As companies are exploring the use chatbots for customer service, one of the first candidates of “content” that come to mind to “botify” are the existing FAQs often represented on corresponding sections on a website. It is tempting to think that you could just take these and convert them into the form of a Conversational UI (CUI) — they are already in the form of answers to questions after all, right?
In reality, though, it needs a bit more to build a chatbot that really does a good job of serving customers. Taking existing content and just changing the User Interface of it is a natural gut reaction whenever a new UI emerges. This was the case with early Websites (full of text, little rich media, let alone interactivity), mobile apps on multi-touch smartphone screens (it took 1.5 years after the launch of the app store for the first game to come out to truly embrace this new form of gestural UI: Angry Birds), and many other examples can be cited. Now we have the CUI, and it will take some time for the designs to adapt themselves to this “new” (not really, but that is a topic for a different post) paradigm of man-machine interaction.
Best practices are being established, and first books about the topic are being published (e.g. Designing Bots: Creating Conversational Experiences by Amir Shevat, or, with more of a focus on voice: Designing Voice User Interfaces: Principles of Conversational Experiences by Cathy Pearl). Tools that promise to just absorb an FAQ section of a website and convert that into a conversational bot are out there and sound promising — yet they quickly fail with simple real-world examples.
So WHY does an FAQ not translate 1:1 into a chatbot? Several reasons.
1) The nature of a dialog: content is king, but context is queen (and she runs the household)!
This is the probably the most important one, so I mention it upfront.
Chatbots are there to chat with the user — not to produce one answer and then end the conversation. Humans don’t communicate in question-answer pairs. Real world communication is much messier than that. By offering customers a medium that they otherwise use for conversations among friends and family, say SMS, iMessage, or Facebook Messenger, you have to cope with the inherent expectation that when chatting with a business the experience would at least be similar. Yet many chatbots can’t even respond to “hi”, one of the most frequent messages sent to a chatbot.
As a side note: to me, that’s the number 1 reason why IVR systems so often disappoint. We expect human, but get “press 1 or press 2” — an unfamiliar and unexpected user interface on a highly familiar channel.
It is in the nature of dialogs that people ask follow-up questions. And when they do, they like to use pronouns to refer to previously mentioned topics or things. This follows the least-effort principle that permeates human language in so many areas. Consider the following four FAQs a bot covers that we built for an automaker earlier this year:
- What is Concierge Service?
- How can I contact the Concierge Service?
- What is the price of the Concierge Service?
- Can my partner or a co-user use the Concierge Service?
Once the context of “concierge service” is established through a question such as “tell me about concierge service”, a follow-up question might be “how much is it?”. It is thus crucial to maintain context to be able to answer questions such as “how much is it?” or “can my wife use it?”. What is it? Or, as a linguist would ask: Which antecedent does the pronoun refer to? To handle that in chatbots you will want to design your Conversational Architecture.
Sometimes even the exact same question can yield different answers, depending on the flow of the conversation. Context awareness is critical for a chatbot. Without it, users will read “I’m sorry, not sure what you just asked” a little too often… a mistake made frequently with the early bot implementations we saw in 2016.
2) Scope of typical FAQ content
Frequently asked questions are just that — frequently asked questions. For not-so-frequently asked questions you’re left alone, or rather left to figure out how to get human help. A chatbot that just covers those questions that are among the FAQs and doesn’t provide an easy path to human help for those that aren’t can easily get frustrating.
3) Domain of typical FAQ content
FAQs are by nature questions that have answers which are in the “public domain”, i.e. can be put on a website and apply to everyone. Oftentimes, however, customers come with questions such as “where is my order”, or “I need to change my upcoming appointment”. FAQs do not answer these; they rather point to a place on the website where you can log in and get an answer to this question. If a chatbot does the same, rather than actually tell you where you order is or asking what day you would rather come in for your appointment, you produce friction and a break of medium, which doesn’t help the experience. Chatbots need to integrate with your CRM and other customer-related systems of record to make them truly useful.
4) Nature of typical FAQ content
Websites by nature are media-rich environments that allow for a high-fidelity display of information. There is no boundary to the amount of information you can convey, nor to the format. However, chat is quite the opposite: you are operating in a medium that is based on the idea of a conversation and constrains the information throughput that can be achieved at a time. Copying & pasting content from the website into a messaging bubble is not the right way.
As part of the transition of FAQ content into the chat medium, consider your message and conversation interaction design. Neutral formulations such as “Customers can register here:” should be converted to second person singular: ”You can register here:”; longer messages — and they sometimes cannot be avoided given the subject matter — must be split up into smaller pieces to fit into the constraints of Facebook Messenger or SMS.
Finally, it is not enough to teach a bot how to understand the question if asked (mostly) verbatim as it’s represented in your FAQs. Questions in FAQ sections are designed as broad questions with all-encompassing answers, and they are worded in “written language style”. Chat however means conversation, gradual discovery, and colloquialisms. Where an FAQ might formulate (somewhat awkwardly) “What are the conditions for the utilization of the adapter”, a real person might ask “what do I need so I can use the adapter”, or simply “how can I use it?”…
5) Intent of an FAQ section on a website
FAQ sections on websites are meant as an additional source of help, among others. Sometimes they are meant to be an entry point into the content of the website. But they live on your website, and are thus focussed around it, often point to places on your website. A chatbot, say one that lives on Messenger or SMS, greets the user with a “blinking cursor”. It is the customer that sends the first message, and that message could be anything. There is no way for you to guide the conversation, you have to respond to what they’re sending, which might be a simple “public domain” question, a CRM-type account question, or a complaint. You can overcome this hurdle by offering human backup for all those things the chatbot wasn’t designed for, but if you don’t, you run the risk of creating something that worsens rather than helps with your CX.
Pulling in FAQ content into your customer service chatbot per se is a good idea — the more information the bot has at its disposal, the better. By bundling FAQs with the questions you are already handling on other channels, say your IVR, integrating it with your enterprise backend systems, and applying the rules of the CUI, you should be able to reap the rewards quickly. Wondering what the business case of a chatbot could look like? Have a look here. And if you need ideas for how to get started designing your own bot, have a look at our resources on www.aspect.ai.
As a next step, why don’t you check out your company’s FAQs and think through what it would take to “botify” your FAQs?
Why you Can’t Just Convert FAQs into a Chatbot 1:1 was originally published in Chatbots Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
Source: Chatbots Magazine