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Challenge and Retention in Games

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Challenge and Retention in Games UC Irvine UC Irvine Electronic Theses and Dissertations Title Challenge and Retention in Games Permalink https://escholarship.org/uc/item/6k3357qx Author Debeauvais, Thomas Publication Date 2016 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, IRVINE Challenge and Retention in Games DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Informatics by Thomas Debeauvais Dissertation Committee: Professor Cristina V. Lopes, Chair Professor Gary Olson Assistant Professor Joshua Tanenbaum 2016 Parts of Chapters 3, 4, 5, and 7 c 2010-2016 ACM All other materials c 2016 Thomas Debeauvais TABLE OF CONTENTS Page LIST OF FIGURES vi LIST OF TABLES viii ACKNOWLEDGMENTS x CURRICULUM VITAE xi ABSTRACT OF THE DISSERTATION xii 1 Introduction 1 1.1 Motivation . 2 1.2 Thesis and Research Questions . 3 1.3 Approach . 3 1.4 Contributions . 6 1.5 Organization of the Dissertation . 7 2 Related Work 8 2.1 Enjoyment . 9 2.1.1 Motivations . 9 2.1.2 Player Types . 11 2.2 Retention . 13 2.2.1 Engagement . 13 2.2.2 Churn . 14 2.2.3 Longitudinal Studies . 16 2.3 In-Game Behavior . 16 2.3.1 Social Sciences . 16 2.3.2 Improving Gameplay . 18 2.3.3 In-Game Purchases . 19 2.4 Summary . 20 3 Ragnarok Online 22 3.1 Gameplay . 22 3.2 Private Servers . 25 3.3 Methods and Limitations . 26 ii 3.4 Supporting Group Play . 28 3.4.1 Tweaking Group Parameters . 29 3.4.2 The who Command . 29 3.4.3 Warpra and Healer . 30 3.5 Maintaining an Economy . 32 3.5.1 Rates . 32 3.5.2 The autotrade Command . 33 3.5.3 The whosell Command . 34 3.6 Improving the Quality of Life . 35 3.6.1 Character Customization . 35 3.6.2 Control Panel . 36 3.6.3 Bot Hunting . 36 3.6.4 Community Management . 37 3.6.5 Free-to-Play vs Pay-to-Win . 38 3.7 Summary . 38 4 World of Warcraft 40 4.1 Gameplay . 41 4.2 Methods and Limitations . 43 4.2.1 Dataset 1: First Survey . 43 4.2.2 Commitment Metrics and Their Limitations . 44 4.2.3 Gold Buying Metric and its Limitations . 48 4.2.4 Dataset 2: Second Survey and Gameplay Data . 49 4.3 Commitment Segmentation . 51 4.3.1 Region and Gender . 51 4.3.2 Hardcore-Casual Dichotomy . 53 4.3.3 Play Motivations . 53 4.3.4 Guild Position . 54 4.3.5 Playing With One's Partner . 55 4.4 Gold Buying Segmentation . 55 4.4.1 Demographics . 56 4.4.2 Play Motivations . 58 4.4.3 Links With Commitment . 59 4.4.4 Generalized Linear Model . 60 4.5 Progression and Churn . 64 4.5.1 Segments . 66 4.5.2 Raid progression and replays over time . 68 4.5.3 Explaining presence and churn . 72 4.6 Summary . 76 5 Forza Motorsport 4 78 5.1 Gameplay . 79 5.1.1 Cars and Modes . 79 5.1.2 Assists and Bundles . 80 5.2 Methods . 83 iii 5.2.1 Race and Achievement Datasets . 83 5.2.2 General Trends and Distributions . 84 5.3 Patterns of Assists . 85 5.3.1 First-race Bundle . 85 5.3.2 Most Frequently Used Bundles . 85 5.3.3 Assist Progression . 86 5.3.4 Assist Transitions . 88 5.4 Modeling Assist Transitions . 89 5.4.1 Scenario 1: Predicting the Success of Disabling . 90 5.4.2 Scenario 2: Characterizing a Successful Disabling . 92 5.4.3 Evaluating the Models . 93 5.5 Summary . 94 6 Jelly Splash 96 6.1 Gameplay . 97 6.2 Methods . 99 6.2.1 Dataset . 99 6.2.2 Data Overview . 100 6.3 Difficulty Spikes . 101 6.3.1 Level Difficulty . 101 6.3.2 Level Hopelessness . 102 6.3.3 XMRs and Board Rerolls . 104 6.4 Chapter Gates . 105 6.4.1 Retention . 106 6.4.2 Purchases and Spending . 107 6.4.3 Facebook Logins . 108 6.5 Energy/lives . 110 6.5.1 Sub-Sampling and Mixed-Effects Regression . 111 6.5.2 Interpreting Churning . 112 6.5.3 Interpreting Purchasing . 113 6.6 Summary . 113 7 Undisclosed Mobile Game 115 7.1 Gameplay . 115 7.2 Methods . 116 7.2.1 Telemetry Data . 116 7.2.2 Defining Churn . 117 7.3 Pre-Tutorial Churn . 119 7.3.1 Inadequate Devices . 119 7.3.2 Longer Loading Times . 121 7.4 Tutorial Churn . 123 7.4.1 Step by Step . 123 7.4.2 Churn Over Time . 124 7.5 Modeling Tutorial Churn . 127 7.5.1 Filtering and Cleaning-up . 127 iv 7.5.2 Logistic Regression . 128 7.6 Post-Tutorial Churn . ..
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