玩家行为分析法编辑本段回目录
虽然全世界的游戏开发者都在试图掌握免费模式的真谛，但过半的努力不过是确定了这个模式到底是什么。
其中一种理解是，免费模式是一种心理实验——依靠开发者预测和引导玩家行为的能力。
以这种理解为前提，玩家数据，而不只是纯粹的收益数字，才是判定免费游戏开发者是否掌握该模式的标准。
Pocket Gems首席执行官Ben Liu在GDC发言上，谈到了他对这个问题的看法，并且详述了他坚持使用同期群分析衡量留存率。这个衡量方法也就是监控某个时间开始玩游戏的人，并将得到的数据与老玩家作对比。
pocket gems game(from insidemobileapps)
Pocket Gems称通过这个方法可以发现，游戏发布之后的更新是否有效，并获知游戏未来的升级方向。Ben Liu在采访中解释了这个方法并为开发者提供了一些建议。
同期群分析的测试的最佳规模是什么？
这取决于你想测量的是什么。
如果你要寻找的是平行分布的度量，那你就需要测试大量玩家，应该不少于几千。但如果你要研究的双向分布，也就是让玩家回答“是或否”的问题，如是否花钱、是否回归游戏，那么需要测试的玩家就要比较少了。
你能简单地介绍一下什么是平行分布吗？
平行分布类似“每玩家收益”。但这两者是不同的，前者更接近指数分布，且在频谱的两端有高值。这种分布有许多变化。
如何确定某几千名玩家是最佳样本规模？
根据统计理论。分布涉及许多数学原理，你可以帮助你发现多少千的玩家在什么时候呈现统计学上的意义。
当规模太小时，数据会有什么表现？
玩家人数越多越好，但测试的时间也就更长了，成本也更高。
通过重复测试、不同时间的观察，如果发现结果差异太大，就说明规模可能太小。
如何确定每天登录的最佳次数？在你的GDC发言中，你表示手机游戏的最佳登录次数是每天五次以上。
那是根据数据得到的结果。我们在iOS和Android上发布了不少20款游戏，观察和测试的结果表明5次或以上就是最佳次数。
那个数字有何意义？每天登录5次或以上的玩家会花某一数量的钱？
从表面上看，那个标准与其他数据是匹配的。
比如，它说明了玩家对游戏的沉浸感强；玩家玩游戏的时间越长，留在游戏中的时间也越长。
我们认为这个数字与赢利的关系比较小，而与玩家沉浸感、游戏的有趣程度、玩家的游戏时间和玩家对游戏的喜爱程度的关系比较大。游戏次数是一个很好的指标。
如果玩家每天上游戏一次，但每次都能玩上两个小说，那说明什么？哪种标准更重要？
手机游戏的登录次数反映了玩家的游戏习惯，所以这个数字非常重要。每次游戏持续的时间虽然也重要，但不如次数来得重要。
而对于社交游戏，应该更加关注玩家游戏的持续时间，而不是登录次数。
登录次数对持续时间有何影响？
应该能看得出来游戏持续总时间与登录次数的对应关系：玩的次数越多，时间也越长。
你们为《Tap Zoo》增加了成就系统和剧情元素，帮助游戏留住玩家。但在早期，手机游戏中往往不多见成就系统和剧情元素。你们的成功是否暗示了硬核游戏和手机游戏之间的平等关系？
我想换一种方式回答。
我得说，人们喜欢追剧情。我认为讲故事的方式是多种多样的。我们的任务系统给玩家安排了一连串的活动，也只是叙述方式之一。
硬核游戏的存在时间更久，所以它们也已经形成自己的叙述方式。但我觉得二者都是迎合了人类讲故事、听故事、追故事的渴望。
游戏开发新人在刚开始寻找衡量用是否成功的指示时，可以参考哪些好资源或者活动？
市面上有许多文献和分析资料，所以我能做的就是多阅读多尝试，找到数据与成功之间的关联，然后在实验过程中解释。
GDC很不错，还有很多活动也会讨论这个话题，所以我就从GDC开始，同时关注和参与其他关于测量和分析的会议。（本文为游戏邦/gamerboom.com编译，作者：Dennis Scimeca）
How to understand mobile player behaviour, according to Pocket Gems
by Dennis Scimeca
As developers across the globe attempt to master free-to-play, half the battle for many is defining just what the model is.
One definition is to think of F2P as a psychological experiment – one that relies on the developer being able to predict and guide player behaviour.
In that context, player data rather than just pure revenue rates is arguably the best way of determining whether a F2P developer really has mastered the model.
Ben Liu, CEO of newly turned publisher Pocket Gems, touched on such issues during his talk at GDC, detailing his firm’s focus on measuring retention using cohort analysis – the monitoring a group of people who began playing a game on a certain date and comparing their stats to that of older users.
It’s a method that allows Pocket Gems to reveal whether post-release improvements to titles have actually been effective, informing any updates released in the future.
To get a wider take on Pocket Gems’ approach, we asked Liu to help us unpack some of his data and advice to other developers.
PocketGamer: What is the optimum size of a cohort for your testing?
Ben Liu: It depends on what you’re trying to measure.
If you’re looking for a metric that’s a parallel distribution then you need a lot of users.
You need more than a few thousand. But if you’re looking for something that’s bimodal, either a yes or a no answer like did they pay money or not, did they come back or not, then the number of users you need is less.
Could you roughly define parallel distribution?
Parallel is like revenue per user. It can be really different and is more of an exponential distribution. There are high numbers at different ends of the spectrum. There is lots of variation within that distribution.
How did you determine that a few thousand players is the best sample size?
It’s based on statistical theory. If you look at how to figure out when something’s statistically significant there are a lot of mathematical rules around bimodal distribution [that say] you can get significance at a certain number of users, and it’s a few thousand.
What kind of noise in the data might indicate that a cohort size is too small?
The larger number of users the better, but it can take a long time or it can be very expensive to do.
If you do a repeated test, if you look at different days and you get widely divergent results, that could be an indication that your cohort’s too small.
How did you determine your metrics for a good number of sessions per day? You said in your talk that for mobile games a good number is five or more sessions.
It’s just based on data. We’ve launched over 20 games on both iOS and Android and looking at all the things that we’ve tested and tried out five or more sessions is a good rule of thumb.
And what did that correlate to? The person who played five or more sessions per day spent x amount of money?
Ostensibly that metric will match up to some other metric.
It matches to long-term engagement in the game, so if they play all the time they’ll stay in the game for a long time.
We think a lot less about monetisation and a lot more about engagement and how fun the game is and how long people stay in the game and how much they enjoy it. The number of sessions is a really good correlation to that.
What if somebody plays a single session a day, but they play for two hours? Which metric is more important?
On mobile specifically the number of sessions, just because of how people play the games, the number of sessions is really important. Length of sessions is important but not as important.
For social the opposite is true. It would be really important to look at the length and not the number of times they were playing.
How does the number of sessions interact with length of play?
I think you’ll see total play time correlates with the number of sessions, so if you play more sessions you play longer as well.
You added both achievements and story elements to updates for Tap Zoo, both of which helped you retain players. But achievements and a focus on narrative didn’t typically feature in mobile games in the early days. Does their success suggest there are more parallels between core and mobile games than people realise?
I would answer the question a little bit differently.
I would say that human beings love following different stories to see what happens next, and I think there are lots of different forms of telling those stories. Our questing system, where you have chains of things that lead to steps down the road and in the future, is just a way of doing that.
Core games have been around a lot longer so they have their own developed ways of doing that as well, but I think it’s just tapping into a fundamental human desire to tell each other stories and hear from each other and see what’s next.
What’s a good resource for a new developer to refer to as they get started developing metrics for measuring the success of their apps?
There’s a lot of literature and analytics providers out there on the market so I would read as much as I could and start with a few metrics, measure them, see if they correlate to success, and then build on that through a process of experimentation.
GDC is fantastic, and there are number of sessions which talk about this, so I would start with the GDC vault and look at all the sessions that are about metrics and analytics and then go from there.(source:pocketgamer)
