1. Data centric Design & Operation
A data-driven and scientific approach for game business
Nguyễn Chí Hiếu - Japan Dept – VNG Corporation
2. Table of content
Methodology of data-centric approach
What is data ?
Disclaimers
Unit economy
3. Methodology of data centric approach
Japanese Methodology & Principle buzzword:
Kaizen
Just-in-time principle
4. Methodology of data centric approach
Good at Math Bad at Math
Opposite of Good at Math is not good at Literature or Creativity
Data-Centric # Limitation of Creativity
5. What is data ?
Is this the “data” we looking for ?
7. Unit Economy
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
Acquisition
Revenue per User
Retention
Monetization
Life Time Value
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. Acquisition – Viral K-factor
K-factor measurement needs reliable viral mechanic.
Viral is becoming less and less effective.
10. Unit Economy
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
Acquisition
Revenue per User
Retention
Monetization
Life Time Value
11. Retention
Let’s have a look at how new users stay in our games.
12. Retention
Percentage of staying user/total user
100.00%
90.00%
80.00%
28-02-12
70.00%
27-02-12
60.00%
26-02-12
50.00%
25-02-12
40.00%
24-02-12
30.00%
= 23-02-12
20.00%
10.00%
0.00%
Date 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28
Normalization chart for user retention over 1 month on daily basis.
13. Retention
Staying user
45000
40000 40945
35000
30000
25000 Staying User
20000
15000 14,318
10000
5000 6,883
0
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Normalization chart for user retention over 1 month.
How do we keep user ?
How did they leave ?
14. Retention
Begging the players: “Don’t leave me, I can change for you” ?
15. Retention
Lock them up ?
Any better idea ?
Let’s stay by asking ourself: “Why do users stay ?”
16. Retention
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.
……
17. Unit Economy
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
Acquisition
Revenue per User
Retention
Monetization
Life Time Value
18. Monetization
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 ?
19. Unit Economy
Profit = ( Revenue per User – Cost per User ) X Number of User
Number of User
Acquisition
Revenue per User
Retention
Monetization
Life Time Value
20. Life Time Value
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
21. Life Time Value – User Life Time
Staying user
45000
40000 40945
35000
30000
25000 Staying User
20000
15000 14,318
10000
5000 6,883
0
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Normalization chart for user retention over 1 month.
22. Life Time Value – User Life Time
Projecting object lifetime is an old problem.
24. Life Time Value - Segmentation
Segmentation criteria
Daily cohort basis.
Marketing Campaign basis.
User source.
User behavior.
User Demographic.
25. Life Time Value - Segmentation
Banner A user LTV: 1$
Banner A LTV: 1,000$
Banner A new users: 1,000
Banner A Profit: 500$
Banner A cost: 500$
Banner B new users: 5,000
Banner B user LTV: 0.1$
Banner B cost: 1,000$
Banner B LTV: 500$
Banner C new users: 500
Banner B Profit: -500$
Banner C cost: 500$
Banner C user LTV: 3$
Total new user: 6,500
Banner C LTV: 1,500$
Total banner cost: 2,000$
Banner C Profit: 1,000$
26. Unit Economy
Profit = ( Revenue per User – Cost per User ) X Number of Users
Number of Users
Acquisition
Revenue per User
Retention
Monetization
Life Time Value