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Game Data Analysis – Tools and Methods

Book Description

Probably the best book available on the overlooked art of game data analysis, this tutorial will help you improve your products by utilizing the right tools and techniques. Written by a dedicated professional in the field.

  • Familiarize yourself with the main key performance indicators for game data analysis

  • Understand the data mining environment used for game data analysis

  • Choose reporting tools available on the market according to your needs

  • In Detail

    Publishing video games online has been gaining in popularity for a number of years, but with the advent of social networks and the use of in-game data analysis recently, its potential profitability has skyrocketed. The power of video game analytics is immensely beneficial if done well; it can provide a lot of information with a high level of relevancy.

    Game Data Analysis - Tools and Methods is a practical, hands-on guide that provides you with a large overview of the choices available performing video game data analysis. From the technical aspect of the field to its implications in terms of game design, you will be able to choose the right tools for your needs.

    This book looks at the most useful key performance indicators used in video games and then highlights the strengths and weaknesses of different solutions that are available in order to collect your data. The book will finally explain the kind of analysis you need to perform according the content of your game.

    You will learn how to generate content through the use of data analysis with A/B testing and multivariate testing. We will also take a look at the general rules of data visualization, and we will describe some of the typical traps that you should avoid when manipulating numbers. So, if you want to acquire all the basics of game data analysis, this book is ideal for you.

    Video Game Data Analysis - Tools and Methods will teach you everything you need to know in order to make the right choice when it comes to the technical solutions and methods available in the field.

    Table of Contents

    1. Game Data Analysis – Tools and Methods
      1. Table of Contents
      2. Game Data Analysis – Tools and Methods
      3. Credits
      4. About the Authors
      5. About the Reviewers
        1. Support files, eBooks, discount offers and more
          1. Why Subscribe?
          2. Free Access for Packt account holders
      7. Preface
        1. What this book covers
        2. What you need for this book
        3. Who this book is for
        4. Conventions
        5. Reader feedback
        6. Customer support
          1. Errata
          2. Piracy
          3. Questions
      8. 1. Context and Themes in Games
        1. The rise of game analytics
        2. Themes in games
          1. The desire for reward
            1. Ownership
            2. Reputation
            3. Achievement and collection
          2. The desire for challenge
            1. Complexity and difficulty
            2. Competition between players
          3. Desire for imagination
            1. Discovery
            2. Emotions and sensations
            3. Immersion, story, and universe
            4. Desire for entertainment
            5. Distraction
            6. Romping
        3. From themes to engagement
          1. Video game as a service
          2. Free-to-play and engagement
        4. References
        5. Summary
      9. 2. Common Key Performance Indicators
        1. Definition and framework of Key Performance Indicators
          1. Criteria
          2. Structure
            1. Acquisition of new players
            2. Retention of players
            3. Monetization of players
        2. Working regularly with KPIs
        3. Summary
      10. 3. Environment and Tools for Data Analysis
        1. Typical programming environment for data mining and storage
          1. MySQL
          2. NoSQL
          3. Hadoop and Hive
        2. Tools available on the market for quick data mining
          1. Available free tools
          2. Facebook Insights
          3. Google Analytics
        3. Commercial solutions
          1. Kontagent
          2. Honey Tracks
          3. Flurry Analytics
        4. Tools available for analysis
          1. Open source tools
            1. R-Project
              1. Gephi
              2. Commercial tools
              3. SPSS
              4. Statistica
              5. Rapid Miner
              6. Tableau Desktop
        5. Summary
      11. 4. Game Analytics and Generation of Content
        1. Testing
          1. The A/B testing
        2. The multivariate testing
        3. Recommendations for good practices
        4. Case study – monetization pop up
          1. Inventory of each feature
          2. Concrete examples of versioning
            1. First example
            2. Second example
        5. Summary
      12. 5. Advanced Analysis and Statistical Methods
        1. General statistical description
          1. Central tendencies
          2. Dispersion tendencies
          3. Statistical distribution and laws
          4. Correlation and regression between variables
          5. Types of variables
          6. Chi-squared test
          7. Linear regression
          8. Logistic regression
        2. Machine learning
          1. Definition
          2. Supervised learning
          3. Unsupervised learning
        3. Summary
      13. 6. Data Visualization
        1. Recommendations for good practices
          1. Basic recommendations
          2. Typical data visualization tools
            1. Line chart
            2. Bar chart
            3. Round chart
            4. Heatmap
          3. Graphic semiology
        2. Typical traps of data visualization
          1. The choice of the scale – values on axis
          2. The choice of the scale – equivalence and units between variables
        3. Summary
      14. 7. Limits of Game Data Analysis
        1. Which game analytics should be used
          1. Game analytics as a tool
            1. Game analytics must serve your team
            2. When starting, focus your attention on simple practices
          2. What game analytics should not be used for
          3. Keep away from numbers
          4. Practices that need to be avoided
        2. Summary
      15. Index