how to define reasonable kpis for mobile games
DESCRIPTION
Keynote speech at GDC China 2012, by Leo Cui, founder & CEO, TalkingDataTRANSCRIPT
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How � to � Define � Just � Right � KPIs � for � Game � Operation �
� � � �
TalkingData � Leo � Cui � �
� � Ta �
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� “TalkingData � is � a � professional � data � service � platform � for � mobile � applications, � serving � 2,500+ � active � apps � presently,with � almost � 1,000 � apps � are � mobile � games” �
• Third-party � mobile � app � statistical � analysis � tools �
• Professional � mobile � app � data � analysis/consulting � service �
• Specialized � product � and � methodology � for � mobile � games �
• Personalized � recommendation � engine/data � mining � service �
• Forecast � model � and � emulation � service �
• User � attributes � tagging � and � preferences � mining � service �
TalkingData � Analytics �
TalkingData � Insight �
TalkingData � Product � Line �
TalkingData � Campaign �
• Mobile � app � campaign � monitoring � and � assessment � platform �
• iOS � monitoring � tool � released � in � Jun, � 2012 �
• Currently � tracking � about � 1 � million � valid � app � activations � per � day � in � App � Store �
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• TalkingData � Analytics � is � the � fastest � growing � mobile � data � analysis � platform, � already � covering � over � 5 � millions � devices � 6 � months � after � the � official � release. � Monthly � growth � rate � holds � at � above � 100% �
2012.5 � 2012.6 � 2012.7 � 2012.8 � 2012.9 �
3M � 7M �
14M �
30M �
TalkingData � analytics � official � release � published � in � May, � 2012, � the � right � timing � to � witness � the � high � growth � of � mobile � Internet � in � China. �
1M �
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Game � developers � need � continuous � data � analysis � to � enhance � products � � Most � developers � don't � have � professional � knowledge � to � analyze � data � systematically, � and � in � the � mean � time, � facing � the � pressure � of � tight � schedule, � high � costs � of � man � power � and � hardware �
� �
App � store � tracking �
� Paying � player � conversion � �
Game � balance �
Game � improvement �
Mobile � game � developer �
Operation � based � on � data � through � out � the � whole � game � life � cycle �
Player � levels/progresses � players � classified � by � their � � activeness �
How � many � registrations? � How � about � DAU、MAU � ? � ……. �
Game � release �
Marketing � campaign �
Campaign � result � tracking �
Player � conversion/retention �
Whale � users �
Props � purchase � stats �
Virtual � Economy �
� Joint � operation/release �
� ... � � Data � Platform �
Mobile � game � developers � facing � "data � dilemma" �
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0%
25%
50%
75%
100%
Apr May Jun Jul Aug
Casual RPG Strategy
Casual � games � are � gradually � falling � out � of � favor � evidenced � by � the � number �
of � games, � while � strategy � and � RPG � games � are � becoming � hotter � since � they �
are � more � suitable � for � revenue � generating � through � IAP �
Game � vendors' � favorite � game � types � are � changing �
Data � source: � “Mobile � App � Data � Analysis � Q3 � Report � 2012 � ", � joint � released � by � TalkingData � and � NetEase �
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0.0%
25.0%
50.0%
75.0%
100.0%
New players
+1 +2 +3 +4 +5 +6 +7 +8 +9 +10
Strategy AcEon RPG Casual Puzzle Desktop
Desktop � games � excelling � at � retention, � with � more � well � polished �
products; � more � rough � ones � in � other � types � of � games, � especially � RPG, �
dragging � down � the � whole � average � rate. �
New � player � day � 10 � retention � of � different � types � of � games �
Data � source: � “Mobile � App � Data � Analysis � Q3 � Report � 2012 � ", � joint � released � by � TalkingData � and � NetEase �
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0.00% �
10.00% �
20.00% �
30.00% �
40.00% �
50.00% �
60.00% �
Strategy �
Action �
RPG �
Casual �
Puzzle �
Desktop �
Life � time � distribution � of � diff. � types � of � games � Hard � core � players � usually � have � shorter � life � time, � therefore � need � to � be � motivated � by �
continuous � flow � of � new � contents. � Desktop � games � have � more � well � defined � playing � routes, �
but � with � lots � of � variations, � and � have � higher � player � stickiness. �
Data � source: � “Mobile � App � Data � Analysis � Q3 � Report � 2012 � ", � joint � released � by � TalkingData � and � NetEase �
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User � preferences � aggregation � distribution � research � – � hard � core � player �
Data � source: � TalkingData � data � mining � research � team �
0.00% �
5.00% �
10.00% �
15.00% �
20.00% �
25.00% �
30.00% �
35.00% �
40.00% �
角色扮演 � 射击游戏 � 动作游戏 � 战略游戏 �
战略 �
休闲 �
射击 �
体育 �
动作 �
益智 �
角色扮演 �
冒险 �
棋牌 �
养成 �
经营 �
模拟器 �
网游 �
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KPI!=Superficial � metrics � • Superficial � metrics �
– Cannot � be � changed � – Non-executable � – Lack � of � benchmark �
• KPI � – Focusing � on � commercial �
purpose � – Approved � by �
management � – Executable � – Benchmark � available �
Fine � operation �
Superficial � metric �
DAU �
Registration �
Downloads �
Conversion � rate �
Cost/Revenue �
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CAC VS LTV?
Mone%za%on (LTV)
Customer Acquisi%on
cost (CAC)
• Free • Virally • campaign
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KPI � � needs � standardized � metrics � definition �
• Install / Sign-‐ups By campaign/channel CAC(Channel) Conversion (Channel)
• Organic Users • MarkeEng Users • Click -‐to-‐ Install -‐to-‐ Sync • Fake Users • New User PercepEon
PercepEon by Channel
• DAU • MAU • Next Day AcEviEes • Usage
Login Emes Login length
• Monthly AcEve Days
• DAU/MAU • RetenEon
1 day/ 7day 30day
• Engagement Monthly Logins per User LifeEme sessions 1~10-‐day acEvity a\er Install
• User lifeEme
Retention � Activation � Acquisition �
ACQ = F(Campaign,channel, Users,CAC, Conv%)
ACT = F(First time Experience,Usage,Design/UX)
RET = F(User guide,operation,task,alert)
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• ARPU(Monthly) • ARPPU(Avg. Revenue per Paying
User • LTV (lifeEme value) • Virtual currency purchased/spent
By level/By date By types purchased
• Paying users(%) • New paying users • Time/level of first charge • Whale
Revenue � Refer �
REV = F(Charge trap,whale, Conv%)
• K-‐factor • Invites
Per DAU Per who send invite
• Invite accept(%) • Times By type
Massages E-‐mail
• Cohort by invitee Revenue ARPU
REF = F(Excitation,UX)
KPI � for � AARRR �
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Guide � 、 � first � time �
experience �
ACQUISITION �
• Social � Networks � • Apps � Store(New/update) � • Lowest � price � promotion, �
Limited � Free �
Retention �
Emails � & � Alerts �
• User � guide �
• Task �
• Excitation �
• Viral �
KPI � Model- � needs � professional � methodology �
• Ads/Campaigns � • PR/Forum/Download � sites � • SEO/SEM � • EDM �
• Publisher � • Traffic � exchange �
Ads、IAP、Freemium �
Degree � of � difficulty, � time, �
interests �
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Red Infinity was established in 2010 and has rich experience in product development and publishing. The company has become one of the industry leaders in just one year.
SNS,,SLG,Poker,Puzzle
MAU 4,000,000
Make money? Metrics-driven design
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Descrip%on ★ TouchArcade.com HOT NEW GAME ★
Versions IniEal release:Sep 14, 2012 Current version:Nov 1, 2012
Puzzle + BaCle + Collec%on + EDU
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Test in App store,Without MarkeEng.
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n DAU n Day 1 retention n Day 7 retention n Virtual income n Marketing Users �
How to op%mize? KPI Dashboards and Alerts – Why did it Happen? – Advantage - Dashboards
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The most Important Metric between Initial release.
n The first experience �
n WHY? It’s been relatively Low �
Day 1 Retention
18.2% Alert
Avg.
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Bad Day 1 retention,but kind of okay after day 2. Cause: new players �
Why?
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Loading Connect
Sign up
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Abruptly � lost � introduction �
Bad Connetion
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n Move to more reliable data center n Consider domestic and overseas server distribution n Simplify introduction, less steps n Embellish introduction n Polish pet UI to make it more attractive �
What can I do?
Advantage
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Difficulty? Operation.
n Daily awards �
n Know players progress �
n Pay attention to degree of difficulty of early levels �
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n Daily task n Login bonus n Scheduled copy n Bonus pet n Friends aid
Only 9 %,WHY?
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Difficulty?
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Make more money.
n A/B test �
n Drill down �
n Whale �
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Extra gems?
Bonus pets?
What’s your opinions?
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Compared � to � revenue � graph, � purchase � is �
distributed � more � balanced � and � forwarding �
Is � it � possible � to � let � more � players � make �
purchase � earlier? �
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Immense � visual � appeal � – � � Premade � PowerPoint � Templates �
Standardized � metrics � Alarm � monitoring �
Talkingdata � Game � Analytics �
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Data � statistics �
Data � analysis �
Data � mining �
• � Standard � reports � (something � wrong � with � the � game?) �
• � Custom � reports � (find � problem: � when? � where? � who?) �
• � Metrics � monitoring � (need � any � action?) �
• � user � segmentation � (specific � user � group � analysis) �
• � multi-dimensional � analysis � (multiple � dimensions � combo � analysis) �
• � cohort � analysis � (time � slice � analysis) �
• � A/B � Test � (functional � analysis) �
• � Statistics � (regression � analysis, � association � analysis) �
• � Forecast � model � (revenue/active � users) �
• � Pattern � recognition � (Probability � of � loss, � probability � of � paying) �
数据运营之路依然漫长! � TalkingData � Game � Analytics �
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� Web: � www.talkingdata.net �
Sina � micro-blog: � Leo_Cui �
Thank � You �