游戏分析学：玩家数据价值最大化

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"Game Analytics: Maximizing the Value of Player Data" 是一本由 Magy Seif El-Nasr、Anders Drachen 和 Alessandro Canossa 编辑的专业书籍，探讨了游戏分析学这一领域。该书详细介绍了如何利用玩家数据来提升游戏的价值，涵盖了游戏设计、用户体验、商业策略等多个方面。在游戏行业中，数据分析是至关重要的，因为它可以帮助开发者理解玩家的行为、偏好和需求，从而优化游戏体验，提高用户留存率，以及实现更好的商业化目标。Game Analytics 这本书深入剖析了如何收集、处理和解析这些数据，以支持决策制定，改进游戏设计，以及实现更有效的营销策略。书中各章节可能涉及的主题包括但不限于： 1. 数据收集技术：讨论了各种工具和技术，用于追踪和记录玩家在游戏中的行为，如事件跟踪和日志记录。 2. 数据分析方法：介绍了统计分析、数据挖掘和机器学习等方法，用于发现数据背后的模式和趋势。 3. 玩家行为分析：研究玩家在游戏中的活动模式，例如玩家生命周期、留存率和参与度。 4. 游戏经济和货币化：探讨如何通过数据分析优化虚拟商品销售、广告策略和订阅模式。 5. 用户体验优化：通过分析玩家反馈和行为数据，改进游戏设计，提升玩家满意度。 6. 风险管理和合规性：在利用玩家数据的同时，也关注数据保护和隐私法规，确保合规运营。此外，值得注意的是，第六章是在美国政府职务内创作的，因此不受美国版权法保护，而第二十六章则获得了加拿大女王版权的许可。这本书由 Springer 出版社出版，并提供了电子版（ISBN 978-1-4471-4769-5），具有国际标准书号（ISBN 978-1-4471-4768-8）和数字对象标识符（DOI 10.1007/978-1-4471-4769-5）。 "Game Analytics" 是游戏开发和运营团队的重要参考资料，它提供了一套全面的方法论，帮助专业人士充分利用玩家数据，以实现游戏业务的持续增长和成功。

Contributors

Erik Reinhard Max Planck Institute for Informatics , Saarbrücken , Germany

Travis L. Ross Department of Telecommunications , Indiana University ,

Bloomington , IN , USA

Sreelata Santhosh

Online Technology Group , Sony Computer Entertainment

America , San Diego , CA , USA

Matthias Schubert

Institute for Informatics , Ludwig-Maximilians-Universität ,

Munich , Germany

Magy Seif El-Nasr PLAIT Lab, College of Computer and Information Science,

College of Arts, Media and Design , Northeastern University , Boston , MA , USA

College of Computer and Information Science , Northeastern University , Boston ,

MA , USA

Janus Rau Møller Sørensen Crystal Dynamics/Square Enix, Redwood City,

CA , USA

Efstathios Stavrakis Department of Computer Science , University of Cyprus ,

Lefkosia , Cyprus

Veronica Sundstedt Blekinge Institute of Technology , Karlskrona , Sweden

Christian Thurau Game Analytics , Ballerup , Denmark

Julian Togelius Center for Computer Games Research , IT University of

Copenhagen , Copenhagen , Denmark

Mark Vaden Online Technology Group , Sony Computer Entertainment America ,

San Diego , CA , USA

Timothy Victor Fields Capcom , Chuo-ku , Osaka , Japan

Ben Weedon PlayableGames , London , UK

Michael Wimmer Institute for Computer Graphics and Algorithms , Vienna

University of Technology , Vienna , Austria

Georgios N. Yannakakis Center for Computer Games Research , IT University of

Copenhagen , Copenhagen , Denmark

Nick Yee Palo Alto Research Center , Palo Alto , CA , USA

Georg Zoeller Ubisoft Singapore , Singapore

M. Seif El-Nasr et al.

While analytics practices play a role across all aspects of a company, the

introduction of analytics in game development has, to a signi ﬁ cant extent, been

driven by the need to gain better knowledge about the users – the players. This

need has been emphasized with the rapid emergence of social online games and

the Free-to-Play business model which, heavily inspired by web- and mobile

analytics, relies on analysis of comprehensive user behavior data to drive reve-

nue. Outside of the online game sector, users have become steadily more deeply

integrated into the development process thanks to widespread adoption of user

research methods. Where testing used to be all about browbeating friends and

colleagues into ﬁ nding bugs, user testing and research today relies on sophisti-

cated methods to provide feedback directly on the design.

Operating in the background of these effects is the steady increase in the size of

the target audience for games, as well as its increasing diversi ﬁ cation. This has

brought an opportunity for the industry to innovate on different forms of play allowing

different types of interactions and contexts, and the accommodation of different

types of users of all ages, intellectual abilities, and motivations. Now, more than

ever, it is necessary for designers to develop an understanding of the users and the

experiences they obtain from interacting with games. This has marked the birth of

Games User Research (GUR) – a still emerging ﬁ eld but an important area of invest-

ment and development for the game industry, and one of the primary drivers in

establishing analytics as a key resource in game development.

Game analytics is, thus, becoming an increasingly important area of business

intelligence for the industry. Quantitative data obtained via telemetry, market

reports, QA systems, benchmark tests, and numerous other sources all feed into

business intelligence management, informing decision-making. Measures of pro-

cesses, performance and not the least user behaviors collected and analyzed over the

complete life cycle of a game – from cradle to grave – provides stakeholders with

detailed information on every aspect of their business. From detailed feedback on

design, snapshots of player experience, production performance and the state of the

market. Focusing on user-focused analytics, there are multiple uses in the develop-

ment pipeline, including the tracking and elimination of software bugs, user prefer-

ences, design issues, behavior anomalies, and monetization data, to mention a few.

1.2 About This Book

This book is about game analytics . It is meant for anybody to pick up – novice or

expert, professional or researcher. The book has content for everyone interested in

game analytics.

The book covers a wide range of topics under the game analytics umbrella, but

has a running focus on the users . Not only is ‘user-oriented analytics’ one of the

main drivers in the development of game analytics, but users are, after all, the

people games are made for. Additionally, the contributions in this book – written by

experts in their respective domains – focus on telemetry as a data source for analytics.

1 Introduction

While not the only source of game business intelligence, telemetry is one of the

most important ones when it comes to user-oriented analytics, and has in the past

decade brought unprecedented power to Game User Research.

The book is composed of chapters authored by professionals in the industry as

well as researchers, and in several cases in collaboration. These are augmented with

a string of interviews with industry experts and top researchers in game analytics.

This brings together the strengths of both worlds (the industry and academic) and

provides a book with a broad selection of in-depth examples of the application of

user-oriented game analytics. It also means the book presents a coherent picture

of how game analytics can be used to analyze user behavior in the service of stake-

holders in both the industry and academia, including: designers who want to know

how to change games for building ultimate experiences and boosting retention,

business VPs hoping to increase their product sales, psychologists interested in

understanding human behavior, computer scientists working on data mining of

complex datasets, learning scientists who are interested in developing games that

are effective learning tools, game user research methodologists who are interested

in developing valid methods to tackle the question of game user experience mea-

surement and evaluation.

Chapters in this book provide a wealth of experiences and knowledge; the urging

purpose behind the book is to share knowledge and experiences of the pros and cons

of various techniques and strategies in game analytics – including different collec-

tion, analysis, visualization and reporting techniques – the building blocks of game

analytics systems. In addition, the book also serves to inform practitioners and

researchers of the variety of uses and the value of analytics across the game lifecycle,

and about the current open problems. It is our ultimate goal to stimulate the existing

relations between industry and research, and take the ﬁ rst step towards building a

methodological and theoretical foundation for game analytics.

1.3 Game Analytics, Metrics and Telemetry: What Are They?

In this book you will see the following words often repeated: game metrics , game

telemetry and game analytics . These terms are today often used interchangeably,

primarily due the relative recent adoption of the terms analytics, telemetry and

metrics in game development. To clear away any confusion, let us quickly de ﬁ ne

them. Game analytics is the application of analytics to game development and

research. The goal of game analytics is to support decision making, at operational,

tactical and strategic levels and within all levels of an organization – design, art,

programming, marketing, user research, etc. Game analytics forms a key source of

business intelligence in game development, and considers both games as products,

and the business of developing and maintaining these products. In recent years,

many game companies – from indie to AAA – have started to collect game telemetry .

Telemetry is data obtained over a distance. This can, for example, be quantitative

data about how a user plays a game, tracked from the game client and transmitted to

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