If you are interested in game analytics one of the best things to do early on is to read up on what other people do. While this does not result in a plan for how to implement analytics in your game, it provides useful information guiding the design of the plan. In this post we provide suggestions for some of the best material out there on game analytics. This second post focuses on presentations, research articles and relevant material around games
Game analytics has in some ways been a part of games since developers started looking at how people actually play games, i.e. from the very beginning, but it is in recent years that analytics has become more deeply integrated in game development across the indie and AAA. Unfortunately, the level of available information has not followed this rather explosive development, meaning that for a non-expert interested in analytics, finding useful information can be difficult. The goal here is to provide a guide to the literature that is available, with an emphasis on the non-expert.
Game Analytics Talks
Industry events are a great place to go to see presentations from people working with analytics from a variety of viewpoints. Analytics has in recent years become one of the major topics at the Game Developers Conference, Casual Connect, the GDC summits, Nordic Game and other big events. Most of these make the presentations available after the conference, either openly or in exchange for a small sum. There are currently somewhere between four to five dozen talks available online which focus on game analytics to a greater or lesser degree. A complete list is out of scope here, but we can mention a few:
Ramon Romero explained in detail at the Game Developers Conference in 2008 how user testing and user research go hand in hand with analytics, outlining how triangulation between methods were used to great effect during the development of the Halo series.
Georg Zoeller, lately of Bioware, showed some stunning visualizations of spatial behavioral data from the MMORPG Star Wars The Old Republic at the Game Developers Conference in 2011. A source of great inspiration for those interested in investigating player behavior to improve game design. The work of Georg and his colleagues set a new standard for spatial visualization.
Nick Lim from Sonamine gave this presentation at Casual Connect in 2011. It is one of the first presentations to openly discuss the power of more sophisticated forms of data mining such as predictive analytics in a form and format that is broadly understandable. Nick Lim surveys the range of analytic goals and methods currently deployed for social media and for games, and present predictive analytics as a general social-network analytics framework with a view towards specific results for predicting customer-specific probabilities of conversion.
Mark Gazecki from HoneyTracks gave this presentation at Casual Connect in 2012, focusing on identifying key metrics for monetization during different stages of the lifecycle of a casual/online game. One of Mark’s key points is that different metrics are important at different stages of the lifecycle of a game.
Yes, we know it is shameless self-promotion, but GA’s Anders Drachen gave a presentation at the 2012 Berlin Data Science Day on the future of game analytics, outlining some of the broader perspectives about analytics, including the ethical considerations a company needs to consider when working with personal data. Look for other great presentations from the same event from e.g. the incredibly succesful F2P provider Wooga.
Chris Wright from Games Analytics presented some of his ideas towards using analytics as a source for driving game adaptation and individual experiences at Casual Connect 2012. He discusses various ideas and solutions as well as some of the ethical consideration involved.
Jefferson Valaderez discusses analytics for F2P games on mobile platforms, and the changes needed to game design strategies in order to flourish on the mobile market, including topics such as monetization, design iteration, engagement and retention.
Outside of the industry, an increasing number of academic researchers have started looking into game analytics, and a lot of very interesting knowledge is produced, although sometimes there is the problem that academic research needs a bit of translation before it can be adopted to a development context. However, there are a wealth of ideas to be found in academic research. More than 300 research publications exist that touch on game analytics in one way or another. Here we will mention just a few. Most of these are behind publisher paywalls, but most local university libraries will have access to them. Alternatively, chase down your cousin’s wife’s brother’s wife who is a professor to get them for you. Some authors also make their publications available via their personal websites.
We will write more about these in the future, taking them up individually and in groups and describing the essential results.
Here are a couple of examples:
Analytics of Play: Using Information Visualization and Gameplay Practices for Visualizing Video Game Data (Ben Medler and Brian Magerko)
How Players Loose Interest In Playing a Game (Christian Bauckhage et al.)
Spatial Game Analytics (Anders Drachen and Matthias Schubert)
Analytics – Without the Games
Because analytics is not just used in games but rather everywhere, there is a wealth of useful material in e.g. web analytics that can be adapted and adopted for use in games. The sheer scope of material available is too big to discuss here, but we can recommend the following books as being of particular interest to anyone interested in game analytics.
Thomas Davenport and Jeanne Harris have written this excellent introduction to analytics in business, focusing on the goal of obtaining data-driven insights rather than making decisions based on gut instinct. The authors provide a good overview of analytics in business contexts, and include a number of case examples that provide inspiration to game development as well, notably in the area of performance and production analytics.
Jiawei Han, Micheline Kamber and Jian Pei are not up to the third edition of this classical textbook about data mining. This book is for those who are interested in taking their analytics a step further, and begin explore more sophisticated methods such as prediction, clustering, and machine learning in general. Readable by non-experts, used as a textbook for tertiary students.
Eric Peterson wrote this seminal guide to web analytics which democratized analytics for web sites, and brought the concept of actionable data to the masses. It is a very good introduction to web analytics, from where many of the key business metrics used in games such as DAU, MAU and ARPU have been directly derived. It is also written in straight-forward language.