“Game Analytics – Maximising the Value of Player Data” – book review

Executive summary

Oh, go on.   Do it.   If you’re working in this area, or nearby, you need to check this book out.  Find a bit of budget, or a well stocked library, and do it.

Why?

Although this topic has generated many mega-tonnes of slideware over the past several years,  there just isn’t much that’s been written about the topic that’s in actual honest to goodness sentences.   Game Analytics – Maximising the Value of Player Data is, to my knowledge, the first book on this topic ever, in the known universe.   So if you’re in the field, how could you possibly not be curious?

What will I be able to do once I’ve got this book that I can’t do now?

I don’t know.     Perhaps you know it all already.  But can you afford to be complacent about that?   Probably not.  So there you are:  you need to read it, if only to reassure yourself that you don’t need it.

Nitty gritty details

In UK, the book costs £90 in hardback,  £72 as an e-book.    The work has qualities that suit each format, and qualities that make each format awkward in its own special way – – but unfortunately, unlike with O’Reilly, there isn’t a dual format purchase option.  (Springer-Verlag:  it would be great if you could sort that out.)

The book weighs in at 800 pages and has, I think,  52 authors, give or take a few.  Some of the book’s most frustrating and most useful aspects flow directly from its form factor.  I bet you can guess what they are without even looking at the book.

On the upside, the book has wide expanses of rich leafy ground to truffle around in.  There is a spread of industry contributors, industry interviews, and academic contributions.  Topic coverage ranges through basics like metrics terminology, and practical issues to do with sampling, through to less ubiquitous techniques such as physiological measurement.    I think it’s unlikely you could have a really good rummage and not come up with something that you’d want to earmark for action – or at least contemplation.  If your mileage differs – let me know in the comments.

On the frustrating side,  the diversity of topics and at times unexpected differences in the surprisingness of the content make it difficult to predict exactly where in the book you might find something that has high potential value.  I have an electronic review copy and I am finding it difficult to interact with the text in the way it calls out for.   I find electronic copies brilliant for structured or keyword based retrieval, for portability, and for sharing.    But  when I want to get to grips with something that spans 800 pages,  and isn’t amenable to keyword searching,  I want a hard copy.  I think this is a book to be flicked at and dipped into on a rainy Tuesday, sitting in a comfy chair,  with a bunch of coloured sticky labels and markers to hand, for when things get good, and an ample supply of tea and biscuits.

Juicy crunchy bits

Interestingly, many of my favourite chapters are authored or co-authored by the editors.  I enjoyed the industry contributions, but my “desert island” picks – the ones I would take with me to a desert island –  would be the core content hidden in the middle in Part Three, Game Data Analysis, and in Part Four, Game Metrics Visualisation.  These are the ones that give you the tools to forge your own path. Of the five chapters in Part Three, my top picks are the ones on Game Data Mining, which gives an overview of data mining techniques as applied to game data, the chapter on Meaning in Gameplay: Filtering Variables, Defining Metrics, Extracting Features, which addresses the ever-so-key question of what to look at, and the chapter on Creating Models for Gameplay Analysis.  These are well complemented by a chapter containing an interview with Digital Chocolate, and two chapters of case studies.   In Part Four there is interesting work on Spatial Game Analytics, Visual Game Analytics, and Visual Analytics tools for analysing temporal progression and behaviour.    I am a sucker for a nice visualisation.   If it comes with a biscuit so much the better.

But there are also gems which catch the light in unexpected ways, such BioWare’s benefits from adopting developer-facing telemetry.   And it’s  certainly interesting to hear such a variety of industry voices – from Sony to Zynga.   Doing interviews to supplement practitioner-authored chapters is a method that mostly works well as a way of capturing insights from practitioners who might not otherwise contribute, either because they are too busy or too pencil-shy.

Surprises

Mercifully – for them and for us – the editors take a pragmatic approach to their subject, and seem to have almost entirely avoided the horror of getting tangled up in academic theories about the nature of games, or play.   This is a literature that has yet to deliver any delight to me – so for me it was a happy surprise that they mostly didn’t go there.

There are also things missing that I find surprising.    One is controversy.   Perhaps expert issues in the field are not yet well enough defined for any clear battle lines to be drawn.   But this situation on paper contrasts pretty sharply with the what I see on the ground (see e.g. my notes on a recent Bafta games event).   Some of these issues are covered in a chapter on stakeholders but this is a relatively passionless structural treatment.

I also wouldn’t know from reading (most of!) the book which techniques are routine, and which are hugely innovative, or about whether there is a strong mapping between measurement and analytical techniques to genres and questions which are being asked.

Wish list

I think the book would benefit from more high level conceptual organisation, a kind of graphical map that positions the other contributions, and the directions the topic is trending in.    While individual topics (e.g. the chapter on Metrics terminology)  are often well structured, there isn’t anything that lets me see at a glance what’s going on with the whole book.   Something like the O’Reilly’s recent  “Analyzing the analyzers” analysis would be interesting to see.

It would also be valuable to see  more focus on the range of actions which can be taken as the outcomes from analysis.   The book illustrates the traditional knowledge cycle of questions, answers, and new questions.    But there is not very much treatment of the role of multivariate testing in game analytics.    The focus is very much on description of phenomena, rather than analytics tightly coupled to design intervention.

Also, there is surprisingly little focus on the nuts and bolts of using analytics to support freemium (or paymium) game models.    In way this is refreshing.   But, like it or not,  and there are loud voices on both sides of the house, the drive to incorporate analytics into every new product launch is largely powered by this business model.   And there is very little in the book in the way of practical business-focussed case studies looking at how analytics can be applied to product management.    The book has its heart in games user research,  rather than business intelligence, or CRM automation as a component of design.

From an applied, commercial point of view, the fact that there are commercial third party offerings for advanced game analytics, such as those from Playnomics and Games Analytics,  is an aspect of the topic that deserves more than a passing reference  – though of course the risk here is that the content is likely to date very quickly as vendors evolve their offerings and their presentation at the same ultra-rapid pace as seen in the underlying games market itself.

Next steps

I am pretty sure the authors are or will shortly be at work on some kind of sequel, after they have mopped their brows.   From the comfort of a safe distance,  I think that one potential follow up is a really short, highly focussed, yet challenging introductory book.    That would be a great place to put the already done work on definitions,  and basic material on sampling, stakeholder analysis,  analytical workflows, and architectures.  The material also potentially suits online exercises and examples – which is not quite such a  low-effort offering,  terms of content development costs, but would be a great way of showing, hands on,  what can be done.

The big question, I think, is about the viability and usefulness of this option for future work is whether analytics is a game discipline that is going to make its way onto game training curricula, and if it does, whether that training is going to be relevant to actual praxis.  At the moment I see a trend to hire quant jocks, data scientists, strategy consultants, and MBAs for data-intensive roles.  The assumption is that  that they will pick up – or create – relevant industry trends while swimming happily around in the deep end, buoyed up by commercial and analytical experience won elsewhere.

The best way to surf this demand curve, content-wise,  is probably not via an undergraduate-friendly curriculum offering.  A hard core high pressure boot camp pitting teams of  MBAs and ML specialists against each other could be a better fit to current market zeitgeist.  Whether or not there is potential for creating a community of practice in a market where everyone is devoted to stirring their own secret sauce is debatable.   But the same holds for algorithmic trading, and they seem to manage it.