中文字幕无码av不卡一区,亚洲综合AV永久无码精品一区二区,黑人巨大白妞出浆,黄色高清无码免费看,久久久久免费精品国产,久久无码人妻丰满熟妇区毛片,欧美日韩国产综合草草,久久福利网站,亚洲一区二区三区中文字幕在线,av国内精品久久久久影院

構建一個聊天機器人是非常容易的，但是，用戶使用它的方式以及能否使用它順利的完成任務，最終決定了一個聊天機器人是否是用戶想要的。所以，要如何設計一個優秀的聊天機器人呢？

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.

似乎從2017年起，全世界都在嘗試使用聊天機器人來構建全新的交流體驗。但事實是，我們可能只是剛剛開起一個長達數十年的緩慢變革。

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.

聊天機器人并不會像一些人所認為的那樣，在一夜之間就迅速普及，一個重要的原因是：雖然他讓人機交流變的更像人際交流，從而可能帶來革命性的交互體驗。但正因如此，也使得我們在設計一個聊天機器人的時候很容易犯各種錯誤。

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.

要解決這個問題，不僅技術上面臨著巨大的挑戰（例如：如何通過“隨意的”文本來了解用戶的真實意圖），同時也需要設計范式上的創新：當用戶界面非常小的時候，你會怎么使用？

對于設計師，在一個聊天機器人項目中，文字本身是他們僅有的創作工具，也是最強大的工具之一。

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.

在過去一年中，我參與到一個大公司聊天式界面的項目中，我想要完整地了解怎樣為聊天機器人創造一個優秀體驗。

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.

構建一個聊天機器人是非常容易的，但是，用戶使用它的方式以及能否使用它順利的完成任務，最終決定了一個聊天機器人是否是用戶想要的。

荷蘭皇家航空公司和我們全新的王牌售票機器人

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.

荷蘭皇家航空公司（KLM）很喜歡嘗試各種新技術，它是世界上最早一批全心擁抱聊天機器人的公司之一，同時也擁有最好的聊天機器人。它雇傭的超過230名經過專業培訓的新媒體客服，這樣人力成本壓力，也是促使公司投入大量精力在聊天機器人項目上的重要原因。

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.

而社交網絡上每周超過十萬的@和點贊，證明了人工智能和聊天機器人的技術組合，可以快速有效的解決簡單的問題。

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在聊天機器人和人工智能上投入了大量的資源，它希望通過這些技術能夠快速且精準的解決用戶的問題。與此同時，它也在投入了很多在具體工具的開發上?，F在你就可以直接在Facebook Messenger上預定機票。

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的聊天機器人不僅很好用，而且通過它訂票比在網站上訂票還要容易。因為，用戶經常會因為搞不清網站上的一個按鈕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.

以下就是我總結地KLM的聊天機器人如此優秀的原因，以及其他的公司可以從中學到什么。

Don’t just assume a single intent

不要只假設單一的使用場景。

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.

我從其他公司的聊天機器人項目中發現了一個常見的錯誤，那就是他們認為用戶一開始就知道，機器人能做什么亦或者所有用戶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.

這也是導致高失敗率的主要原因，當用戶對機器人提出問題，但發現機器人并不能夠理解他們想要問的是什么的時候，用戶就選擇結束對話并關閉聊天窗口。

而KLM意識了這個潛在的風險，所以他們的機器人會根據用戶的提問迅速的給出一系列的相關選擇，比如：客服、航班預定亦或者其他服務。即使這個請求最終是由人工完成的，但這仍然不妨聊天機器人是一個有效的方法去了解用戶的使用路徑。畢竟，它不需要任何的人力。

處理模糊回復

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.

如果你選擇“預定航班”，那么KLM允許你輸入你想要去的任何地方。而這也是所有聊天機器人開發人員的噩夢，因為此時用戶可能說出任何內容，而機器人則需要通過少的可憐的信息去解析這個內容。

即使你讓用戶在一個固定的文本框中輸入內容，但是大多數人還是會輸入一些超乎你想象的內容，然后讓給你來幫他們找出他們所需要的答案。

Even being vague doesn’t break KLM’s bot

模糊的內容并不會玩壞KLM的聊天機器人。

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：我輸入了新西蘭，但沒有說我想要去城市。雖然我準備好了最壞的結果，可最后的結果出乎了我的意料。

KLM的確考慮到了這種情況，而一個好的聊天機器人開發項目，就應當考慮到各種類似于這樣的異常情況，尤其在用戶體驗文案設計的階段（UX Writing 是設計人和軟件交互時所見話術的一種實踐，它關乎設計產品和用戶之間的對話—?知乎）。

在這點上，他們做的很好，KLM不僅禮貌的要求提供更多的細節，并且將兩次輸入的內容聯系再一起，以弄清楚我的意圖，而不是強迫我再次輸入完整的目的地。

“措辭就是一切”

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.

當你在創造一個聊天機器人的時候，機器人說的話就是你的一切。它們是用戶體驗的起點和終點。所以不能有任何令人疑惑，使人誤解或讓人無法將對話進行下去的措辭。

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.

我已經為許多聊天機器人編寫設計了對話。在開始編寫對話之前，首先應該考慮地是用語方式。我注意到KLM在很多地方都使用了易懂的語言引導用戶。所以讓我們來看看他們是什么樣子的。

（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的機器人通過一個emoji表情并用友好的語氣解釋了自己了局限性，告訴用戶“我是一個機器人”，從而讓用戶設立了合理的預期。

這樣做，會使用戶感到舒適，并讓他們了解在使用過程中會碰到一些錯誤，所以他們也會更有耐心的和機器人交談，因為他們知道它還不完美。

（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使用了一個巧妙的技巧來贏得用戶的認可：在繼續對話前，重復它所理解的內容，這樣用戶可以確認理解的是否正確。

比如：一旦你確定了時間和目的地，KLM就會把完整的搜索請求拼出來，為糾正錯誤提供了一個機會。這開始可能很無聊，但是確實是一個有效的技巧。

回想一下你用Siri的經歷，每當她弄錯的時候是多么的令人沮喪。一臺電腦可以試圖讓人用戶覺得它和“人”一樣，但一旦它犯了錯，用戶的這個感覺就會立刻幻滅。通過語言上的一些細小的暗示，KLM可以在機器人犯錯前避免它的發生。這樣就可以保持“即便不完美，但是我們一直在做對的事情”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做的非常好的一點就是在使用中通過對話幫助用戶完成任務。當你有機會自由地回復時，聊天機器人將會引導你做出它所希望的回答。

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

因為有太多種可能的格式，日期尤其的難識別.

這些引導可以避免用戶使用時的挫折感。同時可以簡化開發，畢竟對于開發來說可預測的輸入就是最好的輸入。當你擁有來自世界各地的客戶時，想要弄清楚11/04/2018究竟2018年4月11號，還是2018年11月4號是幾乎不可能的。

不僅只有第一次有用

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.

各種聊天機器人經常碰到的一個問題就是——在第一次與用戶交流的時候往往缺乏對用戶的準確認知。由于聊天機器人不能從已有的后臺系統中獲取數據，所以他們經常不能知道你究竟是誰。

KLM考慮到了這點，所以在訂票過程中，你可以通過聊天窗口獲取到旅程信息的更新，同時也可以在這里收到登機牌。雖然這個功能作用十分的有限，但是這仍然是一個非常好的案例。

它將會話式界面（conversational interface）擴展到第一次交談之外，并保持用戶在較長的時間內依舊原意使用。

一切都比你想的更難

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.

當Facebook推出了他們的聊天機器人平臺之后，有大量的公司嘗試了聊天機器人。但是，其中大多數的體驗并不好。事實證明：大多數的公司一擁而上，并沒有真正的去思考怎樣去構建一個優良的體驗。

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是一個罕見的案例，他們的聊天機器人做的雖然不完美，但是已經非常的好了。相比使用app和網站來搜索航班和機票，“聊天的方式”更加的簡單易行。

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.

如果你也正在考慮做一個聊天機器人，那么就把你的時間花在文案的設計上，在這些細節上下功夫比什么都重要。所話說成也蕭何敗蕭何，而措辭和語氣就是聊天機器人成功與否的關鍵。

You can try KLM’s chatbot here.

原文作者：Owen Williams

譯者：leglars，微信公眾號“AI設計研究院”（ID：uxofai）

本文由 @leglars 翻譯發布于人人都是產品經理。未經許可，禁止轉載

題圖來自作者