Data centric Design & Operation
A data-driven and scientific approach for game business
Nguyễn Chí Hiếu - Japan Dept – VNG...
Methodology of data-centric approach
What is data ?
Disclaimers
Unit economy
Table of content
Methodology of data centric approach
Japanese Methodology & Principle buzzword:
Kaizen
Just-in-time principle
Good at Math Bad at Math
Opposite of Good at Math is not good at Literature or Creativity
Data-Centric # Limitation of Cre...
What is data ?
Is this the “data” we looking for ?
Option A
Option B
We still need a good game to start with
Data-centric: Disclaimer
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
 Acquisition
Revenue per User
 Retention
...
Acquisition – User funnels
 Everyone
 Internet user
 Gamer
 Platform user base
 Target Segment
 Ads Awareness
 Inte...
 K-factor measurement needs reliable viral mechanic.
 Viral is becoming less and less effective.
Acquisition – Viral K-f...
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
 Acquisition
Revenue per User
 Retention
...
 Let’s have a look at how new users stay in our games.
Retention
 Normalization chart for user retention over 1 month on daily basis.
=
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70...
 Normalization chart for user retention over 1 month.
 How do we keep user ?
 How did they leave ?
40945
14,318
6,883
0...
 Begging the players: “Don’t leave me, I can change for you” ?
Retention
 Lock them up ?
 Any better idea ?
 Let’s stay by asking ourself: “Why do users stay ?”
Retention
User retention at a closer look.
 How users funnel into your game.
 How do you impress your player.
 “Don’t make me thi...
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
 Acquisition
Revenue per User
 Retention
...
How we frequently look at the most important part of our business:
 ARPU : Average Revenue Per User
 ARPPU : Average Rev...
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
 Acquisition
Revenue per User
 Retention
...
 Life Time Value = Total Revenue you get from 1 user until they cease
to be your user.
Profit = (Cost per User – Life Tim...
 Normalization chart for user retention over 1 month.
40945
14,318
6,883
0
5000
10000
15000
20000
25000
30000
35000
40000...
Life Time Value – User Life Time
 Projecting object lifetime is an old problem.
Life Time Value – Poisson Distribution
Segmentation criteria
 Daily cohort basis.
 Marketing Campaign basis.
 User source.
 User behavior.
 User Demographic...
 Banner A new users: 1,000
 Banner A cost: 500$
 Banner B new users: 5,000
 Banner B cost: 1,000$
 Banner C new users...
Profit = ( Revenue per User – Cost per User ) X Number of Users
Number of Users
 Acquisition
Revenue per User
 Retention...
Thank you !
My Contact: hieunc@vng.com.vn
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Data centric Design & Operation: A data-driven and scientific approach for game business

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Data centric Design & Operation: A data-driven and scientific approach for game business

  1. 1. Data centric Design & Operation A data-driven and scientific approach for game business Nguyễn Chí Hiếu - Japan Dept – VNG Corporation
  2. 2. Methodology of data-centric approach What is data ? Disclaimers Unit economy Table of content
  3. 3. Methodology of data centric approach Japanese Methodology & Principle buzzword: Kaizen Just-in-time principle
  4. 4. Good at Math Bad at Math Opposite of Good at Math is not good at Literature or Creativity Data-Centric # Limitation of Creativity Methodology of data centric approach
  5. 5. What is data ? Is this the “data” we looking for ?
  6. 6. Option A Option B We still need a good game to start with Data-centric: Disclaimer
  7. 7. Profit = ( Revenue per User – Cost per User ) X Number of User Number of User  Acquisition Revenue per User  Retention  Monetization  Life Time Value Unit Economy
  8. 8. Acquisition – User funnels  Everyone  Internet user  Gamer  Platform user base  Target Segment  Ads Awareness  Interest  Desire  Action  Registration  Download client  Chose character  Tutorial  Play  Stay  Regular player  Payer  Regular payer  …….
  9. 9.  K-factor measurement needs reliable viral mechanic.  Viral is becoming less and less effective. Acquisition – Viral K-factor
  10. 10. Profit = ( Revenue per User – Cost per User ) X Number of User Number of User  Acquisition Revenue per User  Retention  Monetization  Life Time Value Unit Economy
  11. 11.  Let’s have a look at how new users stay in our games. Retention
  12. 12.  Normalization chart for user retention over 1 month on daily basis. = 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 28-02-12 27-02-12 26-02-12 25-02-12 24-02-12 23-02-12 Percentage of staying user/total user Date Retention
  13. 13.  Normalization chart for user retention over 1 month.  How do we keep user ?  How did they leave ? 40945 14,318 6,883 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Staying User Staying user Retention
  14. 14.  Begging the players: “Don’t leave me, I can change for you” ? Retention
  15. 15.  Lock them up ?  Any better idea ?  Let’s stay by asking ourself: “Why do users stay ?” Retention
  16. 16. User retention at a closer look.  How users funnel into your game.  How do you impress your player.  “Don’t make me think” - KISS (Keep It Stupidly Simple).  How can user understand “core design”.  Do you have Retention Features in your game cycle.  What is your Retention Feature KPIs.  1st Login to 2nd Login.  Define your Hardcore/Reg user.  …… Retention
  17. 17. Profit = ( Revenue per User – Cost per User ) X Number of User Number of User  Acquisition Revenue per User  Retention  Monetization  Life Time Value Unit Economy
  18. 18. How we frequently look at the most important part of our business:  ARPU : Average Revenue Per User  ARPPU : Average Revenue Per Paying User  DARPU : Daily Average Revenue Per Paying User  MARPU : Monthly Average Revenue Per Paying User  Conversion Rate.  Paying User Rate.  Sale charts. Is that all ? Can we do better ? Why do user pay ? Monetization
  19. 19. Profit = ( Revenue per User – Cost per User ) X Number of User Number of User  Acquisition Revenue per User  Retention  Monetization  Life Time Value Unit Economy
  20. 20.  Life Time Value = Total Revenue you get from 1 user until they cease to be your user. Profit = (Cost per User – Life Time Value) X Number of User.  Most reliable Life Time Value is historical data.  Historical data = history, you need some way to predict, or project your Life Time Value  2 most simple Life Time Value Models on Cohort basis: LTV = ARPPU x Paying Rate x User Life Time = ARPU X User Life Time LTV = ARPPU x Paying User x Paying User Life Time Life Time Value
  21. 21.  Normalization chart for user retention over 1 month. 40945 14,318 6,883 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Staying User Staying user Life Time Value – User Life Time
  22. 22. Life Time Value – User Life Time  Projecting object lifetime is an old problem.
  23. 23. Life Time Value – Poisson Distribution
  24. 24. Segmentation criteria  Daily cohort basis.  Marketing Campaign basis.  User source.  User behavior.  User Demographic. Life Time Value - Segmentation
  25. 25.  Banner A new users: 1,000  Banner A cost: 500$  Banner B new users: 5,000  Banner B cost: 1,000$  Banner C new users: 500  Banner C cost: 500$ Total new user: 6,500 Total banner cost: 2,000$  Banner A user LTV: 1$  Banner A LTV: 1,000$ Banner A Profit: 500$  Banner B user LTV: 0.1$  Banner B LTV: 500$ Banner B Profit: -500$  Banner C user LTV: 3$  Banner C LTV: 1,500$ Banner C Profit: 1,000$ Life Time Value - Segmentation
  26. 26. Profit = ( Revenue per User – Cost per User ) X Number of Users Number of Users  Acquisition Revenue per User  Retention  Monetization  Life Time Value Unit Economy
  27. 27. Thank you ! My Contact: hieunc@vng.com.vn

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