Many people do not realize how current games rely on data and analytics, so significantly, to become successful. We'll show you how the world's best-selling PC/Console and mobile game developers utilize data and game analytics to improve the player experience and marketing of their games.

1. Data Science Club #3
Why Successful Games Need Analytics
Ivan Trancik, CEO @ Cellense
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2. Data Science Club #3
Agenda
1. Introduction
2. Who is behind successful games?
3. How to apply analytics to games?
a. Market research (Nex Machina)
b. Player Experience (Hill Climb Racing 2)
c. Monetization (Unkilled)
4. Q&A

3. Data Science Club #3
Hello, my name is Ivan (ivan.trancik@cellense.com)
Serial Big-Data entrepreneur
Co-founder @ Infinario (now Exponea)
● Real-time Marketing Cloud
● Maybe you’ve already heard about it :-)
Founder & CEO @ Cellense, BuffPanel
● Full-stack Game Business Analytics
● Bootstrapped, 10+2 employees
● 3 Top #100 Grossing Mobile Games (US)
● 3 Top #1 Best-selling PC Games

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About Cellense

5. 1. Introduction - Gaming Market

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Introduction - Global Gaming Market

7. 2. Who is (not) behind successful games?

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Indie developer?

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Marcus “Notch” Persson (Mojang) - Minecraft (sold for $2.5 billion)

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Ilka Paananen (Supercell) - Clash Royale ($10 billion valuation)

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Marek Rosa (KeenSWH) - Space Engineers (2.5 millions copies)

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Šimon Šicko (Pixel Federation) - Diggy’s Adventure (30+ million EUR revenue 2017)

13. 3. Analytics & Games

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Games & Data
Games:
1. Global B2C type of product
2. Work only in scale
3. Digital (& online) by design

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Games & Data
Games:
1. Global B2C type of product
2. Work only in scale
3. Digital (& online) by design
=> vast amounts of valuable data!

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Games & Data - Applications
Games:
1. Global B2C type of product
2. Work only in scale
3. Digital (& online) by design
=> vast amounts of valuable data!
=> interesting optimizations on all fronts to be made :-)

17. 3.a Market Research

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Market Research - Nex Machina (Steam, PS4)

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Market Research - Nex Machina (Steam, PS4)

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Market Research - Nex Machina (Steam, PS4)

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Market Research - Nex Machina (Steam, PS4)
Hard questions:
1. Why so underwhelming sales?
a. PR too small?
b. Niche too small?
2. What did more successful games do differently?

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Market Research - Nex Machina (Steam, PS4)
Data sources
1. SteamSpy
2. SteamAPI
3. Google Trends
4. Nex’s data

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Market Research - Nex Machina (Steam, PS4)
Nex clearly outperformed median game at much higher price
point.
Niche overview:

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Market Research - Nex Machina (Steam, PS4)
Out of over 1000 games in its niche, only 3 (+Ruiner) relevant
games had better sales than Nex!

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Market Research - Nex Machina (Steam, PS4)

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Market Research - Nex Machina (Steam, PS4)
● General info
● #owners
● Price
● Playtime total
● Userscore
● Scorerank
● Developer
● Pre-release
○ News articles timeline
○ Pre-release search trends
● Post-release search trends
● Release info

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Market Research - Nex Machina (Steam, PS4)

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Market Research - Nex Machina (Steam, PS4)
News articles mentioning Helldivers pre-launch
The peak in news count was almost 10 months before release. Then there was steady
influx of new articles, with bumps every 3-4 months.

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Market Research - Nex Machina (Steam, PS4)
News articles mentioning Nex Machina pre-launch
The peak in news count was almost 6 months before release. Coverage was comparable
to other games.

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Market Research - Nex Machina (Steam, PS4)
Organic interest for Helldivers pre-launch
PR push resulted in steady interest in the upcoming months.

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Market Research - Nex Machina (Steam, PS4)
Organic interest for Nex Machina pre-launch
PR haven’t resulted into any significant organic interest.

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Market Research - Nex Machina (Steam, PS4)

33. 3.b Player Experience

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Hill Climb Racing 2 - about
Fingersoft
Released Q4 2016
iOS & Android
multiplayer racing game
120 million players
(HCR1 over 700 millions)

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Hill Climb Racing 2 - gameplay
Fingersoft
Released Q4 2016
iOS & Android
multiplayer racing game
120 million players

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Very short soft-launch (8 weeks)
“Grow KPIs as much as possible”
=> Roadmap prioritization based on the data!
=> FTUE / Early Retention Only
Retention

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Level progression funnel - wins only
Retention - Level balancing

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Level progression funnel - w/ drop-off after win
Retention - Level balancing

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Churn rate - for how many players is the level last (after win & loss)
Retention - Level balancing

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Fail rate & failed-over-passed rate - how many times players fail for one completion?
Retention - Level balancing

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FUU factor - is losing frustrating or hopeful?
Retention - Level balancing

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First time fail - at which level player loses the first time / loses all lives for the first time
Retention - Level balancing

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Play time - how long does it take to win or lose?
Retention - Level balancing

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Crucial business bottleneck: early matches after player loses
HCR2 is a PvP game => let’s rebalance matchmaking!
Retention

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Tweaking win-rate to optimize retention.
What’s the best win-rate for a game like HCR2? 50%? 60%? 80%?
Retention

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Tweaking win-rate to optimize retention.
What’s the best win-rate for a game like HCR2? 50%? 60%? 80%?
=> Let’s try them all :-)
Retention

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Retention

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Retention
=>

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Early-retention
● Do a battery of player drop-off tests across multiple variables to be sure you’re
always prioritizing the most important issues
● Always confirm hypotheses by A/B tests
Retention - Summary

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LEVEL BALANCING CHALLENGES
- find issues in level design
- optimize difficulty curve
- balance revenue against churn
- improve design of blocker levels
Retention - Level balancing

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LEVEL BALANCING CHALLENGES
- find issues in level design
- optimize difficulty curve
- balance revenue against churn
- improve design of blocker levels
SOLUTION
- insights based on level balancing analyses
Retention - Level balancing

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LEVEL BALANCING CHALLENGES
- find issues in level design
- optimize difficulty curve
- balance revenue against churn
- improve design of blocker levels
SOLUTION
- insights based on level balancing analyses
Retention - Level balancing
ANALYSES
- level progression funnel
- win & fail rate
- failed-over-passed rate
- churn rate (after win & loss)
- time spent per fail & win
- game specific
- boosters used
- stars achieve
- first time fail
- …

53. 3.c Monetisation

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Huge topic
● Retention
● Core Game design
● Currency spend onboarding
● Economy Balancing
...
● Live-ops Offers
Monetization

55. Game Executive 2017
Monetization - Live-ops Offers

56. Game Executive 2017
Monetization - Live-ops Offers
STP Model
Well describes the process in
these questions:
● WHO?
● HOW MUCH?
● HOW OFTEN?
● WHAT?

57. Game Executive 2017
Monetization - Naive approach (Segmentation)
Simple segmentation based on spend
Advantages:
● Easy to understand
● The most widely used
● Enables basic targeting

58. Game Executive 2017
Monetization - Naive approach
Simple segmentation based on spend
Disadvantages?

59. Game Executive 2017
Monetization - Naive approach (Segmentation)
Simple segmentation based on spend
Disadvantages:
● Not taking into account different
spending patterns at the same
cumulative spend
● Not answering “WHAT?”
at all
● Not taking player’s activity into
an account

60. Game Executive 2017
Monetization - Business Analytics approach (Segmentation)
RFM Segmentation
Recency, Frequency and Monetary value
● Directly models purchasing behavior
● Great for predicting purchase
effectiveness
● Easy to understand and apply in content
creation process
● Basis for targeted offers
● Still no answer to WHAT?

61. Game Executive 2017
Monetization - Business Analytics approach (Segmentation)
Player Progression Segmentation
Players in the game are not the same -
● They unlock different content
● Progress to different points in the story mode
● Different split between game modes
● Different approach for spending currencies.

62. Game Executive 2017
Monetization - Business Analytics approach (Segmentation)
RFM Segmentation Player Progression Segmentation

63. Game Executive 2017
Monetization - Business Analytics approach (Targeting)
Number of all segments can be pretty high - we can focus only on a few
● Number of players
● Their payment potential
● (Un)-Availability of content
● Spending habits (which ones are spending premium currencies the most)

64. Game Executive 2017
Unkilled - about
Madfinger Games
Released Q3 2015
iOS & Android
zombie FPS with PvP
6 million players

65. Game Executive 2017
Unkilled - gameplay
Madfinger Games
Released Q3 2015
iOS & Android
zombie FPS with PvP
6 million players

66. Game Executive 2017
Monetization - Business Analytics approach (Example Targeting)
Identified Targetings
● Competitive Hard-core Non-payers
● First-time Payers without Premium Content
● Elite Spenders
● Newbies & At Risk Players
● Hooked Non-payers

67. Game Executive 2017
Monetization - Business Analytics approach (Example Targeting)
Identified Targetings
● Competitive Hard-core Non-payers
● First-time Payers without Premium Content
● Elite Spenders
● Newbies & At Risk Players
● Hooked Non-payers

68. Game Executive 2017
Monetization - Business Analytics approach (Example Targeting)
Competitive Hard-core Non-payers
● Last two story tiers.
● Ranked in PvP
● Already completed at least 1 rare or epic weapon
● Interaction with Premium Currency spending

69. Game Executive 2017
Monetization - Business Analytics approach (Example Offer)
Competitive Hard-core Non-payers
● $5 Price tag (From RFM segmentations)
● Communicate Extra Value for Competitive Players
● Offer stuff they already like to use

70. Game Executive 2017
Monetization - Business Analytics approach (Example Offer #1)
4 VIP chests + 2 bonus VIP chests (hook)
Regular value is 4 VIP chests for $5, if offer included only
chests it should be interesting
Random hero skin (incentive)
Every player has at least 1-2 heroes at this stage.
12x combination of VIP gadgets (incentive)
VIP gadgets are powerful for PvP, 12 gadgets should suffice
for 12 matches which is plenty

71. Game Executive 2017
One-time crafted offers
● Created based on an actual player’s payment potential and their current game
progression
● Confirmed by A/B tests
Monetization - Results

72. Data Science Club #3
● Player segmentation can be a very effective tool to drive the revenue
● 2x-10x revenue during live-ops events
=> Could be as much as 80% of the revenue!
Monetization - Results

73. => WE’RE HIRING! <=
ivan.trancik@cellense.com