Game Data Analysis - Tools and Methods -- Table of Contents -- Game Data Analysis - Tools and Methods -- Credits -- About the Authors -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers and more -- Why Subscribe? -- Free Access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Errata -- Piracy -- Questions -- 1. Context and Themes in Games -- The rise of game analytics -- Themes in games -- The desire for reward -- Ownership -- Reputation -- Achievement and collection -- The desire for challenge -- Complexity and difficulty -- Competition between players -- Desire for imagination -- Discovery -- Emotions and sensations -- Immersion, story, and universe -- Desire for entertainment -- Distraction -- Romping -- From themes to engagement -- Video game as a service -- Free-to-play and engagement -- References -- Summary -- 2. Common Key Performance Indicators -- Definition and framework of Key Performance Indicators -- Criteria -- Structure -- Acquisition of new players -- Retention of players -- Monetization of players -- Working regularly with KPIs -- Summary -- 3. Environment and Tools for Data Analysis -- Typical programming environment for data mining and storage -- MySQL -- NoSQL -- Hadoop and Hive -- Tools available on the market for quick data mining -- Available free tools -- Facebook Insights -- Google Analytics -- Commercial solutions -- Kontagent -- Honey Tracks -- Flurry Analytics -- Tools available for analysis -- Open source tools -- R-Project -- Gephi -- Commercial tools -- SPSS -- Statistica -- Rapid Miner -- Tableau Desktop -- Summary -- 4. Game Analytics and Generation of Content -- Testing -- The A/B testing -- The multivariate testing -- Recommendations for good practices.

Case study - monetization pop up -- Inventory of each feature -- Concrete examples of versioning -- First example -- Second example -- Summary -- 5. Advanced Analysis and Statistical Methods -- General statistical description -- Central tendencies -- Dispersion tendencies -- Statistical distribution and laws -- Correlation and regression between variables -- Types of variables -- Chi-squared test -- Linear regression -- Logistic regression -- Machine learning -- Definition -- Supervised learning -- Unsupervised learning -- Summary -- 6. Data Visualization -- Recommendations for good practices -- Basic recommendations -- Typical data visualization tools -- Line chart -- Bar chart -- Round chart -- Heatmap -- Graphic semiology -- Typical traps of data visualization -- The choice of the scale - values on axis -- The choice of the scale - equivalence and units between variables -- Summary -- 7. Limits of Game Data Analysis -- Which game analytics should be used -- Game analytics as a tool -- Game analytics must serve your team -- When starting, focus your attention on simple practices -- What game analytics should not be used for -- Keep away from numbers -- Practices that need to be avoided -- Summary -- Index.