As game analytics continues to gain importance in the industry, there is a corresponding mass of writings and presentations becoming available. Therefore, I’ve put together another list of great new and older resources about game analytics, monetization, prediction and design, to keep you up to date with what is happening in the field. Cross-posted from the Game Analytics blog
Mike Ambinder gave an excellent presentation at the Steam Dev Days (January 15-16, 2014) about data driven decision-making. The presentation covers Valve’s approach to the acquisition, collection and interpretation of data across products and services. The emphasis on experimentation, migrating knowledge between games and operating iteratively and in a hypothesis-driven manner, is spot on.
The talk covers the infrastructure required to implement a data-driven approach to decision-making, as well as common problems, useful analyses, and lessons learnt as Valve built up their data-driven competency. The recording of this session is available on Youtube, and you can also access Mike’s slides here: Data to Drive Decision-Making
Heather Stark delivers an in-depth analysis of Candy Crush Saga, dissecting the mechanics and monetization aspects of the game. Given its one billion daily gameplays, Candy Crush is still under the intense scrutiny of everyone interested in topics such as cognitive bias, behavioral modification and conversion psychology. You can find the article on Gamasutra.
Michael Manoochehri from Google, and Luca Martinetti from Staq gave a presentation at GDC 2013 about analytics for game developers. They cover the basics of behaviour analysis, virality, user segmentation and understanding retention in near real-time using //staq and Google BigQuery. A recording of this presentation is available on Youtube.
Alex Konda writes about his experience at Ayzenberg, focusing on the nuts and bolts of F2P monetization. Along the way, he showcases some great examples of how to think in economics terms in F2P, dynamic pricing and even briefly outlines some of the core psychological theories in the domain like the flow theory and the impulse purchase theory. Read it on [a]listdaily.
Dmitry Williams talks about virality in games and how it operates, and the crucial role of social networks. He covers the basics of what virality is in a gaming context, and the key features/themes associated with it. He describes how measures such as k-factor, while great for getting an overview on the effectiveness of a campaign, condenses a lot of important information into one number, which can seem more precise than it is. By digging a bit deeper at an individual level, you’ll find out that it ignores important information about your player, notably how connected a specific player is, and her/his relative importance to the game. Read about what “going viral” means: Zombie Epidemics and You.
This is a set of slides from a lecture on game analytics from Cornell, presenting a great overview on the background of the rise of analytics in games, along with a bullet point introduction to game analytics fundamentals. This resource is great for people new to the subject, and includes great examples of practical applications: Game Design Initiative on Game Analytics.
Though Andrew Pearson focuses on the gambling industry, not computer games, this 2012 article provides an excellent introduction to the basics of predictive analytics in the context of behaviour. Pearson describes how predictive analytics work, the pros and cons, and provides a few case examples from gambling. He emphasises the development in customer analytics from simply reporting behaviour, to segmenting customers, to predicting the profitability, and finally to manipulating customer behaviour towards specific patterns that have the highest predicted profitability. Get a run-through predictive analytics in the gaming industry.
Priya Viswanathan provides a couple of useful tips for monetizing mobile game apps, focusing on the user. The blog post also includes links to other reads on the topic.
Predictive analytics is the new green, and Software Advice’s Business Intelligence site Plotting Success recently ran an interesting article on testing the accuracy of predictive models. They interviewed three top data scientists about how they test the accuracy of their predictive models.
Gamasutra interviews a range of experts in game monetization about how difficult monetization is and what in-game economies actually are. Several insights are delivered by Mythic, Execution Labs, FamousAspect and Fortumo.
As special bonus content, an updated list of books on, or with information relevant to, game analytics:
Books on Game Analytics
There are currently five books on game analytics, or very closely related to it/mentioning it, on the market (have I missed any, please let me know. Several books are in development). These can be supplemented by a few excellent texts on business intelligence and analytics in general, as well as books on data mining.
Social Game Design: Monetization Methods and Mechanics [New 2nd edition]
Authored by the highly experienced developers Tim Fields and Brandon Cotton this book focuses on the design and business side of social game development, and outlines what makes games compelling and why people will pay to play them. The book handily outlines different business models, player acquisition strategies, analytics strategies and retention considerations. Recommended for both beginners and experts in analytics who work with social/online games. An excerpt is available from Gamasutra.com.
Your freemium product generates vast volumes of data, but using that data to maximize conversion, boost retention, and deliver revenue can be challenging if you don’t fully understand the impact that small changes can have on revenue. In this book, author Eric Seufert provides clear guidelines for using data and analytics through all stages of development to optimize your implementation of the freemium model. Freemium Economics de-mystifies the freemium model through an exploration of its core, data-oriented tenets, so that you can apply it methodically rather than hoping that conversion and revenue will naturally follow product launch. Written by Eric Seufert.
This book covers a wide range of topics from psychology of players, game design techniques, how to measure analytics and most importantly, monetization tricks. In fact, considering the success of games such as Farmville, Candy Crush, Clash of Clans and Temple Run, we’re surprised there are so few books about this topic. By Will Luton.
In The Curve, Nicholas Lovell weaves together stories from disparate industries to show how smart companies are solving this puzzle. From video games to pop music to model trains, the Internet helps businesses forge direct relationships with a vast global audience by building communities and offering bespoke products and experiences. By Nicholas Lovell.
Game Analytics: Maximizing the Value of Player Data [shameless self-promotion]
Edited by El-Nasr, Drachen and Canossa, this 800-page mammoth covers a variety of topics in analytics, with a focus on behavioral telemetry and its role in game development and research. Aimed at both beginners and experts, and authored by more than 50 experts from industry and research, it covers many important bases such as game data mining, visualization, monetization and user research, as well as topics such as metrics for learning games and quantitative user testing. The sheer scope of the book means that everyone will find something of interest inside, but it should be noted that the book is aimed at providing information and coverage rather than a how-to volume. (disclaimer: I am an editor on this book and therefore horribly biased).