聊天机器人可以做什么（如何设计一个优秀的聊天机器人）

构建一个聊天机器人是非常容易的，但是，用户使用它的方式以及能否使用它顺利的完成任务，最终决定了一个聊天机器人是否是用户想要的所以，要如何设计一个优秀的聊天机器人呢？，今天小编就来说说关于聊天机器人可以做什么?下面更多详细答案一起来看看吧!

聊天机器人可以做什么

构建一个聊天机器人是非常容易的，但是，用户使用它的方式以及能否使用它顺利的完成任务，最终决定了一个聊天机器人是否是用户想要的。所以，要如何设计一个优秀的聊天机器人呢？

How to nail a great chatbot experience

Even though it felt like the entire world was building a next generation experience using chat bots in 2017, the reality is that we’re at the beginning of a slow-burn revolution that’s going to take decades.

似乎从2017年起，全世界都在尝试使用聊天机器人来构建全新的交流体验。但事实是，我们可能只是刚刚开起一个长达数十年的缓慢变革。

Chat-bots are here to stay, but they aren’t the overnight paradigm shift some thought they would be for one reason: they’re hard to pull off. Chat-bots are revolutionary because they feel like a more human way to interact with our devices, but that’s what makes it so easy to get wrong.

聊天机器人并不会像一些人所认为的那样，在一夜之间就迅速普及，一个重要的原因是：虽然他让人机交流变的更像人际交流，从而可能带来革命性的交互体验。但正因如此，也使得我们在设计一个聊天机器人的时候很容易犯各种错误。

Not only are there massive technical challenges — such as understanding user intent from free-form text — it’s a whole new paradigm for design: what do you do when there’s very little interface?

For designers working on chat, text itself is now one of the only canvases they have, making it the most powerful tool in the modern design kit.

要解决这个问题，不仅技术上面临着巨大的挑战（例如：如何通过“随意的”文本来了解用户的真实意图），同时也需要设计范式上的创新：当用户界面非常小的时候，你会怎么使用？

对于设计师，在一个聊天机器人项目中，文字本身是他们仅有的创作工具，也是最强大的工具之一。

Over the last year I’ve worked directly on a handful of chat-first interfaces with big brands personally, and wanted to look at what makes a great chat experience, from beginning to end.

在过去一年中，我参与到一个大公司聊天式界面的项目中，我想要完整地了解怎样为聊天机器人创造一个优秀体验。

It’s incredibly easy to build a bot but not something that people actually want to willingly use — it all comes down to the way the user experiences it and whether or not it’s getting in the way of actually getting the job done.

构建一个聊天机器人是非常容易的，但是，用户使用它的方式以及能否使用它顺利的完成任务，最终决定了一个聊天机器人是否是用户想要的。

荷兰皇家航空公司和我们全新的王牌售票机器人

One of the first big brands in the world to wholeheartedly embrace chatbots was KLM, the national Dutch airline, which is often hailed for being an early adopter to new technology.

The company has one of the best chatbots available, and it has a good reason for caring so much about it: the company employs more than 230 dedicated agents to reply on social media.

荷兰皇家航空公司（KLM）很喜欢尝试各种新技术，它是世界上最早一批全心拥抱聊天机器人的公司之一，同时也拥有最好的聊天机器人。它雇佣的超过230名经过专业培训的新媒体客服，这样人力成本压力，也是促使公司投入大量精力在聊天机器人项目上的重要原因。

With more than 100,000 mentions publicly every week, the sheer impact of being able to quickly solve simple questions with the use of artificial intelligence and chatbots is clear.

而社交网络上每周超过十万的@和点赞，证明了人工智能和聊天机器人的技术组合，可以快速有效的解决简单的问题。

KLM has invested heavily in both chatbots and A.I tools to solve messages as quickly and precisely as possible, but has spent a lot on developing marketing tools as well — to the point that you can book almost your entire flight via Facebook Messenger!

KLM在聊天机器人和人工智能上投入了大量的资源，它希望通过这些技术能够快速且精准的解决用户的问题。与此同时，它也在投入了很多在具体工具的开发上。现在你就可以直接在Facebook Messenger上预定机票。

Not only is the KLM chatbot a fantastic thing to use, it actually seems easier than booking via the website, which can often be clumsy and confusing as you’re trying to figure out which button will do what you want it to.

KLM的聊天机器人不仅很好用，而且通过它订票比在网站上订票还要容易。因为，用户经常会因为搞不清网站上的一个按钮是做什么的而困惑不已。

Here’s what makes KLM’s bot so good, and how other brands could learn.

以下就是我总结地KLM的聊天机器人如此优秀的原因，以及其他的公司可以从中学到什么。

Don’t just assume a single intent

不要只假设单一的使用场景。

A common mistake I’ve seen from other companies that use chatbots is assuming that users who land on their bot will understand it — or have the same intentions.

我从其他公司的聊天机器人项目中发现了一个常见的错误，那就是他们认为用户一开始就知道，机器人能做什么亦或者所有用户都有相同的使用目的。

This often leads to high failure rates as people just argue with the bot, which doesn’t understand their request, or they close the conversation immediately.

KLM’s bot understands this risk, so immediately offers the user a choice of where to go; is the query about support, booking a flight or something else?

Even if the other options end up with a human, this is a fantastic way to figure out where to route the user internally without any humans involved.

这也是导致高失败率的主要原因，当用户对机器人提出问题，但发现机器人并不能够理解他们想要问的是什么的时候，用户就选择结束对话并关闭聊天窗口。

而KLM意识了这个潜在的风险，所以他们的机器人会根据用户的提问迅速的给出一系列的相关选择，比如：客服、航班预定亦或者其他服务。即使这个请求最终是由人工完成的，但这仍然不妨聊天机器人是一个有效的方法去了解用户的使用路径。毕竟，它不需要任何的人力。

处理模糊回复

If you choose Book Your Flight, which is what this bot is made for, KLM lets you type where you’d like to go.

This is basically every bot developer’s worst nightmare, because users could say anything right now, and the bot is left to interpret it based on a very limited understanding of what could happen next.

Even if you get the user to write something you’re expecting into the text box, most people tend to type something vaguer than you’d hope at this point — leaving it with you to figure out the specifics of their answer.

如果你选择“预定航班”，那么KLM允许你输入你想要去的任何地方。而这也是所有聊天机器人开发人员的噩梦，因为此时用户可能说出任何内容，而机器人则需要通过少的可怜的信息去解析这个内容。

即使你让用户在一个固定的文本框中输入内容，但是大多数人还是会输入一些超乎你想象的内容，然后让给你来帮他们找出他们所需要的答案。

Even being vague doesn’t break KLM’s bot

模糊的内容并不会玩坏KLM的聊天机器人。

I ended up naturally typing New Zealand without the actual city I was planning to visit — and I expected the worst but found myself surprised: they’d thought of this scenario.

A good bot development project — particularly from the UX writing side — will consider all of the different weirdness that could eventuate here, and KLM did this right.

Not only did KLM ask for more specifics politely, they nailed combining the two separate data points to figure out what I meant, rather than forcing me to enter the full destination myself all over again.

比如：我输入了新西兰，但没有说我想要去城市。虽然我准备好了最坏的结果，可最后的结果出乎了我的意料。

KLM的确考虑到了这种情况，而一个好的聊天机器人开发项目，就应当考虑到各种类似于这样的异常情况，尤其在用户体验文案设计的阶段（UX Writing 是设计人和软件交互时所见话术的一种实践，它关乎设计产品和用户之间的对话— 知乎）。

在这点上，他们做的很好，KLM不仅礼貌的要求提供更多的细节，并且将两次输入的内容联系再一起，以弄清楚我的意图，而不是强迫我再次输入完整的目的地。

“措辞就是一切”

When you’re building a chatbot, your words are everything. They’re the beginning and end of your user’s experience with you, so you can’t afford any misinterpretations, dead ends or confusing phrasing.

当你在创造一个聊天机器人的时候，机器人说的话就是你的一切。它们是用户体验的起点和终点。所以不能有任何令人疑惑，使人误解或让人无法将对话进行下去的措辞。

I’ve written the UX copy for a number of chatbots, and your use of language should be the principle consideration before writing a single line of code. I noted a number of places that KLM uses great copy to guide the user, so let’s walk through them.

我已经为许多聊天机器人编写设计了对话。在开始编写对话之前，首先应该考虑地是用语方式。我注意到KLM在很多地方都使用了易懂的语言引导用户。所以让我们来看看他们是什么样子的。

（1）KLM sets expectations immediately by making it clear it’s a bot through the use of an emoji and in a friendly tone explaining its own limitations.

By doing this, the user already feels comfortable, but understands something might go wrong, so is far more willing to be patient because they know it’s not perfect yet.

（1）KLM的机器人通过一个emoji表情并用友好的语气解释了自己了局限性，告诉用户“我是一个机器人”，从而让用户设立了合理的预期。

这样做，会使用户感到舒适，并让他们了解在使用过程中会碰到一些错误，所以他们也会更有耐心的和机器人交谈，因为他们知道它还不完美。

（2）KLM uses a smart, subtle trick to win points from users: repeating what the bot understands to be the correct query back to them before continuing.

Once you’ve figured out dates and destination, for example, KLM spells the search out, offering an opportunity to correct any mistakes. This may seem tedious, but there’s a great trick behind this.

Think of the times you’ve used Siri and how frustrating it is when she gets it wrong; if a computer is trying to be human and makes a mistake, the illusion is ruined immediately. By leveraging subtle language cues, KLM able to avoid the computer giving the wrong answer before it happens, and maintain the illusion that we’re getting everything right, even if it isn’t perfect.

（2）KLM使用了一个巧妙的技巧来赢得用户的认可：在继续对话前，重复它所理解的内容，这样用户可以确认理解的是否正确。

比如：一旦你确定了时间和目的地，KLM就会把完整的搜索请求拼出来，为纠正错误提供了一个机会。这开始可能很无聊，但是确实是一个有效的技巧。

回想一下你用Siri的经历，每当她弄错的时候是多么的令人沮丧。一台电脑可以试图让人用户觉得它和“人”一样，但一旦它犯了错，用户的这个感觉就会立刻幻灭。通过语言上的一些细小的暗示，KLM可以在机器人犯错前避免它的发生。这样就可以保持“即便不完美，但是我们一直在做对的事情”的印象。

（3）KLM does a great job of helping you along the way with the wording it uses. When you’re given the chance to respond in free form, the chatbot guides you on how it expects you to respond.

These types of cues avoid frustration on the user’s part and make it easier on the developer’s side: predictable input is the best input, and trying to figure out if 11/04/2018 is the 11th of April 2018, or 4th of November 2018 is impossible if you’ve got customers around the world.

（3）KLM做的非常好的一点就是在使用中通过对话帮助用户完成任务。当你有机会自由地回复时，聊天机器人将会引导你做出它所希望的回答。

Dates are particularly hard, because there’s so many formats humans can respond in

因为有太多种可能的格式，日期尤其的难识别.

这些引导可以避免用户使用时的挫折感。同时可以简化开发，毕竟对于开发来说可预测的输入就是最好的输入。当你拥有来自世界各地的客户时，想要弄清楚11/04/2018究竟2018年4月11号，还是2018年11月4号是几乎不可能的。

不仅只有第一次有用

A common area these bots fall over in is a lack of awareness of the user beyond that first interaction.

Often chatbots don’t understand who you actually are because they are unable to access data from existing backends.

KLM thought of this, and their bot is able to be useful beyond day one: you can choose to receive travel updates in one place and get your boarding pass without leaving it.

While it’s still fairly limited, this a great example of extending a conversational interface beyond just that first chat, and keeping users engaged long-term.

各种聊天机器人经常碰到的一个问题就是——在第一次与用户交流的时候往往缺乏对用户的准确认知。由于聊天机器人不能从已有的后台系统中获取数据，所以他们经常不能知道你究竟是谁。

KLM考虑到了这点，所以在订票过程中，你可以通过聊天窗口获取到旅程信息的更新，同时也可以在这里收到登机牌。虽然这个功能作用十分的有限，但是这仍然是一个非常好的案例。

它将会话式界面（conversational interface）扩展到第一次交谈之外，并保持用户在较长的时间内依旧原意使用。

一切都比你想的更难

When Facebook launched its chatbot platform, there was a deluge of different bots to try, but many of them were a frustrating experience. As it turned out, many brands jumped on the hype train without really considering the nuances involved in building a great experience.

当Facebook推出了他们的聊天机器人平台之后，有大量的公司尝试了聊天机器人。但是，其中大多数的体验并不好。事实证明：大多数的公司一拥而上，并没有真正的去思考怎样去构建一个优良的体验。

KLM is a rare example of a chatbot done well. While it’s not perfect, it’s a fantastic way to search for flights that doesn’t feel more cumbersome to use than its app or website — which is the entire point in the first place.

KLM是一个罕见的案例，他们的聊天机器人做的虽然不完美，但是已经非常的好了。相比使用app和网站来搜索航班和机票，“聊天的方式”更加的简单易行。

If you’re considering building a chatbot, sweat the details and more than anything else, focus on the words you use. Your phrasing is the beginning and end of a great chatbot story, and it’s key to whether or not it succeeds.

如果你也正在考虑做一个聊天机器人，那么就把你的时间花在文案的设计上，在这些细节上下功夫比什么都重要。所话说成也萧何败萧何，而措辞和语气就是聊天机器人成功与否的关键。

You can try KLM’s chatbot here.

原文作者：Owen Williams

译者：leglars，微信公众号“AI设计研究院”（ID：uxofai）

本文由 @leglars 翻译发布于人人都是产品经理。未经许可，禁止转载