Making, combining, experimenting and inspiring at #playful13

I lucked into this conference last year when someone I know on twitter couldn’t attend.    It’s now inked into my diary for the forseeable future.  Playful describes itself as

A sticker-book of brilliant thinking designed to make you want to Make Stuff.

And it’s not wrong.

Full marks for diversity of topics.  We had mummified deer covered with beeswax, which inspired chefs into new ways of dealing with rotten plums,  a billion or so different snakes and ladders boards generated through genetic algorithms, eye popping mind-bending graphics making complexity out of simplicity, and back again, a poignant and poetic talk about boxes,  and a story about dropping out of the rat race in a virtual world.   We had real adventure playgrounds,  virtual performance art,  bananaphones, folding wheels, not terribly practical jokes on the postal service, people at Facebook dancing a marked up two step on polished concrete that based on the rhythms of a loved up couple’s Facebook posts.  We had movies of smiling engineers drilling into hardened steel with home made EMF machines.   We took a deep dive into the physical pleasures of response curves in button pressing, and the pleasurable physics of custard-punching.

What do mummified deer, dustard punching, and bananaphones have in common?  The announced theme was “playing with form”.  What I really picked up from the talks as a unifying theme was a strong feeling of joyous experimentation, and a passionate belief in the importance of experimenting as a way of opening up creativity.

All this in peaceful, beautiful Conway Hall, a London landmark of the humanist movement.  I love Conway Hall.   And I loved the event.  All the talks were interesting.   And everyone in the audience I spoke with was too.

Conway Hall

Two different talks used the same quote,  from Mike Chrisp -

Build what it is you want to build and learn as you go.

What good advice.

Many thanks to Mudlark for curating, and to the speakers*, for blowing a big, teasing, leaf-strewn wind through my mind.

* Duncan Fitzsimmon, Ann Holiday, George Buckenham, John V Willshire, Fran Edgerly, Pippin Barr, Dani Luri,  Marie Foulston, Ben Reade, Rev Dan Catt, Stephanie Posavec,  and Rob Lowe (aka Supermundane).

The recipe for Candy Crush Saga’s success: luck, skill, and puzzles is pulling in one billion daily gameplays for its f2p games, according to Reuters. Candy Crush Saga, its top performer,  is estimated to be bringing in $840k per day in the US iOS market alone, according to  Since dropped in-game advertising earlier this year and has only recently started to offer Candy Crush branded socks, it’s fair to guess pretty much all this revenue comes from in-app-purchases.

Level 1 of Candy Crush Saga

Happy times for (the trading name of the game’s developer), (the UK registered company that trades as, and’s Maltese-registered parent (Midasplayer International Holding Company).    An  IPO is thought to be brewing.   

There are, of course, detractors.  But compared to the backlash against Zynga’s monetisation tactics, the nature of the complaints is somewhat different.  Civilian comments often centre around the complaint that the pay offers sprinkled throughout the game make it too easy to rack up spend  (e.g. this LA times review).    Rather intriguingly, some people dislike the game, but pay for it anyway,  like the gizmodo commentator who called it “a simple and blatantly unoriginal time-waster” and in the same breath said they had spent money on it – but only to to get from one episode to the next.

Under-rated but essential:  luck

Luck has been hugely important to Candy Crush Saga – in two ways.

Firstly, because they got lucky.  Not even foresaw how successful the game would be.  According to an interview with games guru Tommy Palm,  in ValleyGawker,  Candy Crush Saga’s success was “nothing that we anticipated originally”.  They clearly thought it was promising, based on initial play testing and monitoring of the arcade version on,  but its reception in the market when released as a saga version on Facebook was even better than anticipated.

They then successfully  invested in further growth via advertising, and via continued development of additional levels and monetisation inducements in the game.  I have a mental image of teams of people at kitted out in brightly coloured knitted curling team outfits,  all sweeping quickly with brooms, trying to make the Candy Crush Saga stone go further, further, further along the ice….

Secondly,  the game itself requires luck as well as skill to succeed.  This can be easily misunderstood.    One analysis of Candy Crush’s design on Gamasutra, by a professional game economist, claims that early on, when you cross your first river in the saga map, the game changes from a skill game to a “money game”, in which the dominant factor is luck, and you need to buy more and more chances in order to progress.

But CCS is not a game in which you can reliably buy your way to happiness by bribing Lady Luck.  It is unlikely you could win a game without trying your best.   And this requires skill.   But mere skill is not enough, either.  Luck is also required.

This skill/luck symbiosis is one place in Candy Crush Saga where the secret sauce really bubbles and boils.   You can, if you wish, buy more chances at beating a level.   And you can buy more tries at a game.   These pay gates will give you more shots at being lucky –  and more shots at exercising your skill.  And I suspect it will sometimes give you the desired result – but not always, or possibly even not usually.

At many levels of Candy Crush, making an optimal-within-the-limits-of-human-cognitive-processing choice of moves will usually result in failure to clear a level.   And it’s my guess – as a non-purchaser – that although a pay gate is never far away, you usually can’t buy your way out of failure.   You can try to.  But I think you can buy more unhappiness much more easily than you can buy happiness.  Very scando.   But clearly effective.

By contrast, success occasionally comes unexpectedly in extremely generous measure, in an orchestral crescendo and visual extravaganza of seemingly ever increasing and never-ending awesomeness.   Wow.  I don’t smoke cigarettes but if I did I might want one.

This mixture of very tight level gating (both skill-based and chance-based) and unpredictable super-rewards is, I think, part of the appeal of Candy Crush’s gameplay.   The recipe is no where near as simple as making life difficult for people, and then offering them an easy way out by paying.  It’s much more interesting.

Skill is hugely important

Candy Crush is a game of skill.   The specific skills required of the user are relatively straightforward in principle, but difficult to implement in practice.   At least I find them so.  Your mileage may differ.  This is a quality which the co-founder, Ricardo Zacconi, calls “easy to learn and difficult to master“.

The game’s design is also skilful.   Intentionally so – clearly.  But possibly also in ways that its designers are still developing and enriching their understanding of.

Here’s what I think it does right:

a.  it is impossible to make an illegal move – the UI simply won’t allow it – and if you don’t move within a reasonably short amount of time, the UI will twinkle an option at you

  • this makes for easy on-boarding, and quickly builds a feeling of competence (which won’t persist…. but hey ho one can always hark back to those glory days)

b.  beautiful graphics and effects – what happens on the board as a result of most moves is simple, but  looks and sounds just great

  • this makes “grinding” – playing repeatedly without winning – enjoyable in itself

c.  irregular super-reward cascades – sometimes the effects of a move are just outrageously lovely and satisfying – not only in their consequences for your progress in the game, but in themselves, as effects

  • this is one of the best deployments of the powerful operant conditioning effect of variable reward intervals that I’ve yet seen

The rockstar designer and monetisation guru Michail Katkoff puts it this way, in his Game Analytics blog post:  [the] “…graphical and audio feedback that follows these combinations is simply over the top. That massive fanfare of feedback is also particularly important for our casual gamers, as they aren’t traditionally good at playing games. With this kind of gameplay feedback we can make them feel good about themselves – we can make them feel like true masters”.   My own view is that the variability of this perceptual reward is just as important as its lovely over the top quality, in facilitating the desired outcome – lots of play.  (And with that, perhaps, lots of pay.)

d.  big variety of paygates on offer – just in case, just in time, special powers, more plays, extended games, no waiting between episodes…

  • I’ve no idea which ones are most successful – but whatever floats your boat, purchase-wise, you can probably do it

e.  saga format – visualisation of level progress via a map-based progression story given structure by division into episodes

  • this is a very simple but effective way of creating a sense of visible progress and achievement out of an activity which is basically playing more and more (and usually – but not always -more difficult) variants of the same game over and over and over again
  • it is not in itself a defensible competitive advantage – it is too easy to copy – but there are experience engineering aspects of the saga that, being less obvious, might be more possible to retain early mover advantage on

f.  social facilitation – much reference is made in reviews to the importance of the  leaderboard as a social feature Facebook-connected games – but, bizarrely, nobody seems to make much reference to the positively reinforcing social mechanisms the game uses  – my friends can be rewarded when I play, and when I succeed, and I can help them at no cost to myself when they request it.  Very potlatch.

  • rewarding friends sets up both a reminder function for re-engagement for friends, as well as offering them gameplay benefits – and it shows a good understanding of human ethnomethodology, and the importance and power, across cultures, of reciprocal gifting arrangements.

g.  luck/skill mix – neither luck nor skill will get you through the game’s levels – you need both

  • the mixture, in combination with the basically attractive nature of play, and the intermittent use of super-rewards creates powerful psychological motivations – for some people – to persist in play.   I hope to have time to talk more about this, as I think it’s fascinating and poorly understood.

h.  exquisite split-second comic timing – I laugh out loud love the mischievous way the game pauses to let me contemplate and prepare for my next move, before telling me my time is up, and offering me the chance to pay for further moves.

  • an action plan interrupted creates a tension – which can be relieved by paying

i.   habit automation exploitation – when completing successive tries at a level, you select a green button to go to the next move, but when you have run out of tries, the pay button is in the same place and looks the same – except it’s pay rather than play…

  • people can easily back out if “pay” isn’t what they want to do – but my guess that this little kick onto the first step towards payment has helped more than a few people give it a go

j.   varied level progression – in general, later levels are harder, but there are odd plateaus and even reductions in difficulty, given the accumulation of skill, where progress is rapid

  • my guess about the effect of this is a kind of psychic momentum, and build up of expectation about continued progress, which, when thwarted, induces a need to bring things back to plan

k.  demanding yet snack-able

  • playing one game gives you a good workout – and an immersive  power break – but it only takes a few minutes

l.    the use of candies as game tokens, and gravity cascades as a board configuration change movement

  • feels good

If you copy all these design features wholesale, will you easily make another Candy Crush?  Almost definitely not – for several reasons.   For one thing,  I’m sure there are many aspects of the game I haven’t noticed.   And it’s more than possible I’ve noticed stuff that isn’t actually there.  It’s not just me.  People are really good at that.

For another thing, even hasn’t yet made another Candy Crush.  One nordically blunt teardown from Michail Katkoff of one of their newer titles, Pet Rescue Saga,  says it has “simply copied the mechanics from CCS without actually making sure that they fit the game”.   Ouch.  But, even though it isn’t a Candy Cross Saga, Pet Rescue Saga is a game many a studio would envy – it is successful by mortal standards.  It’s just not as jaw-droppingly successful as Candy Crush Saga.

The transplant of a mechanic from one game to another is not necessarily straightforward.  I think that design success is an emergent feature of all the components I’ve called out,  and more, working together in the right proportions.    Transplanting them to a new context is something that is even more difficult than transposing the key of a piece of music. You have to expect it to feel different, in a different context.    It’s more like transplanting a peony: there’s a big chance it won’t work.


I think  I understand some of what makes Candy Crush Saga tick.  But there are lots of things that puzzle me.

One is payment.   A biggie, eh?   I started playing Candy Crush Saga out of a desire to reverse engineer my experience into an understanding of the game’s finer points.   And I have continued to play it for fun.   But I haven’t paid.    In this I am not alone.  According to oft-quoted Tommy Palm, game guru, the game was designed so that it would be possible to work through it without paying, and indeed, of those people who make it to the top-most  level,  70% do so without spending anything.  Even a penny. (Except, perhaps if they are British.)

This means, of course, that 30% of the top-achieving players have spent money.   And who knows what percentage of people who are toiling towards the top – but don’t succeed – actually try to buy their way there?  It could be more.   It could be less.

The precise  personality factors and situational triggers that work to inspire payment are a mystery to me.   But that shouldn’t stop me from having fun guessing.  Mixing  typologies with abandon, I would guess that achievers and completer/finishers would feel the pull more strongly.    Situationally, I’d guess the almost-there-but-for-one-more-move situation would be a really strong trigger for payment, in-game, and a feeling of progress across tries before expiring free plays might tip me over to wanting to top up plays before they replenish with time.  But my puzzle is that this situation arises so very very rarely in my game play.  Usually I’m either miles out when I lose, or everything comes right.    Very rarely would any of the offered powerups make a difference.   And I like the fact that one’s playtime is limited.   I lose nothing by waiting.

Another puzzle is the massive dropoff they engineer into the tougher levels.  Tommy Palm said in his ValleyWag interview that they needed to tweak difficulty of level 65 down to the point where “only” half the users dropped out at that point.  That’s one hell of a tough gate.  Worse than Beecher’s Brook at the Grand National.    It’s really puzzling that they’d think it a good thing to lose “only” half their users – when presumably they could, without straining themselves terribly, have made it easier still.  The only way this could be a good result  is if a goodly percentage of those players paid before quitting.   More so, perhaps, than would be the case if a level was almost impossible.   I can feel a graph coming on.

Another puzzle about the game for me is that I think there is some meaning to the scalloped pattern of level difficulty that I haven’t quite understood.  Tommy Palm said that last level in an episode is said to be the most difficult – but I’m not sure that’s been my experience.   Still chewing on this, and I need to think more about it.

And finally, I’m puzzled about the style of the graphics that go with the saga level map.  The game board itself is bright and shiny, hyper-real, strongly lit with occasional sparkles.    But the saga graphics and the character that lumber around it in an extravagantly 2d way are from a different mood board.   A bit clown-sinister.  A bit ironic.  But not, perhaps, quite enough.   I wonder what work that clash and tension between the two graphic styles does, in terms of affecting the feeling-tone of my experience.   If I think I’ve figured it out I’ll let you know.

“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.


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.


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.

Yah, it's me!

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.