Smartifying the game December 2014 Iñaki Puigdollers Sabin Game data Scientist @Social Point Strata London 2017 December 2014

It worked for us, will work for you! EARLY VIDEOADS SMART OFFERS DYNAMIC BALANCING Cost 1 DS + 3 days Impact +20% Revenue Cost 1 DS + 3 days Impact +20% Lifetime value Cost 2 DS + 4 days Impact +26% Retention

3. Product vs Analytics features Travel Plan About us 2. Why are we here today? 4. What we did at SP 3. Product vs Analytics features

3. Product vs Analytics features Travel Plan About us 2. Why are we here today? 4. What we did at SP 3. Product vs Analytics features

This is me Game Data Scientist @Dragon City Previously, Data Scientist at Schibsted central offices Quite diverse background, but mainly mathematics Passionate about data & gamer to the bone!

This is me I don’t do Data Magic! Game Data Scientist @Dragon City Previously, Data Scientist at Schibsted central offices Quite diverse background, but mainly mathematics Passionate about data & gamer to the bone! I don’t do Data Magic!

Amazing People!

This is where I work How many People knows about Social Point? How many people knows about T2 owing Social Point?

3. Product vs Analytics features Travel Plan About us 2. Why are we here today? 4. What we did at SP 3. Product vs Analytics features

Invest in Analytics, Save Money! Analytics Features Few Resources High Impact What I mean is save time + money

Customer Lifecycle Marketing Analytics Features are anything that tailors the game to the individual using data CRM Intelligent Offers ANALYTICS FEATURES Must: Change the game Increase important KPIs using data not content Tailor the game to individual/group of players Dynamic pricing Predictive Analytics Customer marketing (in the game) Customer Lifecycle Marketing Analytics features also called data products, an example is the movie recommendations Netflix do to the users or items recommendation of Amazon

3. Product vs Analytics features Travel Plan About us 2. Why are we here today? 4. What we did at SP 3. Product vs Analytics features

Product features are rigid and complex One size fits all different individuals have different interests/flavors Long definition time A segment of the userbase may dislike it Revenue is uncertain Complex features Lots of people involved Feedback loops Lots of potential bugs Cost is high Time to market is high Example of product feature: fingerprint passcode introduced in iPhone 6

Based on well-known solutions Analytics features are personalized and cheaper ANALYTICS FEATURES Tailored for each user Based on data Methodology to define the dataset Content is suitable for each user More likely to convert Based on well-known solutions 1 Data Scientist + 2/3 days = 1 MVP (Minimum Viable Product) Low cost Fast MVP

Invest in Analytics, Save Money! Product Features Analytics Features 6 People 1 Mobile Developer 1 Backend Developer 1 Producer 1 QA 1 Artist 1 (Game) Designer 2 People 1 Data Scientist 1 QA Minimum team involved Time to market Variable Depends on feedback loops 2/3 days Scope The whole User base Each individual User

GREAT GAMES AND GREAT BUSINESS “Smart” games make more money PRODUCT FEATURES + ANALYTICS FEATURES GREAT GAMES AND GREAT BUSINESS COST/INVESTMENT = HIGH REVENUE UPLIFT = POSITIVE BUT UNCERTAIN COST/INVESTMENT = LOW REVENUE UPLIFT = POSITIVE AND LIKELY TO BE 10-30% Every game has this Not every game has this Analytics features are competitive advantage today in gaming industry

3. Product vs Analytics features Travel Plan About us 2. Why are we here today? 4. What we did at SP 3. Product vs Analytics features

Time to unlock the feature Increase revenue by Unlocking Videoads earlier in the game Old World Time to unlock the feature Make VAds Available NGU Explain what are rewarded Videoads Old World is a product feature

Increase revenue by Unlocking Videoads earlier in the game Old World Time to unlock the feature Make VAds Available NGU Predictas Payer? New World Shortly after register No Make VAds Available NGU Explain what are rewarded Videoads Old World is a product feature Yes Make VAds Available Time to unlock the feature

+20% Uplift in Videoads Revenue 2 people and 3 days increased Videoads revenue by 20% COST IMPACT 3 Days of development +20% Uplift in Videoads Revenue 1 Data Scientist No cannibalisation with IAP (In-App Purchases) 1 Person (content creation) 3 days + 2 people

Some days after the last purchase Increase re-conversion with Smart Offers Yes Predict if pay again? Does he/she pay again? Payer does a purchase Yes Payer No Some days after the last purchase No

+20% Uplift Payers’ LTV (LifeTime Value) 2 people and 3 days increased Payers’ LTV by 20% COST IMPACT 3 Days of development 1 Data Scientist +20% Uplift Payers’ LTV (LifeTime Value) 1 Person (content creation) 3 days + 2 people

Increase retention with dynamic difficulty balancing STEP 1 STEP 2 STEP 3 Identify players with low skill Assess how many of those are frustrated by the difficulty of the game Increase the chances of finding health potions in the game Model 1: Logistic regression for low skilled players Model 2: Logistic regression for churn probability

+26% Uplift in FDR (Following Day Retention) 3 people and 4 days increased Retention by 26% COST IMPACT 2 Days of development (each model) 2 Data Scientist +26% Uplift in FDR (Following Day Retention) 1 Person (content creation) 4 days + 3 people

It worked for us, will work for you! EARLY VIDEOADS SMART OFFERS DYNAMIC BALANCING Cost 1 DS + 3 days Impact +20% Revenue Cost 1 DS + 3 days Impact +20% Lifetime value Cost 2 DS + 4 days Impact +26% Retention