FAQ pages are the most common way for businesses to ease the demands on their online customer support by answering the most frequently asked questions automatically. Their purpose is to be quick, simple and helpful to both parties. While there has always been an emphasis on making FAQ pages easy to search and scan through, it’s FAQ chatbot that became the trendiest, more natural, way of enabling self-service.
Nevertheless, many businesses are still shying away from the idea of an interactive FAQ chatbot because of perceived complexity. However, today, using the right tools and processes, it’s possible to build FAQ chatbot without coding background.
This article will cover FAQ chatbot basics and building processes for a simpler rule-based as well as the more challenging NLP chatbot in order to create an optimal conversational FAQ design that works best for your business.
According to the Global State of Multichannel Customer Service Report by Microsoft, over 90% of consumers expect a business to offer a self-service support portal or FAQ page. In fact, another study showed that 67% of consumers actually prefer self-service over talking with a human agent. So, at this point, it’s really not a question of whether or not to have the FAQ section but rather how to deliver it in the most effective way possible.
But why chatbots?
Simply put, the technology is getting better and consumers are becoming more and more accustomed to the idea of talking to a bot. Instead of having to search through a an FAQ page – no matter how well-organized – they can get to the point quicker by typing or saying a question they want to ask directly.
Furthermore, chatbots are far easier to adapt, making the experiences frictionless on the desktop as well as mobile. After all, there isn’t anything more natural for mobile communication than texting. Plus, bots allow you to reach out beyond your website or app and be there for your clients on the instant messaging apps they already use.
Being present and ready to help on multiple channels is more important than ever. According to Aberdeen Group Inc, business with the best omnichannel customer engagement strategies retain 89% of their customers, on average, as opposed to the 33% average rate for businesses with weak omnichannel strategies.
So, let’s have a look at how you can build an FAQ chatbot for the web or a messaging app like WhatsApp using rule-based as well as NLP approach.
Choosing to make an FAQ bot is just the first step.
Before you go any further, you need to examine your FAQ needs. The amount and complexity of your FAQ database, as well as channels where you want to publish the FAQ, will help you determine which type of chatbot will serve and help your customers in the most efficient way possible.
You can build a rule-based chatbot, NLP-based bot or bot that uses a combination of the two.
This kind of bot doesn’t rely on AI but rather follows a decision-tree conversation structure. It’s driven by a series of predefined rules designed to solve specific problems or achieve particular goals. With rule-based bots, conversations are mapped out like a flow chart, limiting and controlling user questions and responses.
Rule-based chatbots can be simple or incredibly complex. However, they never allow users to leave the predefined conversational flow. In this case, the personalization happens through choice-making and information conditioning.
Recommended Channel & Use:
Website or any other interface that allows for rich responses such as buttons or images. Most useful in cases when the number of questions and answers is fairly limited and/or you need to get an FAQ up-and-running very quickly (e.g. FAQs for one time events or small companies with a narrow focus, etc.)
Rule-based bots allow you to give your FAQ design personality as well as a good level of personalization for a more pleasant experience. For instance, if a customer clicks to see the shipping rates, you don’t need to show the list of all the countries where you deliver. Instead, your bot asks “Which country is the delivery for?” allowing you to display on the information relevant to the user. Furthermore, since information gathering happens as part of a conversation, you can use the bot’s personality to drive your brand image as well as overall values.
A bit awkward to use on interfaces that don’t allow for rich responses. Not user-friendly for extensive FAQ databases.
NLP (Natural Language Processing) is a small sub-section of AI that deals with linguistics. The ultimate objective of this technology is to process, analyze, decipher and make sense of the natural human language in a way that is valuable. It may but doesn’t have to be enriched by machine learning that enables the bot to learn from experience, not just training.
If you want to learn more about how natural language processing chatbot works, check out our latest article on the topic!
To give you a better idea, a trained NLP bot can understand the following information in any format it has been trained for:
- “I want to make a table reservation for 4, tomorrow at 8:30 pm.”
- “I wanna make a reservation… a table for 4, tomorrow at 8:30 pm.”
- “Book me a table for tomorrow at 20:30, four guests”
However, the NLP bot doesn’t “understand” in the same way a human does. It’s trained to identify certain bits of information inside an unstructured natural text, pull them out and carry out the actions that have been associated with that intent.
So, what the bot REALLY sees are highlighted and instantly categorized data. The bot knows that in the context of “reservation” a number (4, four) or number-word combinations (4 people, 4 guests, table for 4) refers to a number of places that need to be reserved.
The main difference between NLP and the rule-based bot is that NLP bot doesn’t depend on a pre-defined conversation flow. It allows the user to ask about what they want to find out right off the bat, using words that feel natural to them.
Recommended Channel & Use:
The NLP bot is great for every interface. However, it’s particularly useful in limited user interfaces (e.g. WhatsApp) where the user experience depends solely on typed input. Using NLP is particularly hand if your FAQ knowledge base is too extensive to be comfortably built into a conversation tree.
NLP FAQ chatbot can not only streamline personalization by allowing the user to go straight to the point but also communicate its personality perks in a more natural way by engaging in small talk. Plus, it’s flexibility allows you to implement the bot on any interface from a landing page to WhatsApp without having to make changes.
Building NLP bot is more complicated than a rule-based bot. Furthermore, poorly trained NLP bot can lead to negative conversational experiences and customer frustration. If your product or service is too technical or complex, users might not always be able to formulate the questions, so leaving them without any structure might backfire.
As you have probably guessed, a hybrid bot combines the elements of a rule-based and NLP chatbot.
Indeed, incorporating NLP inside a rule-based bot structure is possible.
Well, thanks to the growing number of no-code builders and their integrations. For instance, Landbot now enables Dialoglfow integration that allows you to take advantage of Dialogflow’s NLP capabilities as well as the control over the conversation characteristic of the rule-based chatbot.
Recommended Channel & Use:
Anywhere. You are able to adjust bot mechanics based on the designated final interface. Good for complex or simple FAQs.
A Simpler way of working with NLP.
Let’s take a look at how creating an FAQ chatbot works in practice, using Landbot with Dialogflow integration.
If you are not familiar with one or both tools visit our: