics: a new healthy approach 
Thinking 
Tagging & 
testing 
Softlaunch 
& iterating Launching
Thinking 
Tagging & 
testing 
o Business questions 
o Subquestions 
o Graphics mockup 
o Relevance check 
o Analytics package limits 
o Enrich 
Softlaunch 
& iterating Launching
Thinking 
o Consolidate tagging plan 
o Implement tagging plan 
o Test tagging plan 
Tagging & 
testing 
Softlaunch 
& iterating Launching
o Softlaunch 
o Investigate and cross-check 
findings 
o PRIORITIZE and ACT 
o Iterate 
Thinking 
Tagging & 
testing 
Softlaunch 
& iterating Launching
Thinking 
Tagging & 
testing 
Softlaunch 
& iterating Launching
Analytics 
Tips N Tricks
Insight into how an analytics package works 
Client Game 
EventA 
Parameter1 
Parameter2 
Parameter3 
EventB 
Parameter1 
Parameter2 
Parameter3 
EventA 
Parameter1 
Parameter2 
Parameter3 
EventB 
Parameter1 
Parameter2 
Parameter3 
…. 
…. 
…. 
…. 
Batch upload at 
start or end 
session 
Events collection 
Game logic 
Analytics server platform 
Raw Events buffer 
Aggregation 
DB 
storage 
Web interface 
Calls to 
analytics 
API when 
events 
occur 
load data
Limitation of free analytics solutions 
Limitation Typical 
limit 
Workaround 
#event types 300 Could fuse but best is to reduce number 
of event 
#parameters per event type 10 Split into 2 events 
typically start/end of session events 
#parameter values 500 Define discrete values in code 
No unique users count for params - Create single occurrence event 
Impossible to cross-analyze 
- Use raw data 
parameters values 
Fuse with param names/values 
Lag in consolidation process - Be patient or use paid package  
Values are consolidated at 
- Use raw data 
calendar aggregates (week, 
or switch to paid package 
month)
Raw data is really powerful! 
o Removes limitations 
o No aggregation 
o Backtrack to real sessions and user events 
o Getting raw data is possible 
o Extract from analytics platform 
o Sample population 
o Player unique identifier 
o Get user counts 
o Follow users activity across sessions
Analyzing distribution - Rank-based aggregates 
30 
25 
20 
15 
10 
5 
0 
<5 5-14 15-24 25-34 35-44 45-54 55-64 85-94 95-104 
Number of players 
Number of sessions 
First purchase in the game 
11 
Lower 
decile 
90% 
players 
75% 
players 
50% 
players 
25% 
players 
10% 
players 
16 
Lower 
quartile 
25 
Median 
38 
Upper 
quartile 
50 
Upper 
decile 
30 
Average
Playsoft’s typical 
analytics structure
Playsoft’s typical analytics structure 
o Retention 
o Early retention funnel 
o Game progression retention funnel 
o Explain churn 
o Engagement 
o Length & frequency of sessions 
o Session types / path for typical game session 
o Level design - win/loss ratios 
o Balancing creates demand? 
o Player progress versus performance 
o User play style
Playsoft’s typical analytics structure 
o Virality 
o Social network connection stats 
o Requests produced / transformed 
o Posts produced / transformed 
o Monetization 
o First purchase 
o Reason for buying currency 
o Promotions efficiency 
o Ads efficiency per type 
o Whales, Dolphins & Minnows economy 
o Acquisition 
o Cohorts for each acquisition channel/period
Use a healthy approach, and you will grow! 
Let’s keep in touch! maxime.montasheri (at) playsoft.fr

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Free2 play soft launch obtaining tangible results through action-oriented analytics - maxime montasheri

  • 1. Free2Play Obtaining tangible results through action-oriented analytics Maxime Montasheri Director of Publishing Playsoft October 2014
  • 2. About Playsoft Key facts: • Funded in 2004 • Around 100 employees on 2 locations (Paris France, Gdansk Poland) • Game development studio and porting house Games services World class games creation and postproduction services Publishing We produce and publish AAA and casual mobile games Gaming agency We help you promote your brand through gaming
  • 4. Virality Free2Play system Monetization Engagement AUDIENCE Acquisition Retention Building success: 1. Retention through engagement 2. Virality 3. Monetization & Acquisition
  • 5. Making money with Free2Play Acquisition cost Player Lifetime value Engagement Oh my god! The Balance is positive, let’s pour in the MILLIONS!! retention monetization License Store support Virality PR
  • 6. Free2Play fundamentals If all this is unfamiliar… here is a reading recommendation Free-to-Play: Making money from games you give away By Will Lutton This book is a quick overview of the reason why Free2Play works, and what are the most important aspects you should consider when trying to build a successful free2play game.
  • 8. Free2Play use of analytics 1. Monitor business performance 2. Optimize business performance by guiding production efforts
  • 9. Analytics in the real world – common pitfalls o Poor implementation of tagging plans o Lack of trust in results o Can’t get useful information o No action is taken
  • 10. Common (bad) approach observed in the trenches Tagging Launching Thinking - List events - Find things to track - Implements tags - Access data you can get easily - Try to build a graphic - Ooops!! we can’t get/display this interesting info we need - Ooops!! tags have been implemented incorrectly and data is incorrect
  • 11. Analytics: a new healthy approach Thinking Tagging & testing Softlaunch & iterating Launching
  • 12. Thinking Tagging & testing o Business questions o Subquestions o Graphics mockup o Relevance check o Analytics package limits o Enrich Softlaunch & iterating Launching
  • 13. Thinking o Consolidate tagging plan o Implement tagging plan o Test tagging plan Tagging & testing Softlaunch & iterating Launching
  • 14. o Softlaunch o Investigate and cross-check findings o PRIORITIZE and ACT o Iterate Thinking Tagging & testing Softlaunch & iterating Launching
  • 15. Thinking Tagging & testing Softlaunch & iterating Launching
  • 17. Insight into how an analytics package works Client Game EventA Parameter1 Parameter2 Parameter3 EventB Parameter1 Parameter2 Parameter3 EventA Parameter1 Parameter2 Parameter3 EventB Parameter1 Parameter2 Parameter3 …. …. …. …. Batch upload at start or end session Events collection Game logic Analytics server platform Raw Events buffer Aggregation DB storage Web interface Calls to analytics API when events occur load data
  • 18. Limitation of free analytics solutions Limitation Typical limit Workaround #event types 300 Could fuse but best is to reduce number of event #parameters per event type 10 Split into 2 events typically start/end of session events #parameter values 500 Define discrete values in code No unique users count for params - Create single occurrence event Impossible to cross-analyze - Use raw data parameters values Fuse with param names/values Lag in consolidation process - Be patient or use paid package  Values are consolidated at - Use raw data calendar aggregates (week, or switch to paid package month)
  • 19. Raw data is really powerful! o Removes limitations o No aggregation o Backtrack to real sessions and user events o Getting raw data is possible o Extract from analytics platform o Sample population o Player unique identifier o Get user counts o Follow users activity across sessions
  • 20. Analyzing distribution - Rank-based aggregates 30 25 20 15 10 5 0 <5 5-14 15-24 25-34 35-44 45-54 55-64 85-94 95-104 Number of players Number of sessions First purchase in the game 11 Lower decile 90% players 75% players 50% players 25% players 10% players 16 Lower quartile 25 Median 38 Upper quartile 50 Upper decile 30 Average
  • 22. Playsoft’s typical analytics structure o Retention o Early retention funnel o Game progression retention funnel o Explain churn o Engagement o Length & frequency of sessions o Session types / path for typical game session o Level design - win/loss ratios o Balancing creates demand? o Player progress versus performance o User play style
  • 23. Playsoft’s typical analytics structure o Virality o Social network connection stats o Requests produced / transformed o Posts produced / transformed o Monetization o First purchase o Reason for buying currency o Promotions efficiency o Ads efficiency per type o Whales, Dolphins & Minnows economy o Acquisition o Cohorts for each acquisition channel/period
  • 24. Use a healthy approach, and you will grow! Let’s keep in touch! maxime.montasheri (at) playsoft.fr

Editor's Notes

  1. In free to play the compulsion loop is at the center of your success Build retention through engagement of your audience Make sure you can leverage your audience through virality Optimize acquisition and monetization to boost revenue
  2. TAGGING List all events in the game you can think of Think about useful stuff you could track on those events Implements tags in the game THINKING Access data you can get easily Try to build meaningful data from it Ooops we can’t get this interesting info we need Ooops tags have been implemented incorrectly and data is incorrect
  3. Business questions: list all your business questions about F2P fundamentals that can impact the game success Subquestions: build analytics oriented subquestions based that can be answered through data Graphics mockup: define how you want results displayed (what is the result graph) Relevance check: ask yourself if you really need it: will I take any action on this data? Convert to data: find a way to track the data, with the limit of your analytics system (events, parameters) Enrich: use common approach to make sure all interesting events are covered
  4. Consolidate tagging plan: provide a clear list of events and associated parameters for developers. It needs to have examples of values and names and be extremely straightforward. Implement tagging plan Tag Testing: test each individual tag through QA
  5. Softlaunch: release the game in a sample country and build the dashboard Validate you can get things you need Challenge results and find corroborating evidence on your biggest findings Investigate and cross-check findings ACT and PRIORITIZE: that is a crucial point, optimization analytics without production power to make changes is useless Iterate: there is no point in launching a F2P product that doesn’t have good fundamentals
  6. Launching: There is only one chance to make a good launch. Even though some games take off long after they have been released, your first worlwide launch is where you will get the most support from Apple, Google and Journalists… Don’t launch if your product is not ready!
  7. Removes limitations data is not aggregated you can cross-analyze parameter values no limitation in the number of value amount order-based aggregate functions can be used (see next slide) Backtrack to real sessions and user events Getting raw data: Most analytics solutions let you retrieve all events received in the last few hours. You can extract it on a server and put it in your own database. Generate and use a unique identifier for users (but not IDFA, it is forbidden to use it for this purpose) Of course this can only be done during softlaunch or on a sample of the users in production.