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游戏设计师该如何有效利用游戏分析

发布时间:2015-05-08 16:29:29 Tags:,,,,

作者:Nathan Lovato

作为游戏设计师,我总是认为我们的工作便是艺术与科学的结合。毕竟游戏设计与心理学和设计是紧密联系在一起的。设计是非常直接与明显的。存在许多关于这一主题的内容。

这仍然是一个非常年轻的领域。在10至15年前,我们还不具有追踪玩家行为的处理能力和连接性。但今天,一切都不同了!游戏分析能够提供给游戏工作室中的任何人令人兴奋的全新可能性!游戏分析可以为游戏开发改头换面。它们的作用将延伸到测试,QA,社区管理以及盈利等方方面面。

作为设计师的我们现在可以基于真正的数据去做决定了!这也是我们今天打算讨论的内容。

所以什么是游戏分析呢?

游戏分析便是使用统计数据对于玩家行为的研究。即包括你可能想要追踪的各种类型的数据。大多数情况下,我们总是想将其与市场营销和盈利结合在一起。然而这些统计数据并不是只适用于市场营销者或制作人!

它们是非常出色的学习工具,能够帮助你更好地了解你的用户。游戏分析能够让我们脱离主观看法而更好地理解玩家们。

pasted_image_at_2015(from gameanalytics)

pasted_image_at_2015(from gameanalytics)

分析的结果便是参数

参数是经过一段时间追踪到的一连串数据。基于参数我们可以追踪到任何内容:平均回合持续时间,玩家卸载游戏的时间点,目标玩家群体等等。

主要存在4种参数类别:

1.用户参数:相当于所有与用户获取和用户留存相关的数据。它们也可以被当成市场营销者的数据。这一类别的参数包含了DAU(每日活跃用户)和ARPU(每用户平均收益)。

2.社区参数:社区参数专注于社区行为和发展。它们将追踪你的游戏内部聊天中的内容。所有的社交元素都属于这一类别。例如游戏内部和社交网站上的信息传递。

3.性能参数:性能参数将追踪你的应用的性能和潜在漏洞或坍塌。它也是你那遥远的服务器,游戏的加载时间或运行时的帧速的响应器。它能够帮助你完善后端系统。

4.游戏玩法参数:游戏玩法参数将记录任何发生于游戏内部的情况,即介于玩家和游戏之间。例如玩家在特定关卡中所花费的时间,玩家死了多少次等等。它们能够帮助设计师判断用户游戏体验的情况。

作为游戏设计师,我们经常基于较温和的艺术方式去创造我们的项目。毕竟我们是设计师。乍看之下,游戏分析就像是市场营销者们用于推动游戏盈利所使用的工具。例如与盈利相关的分析能够反映游戏所提供的体验质量。而用户留存也是与游戏设计师相关的:它们将提供给你关于游戏最初体验的吸引力的整体概况。

但是游戏并不只是关于钱。它们还是关于与游戏玩法相关的任何参数的分析!

尽管做为一种艺术学科,游戏设计同时也是一种基于技术的工作。游戏分析能够通过真实数据帮助我们理解玩家的行为:

如果你知道玩家何时在哪里受困,你便能够轻松调整游戏的难度。

如果你知道玩家会购买什么道具以及不愿意购买什么道具,你便能够调整价格。

如果你知道玩家的年龄,你便能够针对他们更好地调整内容。

游戏分析是与任何人有关的

各种规模的工作室都需要考虑数据追踪。我并不需要告诉你所有AAA级工作室会追踪测试者和玩家行为等数据。他们拥有大量的预算,因此对于客观数据的需求更高。拥有300名成员的团队并不能只是依赖于游戏设计师的猜测。

我们可以使用一些基本的参数去了解玩家对于我们游戏的反应。好消息是你并不需要一个专用服务器与后端开发人员去设置分析。如今存在许多免费工具能够为你处理这些过程。

游戏分析同时也与原型创建或测试阶段相关。它们让我们有机会检查核心游戏玩法的运行。你可以追踪玩家的移动并了解他们在特定关卡中的哪个位置会受困。你也可以追踪到他们在哪个点上离开游戏:是在死亡之后,还是在关卡的中间阶段?或者是在到达最后阶段?

即使没有追踪游戏中玩家的行动,你也能够使用基本的参数去解决一些主要问题。如你可以估算游戏教程的作用,或者在最初游戏阶段游戏的吸引力。在任何手机游戏中,糟糕的设计决策都会破坏游戏的用户留存。例如教程的长度或前几个关卡的难度。如果玩家因此受挫,他们便会选择卸载游戏,或者会因此感到非常厌烦。

面对用户分析

在面对用户分析时,我们总是很难去预测人类的行为。我们不能只是依赖于一些通用参数。DAU,ARPU和其它常见的参数只能帮助我们看清游戏的整体状态。我们需要游戏的每个部分都适合各种类型的用户。作为设计师,我们希望能够理解每一个玩家。因此我们需要使用一些更具针对性的数据去进行适当的分析。

然而我们却不可能追踪所有的内容

我们必须选择一些特殊的数据流进行分析!我们可以自行支配所有的参数,但是却不能追踪所有的内容。我们所控制的每个数据流都带有处理成本—-不管是在服务器端还是人力方面。尽管今天的我们能够收集并处理许多数据,但是我们却不可能获得所有内容。我们必须明确那些相关与不相关的参数。

我们应该追踪怎样的参数?

在不同项目中,你应该追踪的参数的属性与数量也是不同的。你需要在游戏开发前期计划游戏分析的使用。基于游戏类型和范围,你将找到一些相关的参数。例如与社区和盈利相关的参数在单人游戏中并不重要。

除了一些常见才参数外,每个项目还有自己的不同需求。

小团队并不需要追踪大量的数据。他们不需要像大公司那样监控所有的用户行动与输入。一些简单的参数便能够帮助他们解决主要的游戏玩法问题。以下便是一些能够帮助你平衡游戏进程的内容。你需要清楚:

玩家何时离开游戏

他们在游戏回合中平均待了多长时间

玩家在游戏中前进了多远

玩家在什么时候卸载了游戏

这些数据流都是很容易追踪到的。通过结合这些数据流,你能够了解到底是什么内容让玩家感到受挫。结合这些数据与你的目标用户群体,你便能够基于用户去明确相关分析。例如你可以将卸载了你的硬核游戏的10岁用户从成人群体中过滤掉。

与游戏玩法相关的分析会较深入。甚至连最简单的游戏也会使用各种变量。即包括位置,状态,参数等等。我们并不能独自追踪到所有的这些内容:分析结果需要消耗大量的时间。因此我们需要采取巧妙的方式去划分各种数据。从根本上来看,我们可以将类似的行动归为一组。假设我们想要知道游戏中武器的效能。我们并不需要追踪每种武器类型,修饰等等。相反地我们可以专注于玩家对特定怪物所造成的破坏性。

我们不应该追踪怎样的参数?

我们可以更轻松地过滤掉那些不该追踪的参数。游戏设计师并不需要追踪所有可行的参数去了解玩家的行为。一些精心挑选的参数便能够传达给我们足够的内容。如果我们在特定类别中分析了更多数据流,我们从每个参数中所获得的利益便会更少。

我们可以只是优化自己的分析模式。并且知道该在哪里停下来,就像我们往往能够通过一些独特的参数发现一些特别的设计缺陷。

但是我并不想追踪太多个体变量。让我们以一款多人RPG游戏为例。我们想知道每个角色的总水平。比起追踪每个特征,我们将基于一些相关值将它们结合在一起。我们可以追踪他们每秒的破坏力和生存能力。如此我便可以只监控2种相关的参数。

找到可遵循的适当参数并过滤它们是一种平衡的方法。这并不是什么科学。所以请果断地去尝试!

对于游戏设计师来说,所有的参数都很重要

免费游戏拥有不断发展的社区。有些人会不时回到游戏中。也有些人在匆匆体验一些游戏内容后便会离开。带有永恒世界的游戏不只需要留住玩家。它们同时也需要迎来不同的新玩家。正因为如此,它们的用户基础不断发生着变化。它们的社区也不断发展着。作为一名游戏设计师,你需要找到能够保持游戏世界新鲜感的新理念。

也就是社区参数迟早会派上用场。大多数情况下,玩家会在游戏内部的聊天渠道中表达自己的意愿。你的部分角色便是实现玩家的某些愿望。所以追踪玩家的聊天内容是获得新理念与有价值的反馈的有效方式。这同时也是发现漏洞的好方法,即玩家总是会在聊天过程中表达出自己的想法。这比联系支持团队更快捷。对于游戏设计师来说,各种类型的参数都是有价值的。

实时更新

使用分析还能够完善游戏开发途径。其中便包含动态更新游戏的能力。

任何应用商店对于更新的审批过程都需要花费许多时间。不管何时只要你的游戏出现游戏玩法问题,你都不希望再等好几天去解决这些问题。

而基于有效的参数,你便能够监控玩家对于你的最新更新内容的反应。如果你看到玩家正费力地与特定boss相抗衡,你便会想马上改变boss的生命值。如果你看到玩家并未在游戏中购买任何道具,你便会想马上调整道具的价格。

当玩家启动游戏时,你便可以通过遥远的服务器下载相关数值。基于这种方式你便能够实时保持游戏的平衡了!就像大多数游戏玩法总是待在网上那样,我们也可以每天完善游戏体验了。这是在测试阶段快速迭代的一种有效方式。尽管技术执行起来还是有点复杂,但却是一种可行的做法。

结论

希望本文能够帮助你看清游戏设计师能够从分析中得到什么。

总之,游戏分析并不是关于销售。而是关于如何更好地理解我们的游戏和用户。它们让作为设计师的我们能够有效地修改游戏玩法问题并完善游戏的沉浸感。它们能够帮助我们推动游戏的最终成功。并因此提高游戏创造更多收益的能力。这至少是设计师和市场营销者可以并肩协作的一个领域。从根本上来看,游戏工作室要想生存下去的话既需要曝光度也需要金钱。

作为游戏设计师,我们需要有效利用游戏分析的作用:

从开发前期便开始执行它们

专注于理解用户行为

重视各种类型的参数!

对于任何想要生存下去的工作室来说,推动游戏质量至关重要。而这在过去曾经是一种盲目的平衡行为。

本文为游戏邦/gamerboom.com编译,拒绝任何不保留版权的转发,如需转载请联系:游戏邦

Game Analytics From A Game Designer’s Perspective

Nathan Lovato

As game designers, we tend to perceive our activity as a mix of art and science. After all, game design is deeply linked to psychology, as well as design! The design part is pretty straightforward and well-documented. There is plenty of reading on the topic, starting with Jesse Schell’s famous textbook.

It is different with game analytics.

The domain is still young. 10 to 15 years ago, we lacked both the processing power and the connectivity to track player behaviors. But today, it is different! Game analytics offer an exciting array of new possibilities for everyone in game studios! Game analytics can change the face of game development. They are helpful from alpha testing to QA, community management to monetization.

Where we had to guess before, we designers can now make decisions based on real data! This is what we are going to talk about today.

So what are game analytics?

Game analytics are simply the study of our players’ behaviors using statistics. This expression covers all the types of data you may want to track. Most of the time, we tend to associate them with marketing and monetization. However, those statistics are not only for marketing people or producers!

They are a great learning tool, an occasion to get to better know and understand your audience. Game analytics offer us an opportunity to understand players beyond our subjective interpretation.

Analytics boil down to metrics

A metric is a stream of data that is being tracked over time. Metrics can track anything: average session duration, game uninstalls, player demographics…

There are 4 main categories of metrics:

1.Customer metrics: They correspond to all the data related to the acquisition and retention of customers. They can also be seen as the marketers’ data. Specific metrics in that category include DAU (Daily Active Users), ARPU (Average Revenue Per User).

2.Community metrics: Community metrics focus on the community’s behavior and evolution. They track what happens in your in-game chat for example. All sorts of social interactions fall in that category as well. For instance, both in-game and social network messaging.

3.Performance metrics: Performance metrics track your application’s performances and potential bugs or crashes. Be it a response time from your distant server, the game’s loading duration or framerate at runtime. Anything that can help you to improve your back-end systems.

4.Gameplay metrics: Gameplay metrics record anything that happens inside the game, between the player and the game. I.e. time spent in a given level, how many times the player died. They empower us to estimate the quality of the user’s gameplay experience.

As game designers, we often like to approach our projects in a mildly artistic way. After all, we are designers. At first, game analytics may seem like a cold tool, a big black box for marketing people to boost the monetization of a game. For one, monetization related analytics reflect the quality of experience offered by the game. E.g. retention is relevant to game designers: they give you a broad overview of how compelling is the first experience of your game.

But game analytics are not only about money. They are about analyzing any type of gameplay related metric!

Despite being an artistic discipline, game design is also a highly technical activity. Game analytics enable us to understand the behavior of players using factual data:

If you know when and where a player gets stuck, you can easily tweak your game’s difficulty.

If you know what items people buy and people don’t, you can adapt prices.

If you know how old your players are, you can better adapt your content to them.

Game Analytics are relevant to everyone

Studios of all sizes are concerned by data tracking. Well, I won’t need to tell you that all AAA studios tracked by beta testers’ and players’ behaviors. They have the largest budgets, thus the highest need for objective data. A team of 300 people cannot only rely on guesses from game designers!

We could all use some basic metrics to understand how well our players react to our game. Good thing is, you don’t need a dedicated server and a backend developer to set up analytics for you. Today, there are plenty of free tools that handle the processing and monitoring for you (e.g. GameAnalytics)!

Game analytics are also relevant from the prototyping or Alpha testing phase. They give us an opportunity to check that our core gameplay works. You can track the player’s movements and know where he gets stuck in a given level. You can also track at what point he or she leaves the game: was it after a death, in the middle of the level? Or was it maybe after reaching the end of a section, just as expected?

Even without tracking the player’s movement in game, you can solve critical issues with basic metrics. E.g. you can estimate the quality of your game’s tutorial, or you game’s appeal during the first gameplay session. On any mobile game, a bad design decision can kill your game’s retention! For example, a lengthy tutorial or a difficult first level! Players will uninstall the application if they fail straight away. Or if they are simply bored.

Working with user analytics

When we work with user analytics, we work with hard to predict human behaviors. We cannot simply rely on a few generic set of metrics. DAU, ARPU and other common metrics only give us insights on the overall state of the game. We need each part of our games to be accessible to a wide range of users. As designers, we want to understand our players on an individual level. As well as on a broad level! Thus, we need a lot of specific data to run proper analyses.

Yet, we cannot track everything

We have to pick specific streams of data to analyze! All sorts of metrics are at our disposal, but we can’t track everything. Each stream of data we monitor has a processing cost. Both on the server and the human side. Although we can collect and treat a lot of data today, we can’t get everything. We have to find what metrics are relevant to us, and which ones are not.

What metrics should we track?

The nature and amount of metrics you should track completely changes from project to project. You need to plan your use of game analytics during the game’s pre-production phase. Depending on your game’s genre and scope, you will find more or less relevant metrics. For instance, community and monetization related metrics don’t matter in single player games.

Beyond a few generic metrics, each project has different needs.

Small teams don’t need to track large amounts of data though. They don’t need to monitor all user actions and input like big companies do. A few simple metrics can help you solve critical gameplay issues. Here are some useful general picks to balance your game progression. You want to know:

When players leave the game

Their average session duration

How far players go in the game

At what time players uninstall your app

The few streams of data exposed above are very easy to track. By combining those streams of data, you can get a sense of what content frustrates your users. Mixing this data with user demographics, you can also refine your analysis based on your audience. E.g. you can filter out 10 years old users uninstalling your hardcore game for grown-ups.

Gameplay related analytics go extremely deep. Even the simplest game uses a large amount of variables. Objects have a position, states, parameters, etc. We cannot track them all individually: analyzing the results would cost a lot of time. Thus, we need clever ways to group sets of data together. Basically, we can group actions that are similar in their form. Let us imagine that we want to know how efficient weapons are in a game. We don’t need to track each weapon’s type, modifications, etc. Instead, we can focus on the damage players inflict to a given monster.

What metrics should we not track?

It is probably easier to filter out the data we shouldn’t bother tracking. A game designer doesn’t need to track every bit of available data to get profound insights on the players’ behaviors. A few carefully picked metrics can tell us a lot. Also, the more streams of data we analyze in a given category, the less benefits we gain per metric.

We can only optimize our model of analysis to a certain point. It is tricky to know when to stop, as some very specific design flaws may only be found via a unique metric.

But we basically do not want to track too many individual variables. Let us take a multiplayer RPG as an example. We want to know what is the overall power level of each character. Instead of tracking every characteristic, we can compound them in a few relevant values. We can simply track their damage per second and survivability. That way, we only have to monitor 2 relevant metrics.

Finding the right metrics to follow and to filter out is a tough balancing act. It is not a science. So do not hesitate to experiment!

For a game designer, all metrics matter

Free to play titles have evolving communities. Some players only come back to the game occasionally. Others rush through the available free content and leave. Games with persistent worlds do not only need to retain players. They also need a constant flow of new players to stay afloat. Because of that, their user base keeps evolving! Their community evolves. As a game designer, you need to find new ideas often to keep refreshing the world.

That is when community metrics come in handy. Most of the time, player will express their desires in the in-game chat’s general channels. Part of your role is to answer some of the players’ desires. So tracking general conversations can be a good way to get new ideas and valuable feedback. This is also a great place to discover bugs, as players will tend to express themselves spontaneously in the chat. It is much faster than contacting the support team. I guess that you can see where I’m going. All types of metrics are valuable to a game designer!

On the advanced side: Updating on the fly

Using game analytics opens other, more advance opportunities to improve your development pipeline. One of these is the ability to dynamically update the game.

It takes a lot of time for an update to be validated on any app store. Whenever your game has a critical gameplay issue, you don’t want to be waiting for days for the issue to be solved.

With solid metrics, you can monitor the way players are reacting to your latest update. If you see that players are struggling against a given boss, you want to change its health maybe. And you want to change it now. If you see that players are not buying some objects in your game, you want to tweak their cost. And you want to tweak it now.

When the player launches the game, you can download values from the distant server. That way, you can balance your game on the fly! As most players are always connected to the Internet, we can keep improving the gameplay experience from day to day. This is also a great way to iterate really fast during beta phases. Although that technique is somewhat complex to implement, it is a great possibility to keep in mind.

Summary

Hopefully, this article gave you an overview of what analytics have to offer to a game designer.

To sum it up, Game analytics are not just about sales. They are about getting a better understanding of our games and of our users. They empower us designers to fix gameplay issues and improve the game’s immersion. They empower us to boost our game’s success. And by extension the game’s ability to spread and generate revenue. This is at least one terrain where designers and marketers can appreciate to work hand-in-hand. Ultimately, a game studio needs both visibility and money to live.

To harness the power of game analytics, as a game designer:

Implement them from the pre-production phase

Focus on understanding your users’ behaviors

Take interest in all sorts of metrics!

Pushing the quality of the game is essential for any studio to thrive. It used to be a blind balancing act.(source:gameanalytics)

 


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