“Sorry, I don’t understand what you said. Could you repeat it?” The odds are that you have already seen a similar reply when the bot couldn’t answer your question. Do you remember what you felt at that time? Was it disappointment, irritation, or maybe anger?
Nobody likes when technology fails. And when it does, users can experience so-called computer rage, the digital frustration resulting from IT problems. Digital rage can be expressed at the moment of frustration but can also have a long-lasting effect. Users who get poor digital experience are more likely to lose trust in using digital solutions in the future.
Speaking of chatbots, they can’t always answer every user question — they are not there yet. However, the fact that chatbots are limited doesn’t imply they have to frustrate the user whenever they can’t provide a proper answer.
Quite the opposite, chatbots can provide a positive user experience even if they don’t know the answer, provided they’re designed well.
Follow this reading, and you’ll learn how to design error messages that guide the user toward the resolution and provide a seamless experience.
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A chatbot error message (also known as a fallback response or failure message) is triggered when the chatbot doesn’t understand the user’s question. This can happen when you undertrain your chatbot, overload the user with too much information, ask too many questions at once, or use unclear prompts.
The best way to deal with communication breakdowns is to simply prevent them. However, that’s not always possible. Even if you do your best to reduce the number of potential conversation blockers, you’ll still need to prepare your bot for unsuccessful interactions in case they occur.
Error handling is important as communication breakdowns distract the user from achieving their goal, if not prevent resolutions.
What’s more, when the user receives a poor experience, their satisfaction plummets. That can hurt your customer relationships and your brand image.
75% of US shoppers stop buying from a company that offers poor user experience.
60% of users are concerned that chatbots can't understand their questions.
40% of users have no preference when engaging with a chatbot or a real agent for help as long as they get the assistance they need.
Fortunately, you can quickly recover the conversation and steer the user back on track with proper error message. According to the Nielsen Norman Group, there are five pillars of a good web error message that can help you with that. Let’s review them to see how you can apply them to chatbots.
The good fallback response informs the user that something went wrong. When the problem occurs, your chatbot needs to let the user know that it can’t provide them with an answer because it doesn’t understand their query.
Sorry, I don’t understand this question
Sorry, I’m just a simple bot and I don’t understand this question. Could you reformulate this question?
Sorry, I’m just a simple shop bot and I don’t understand this question. For sure, I can help you with the following issues:
Being explicit is vital, but more is needed. Good chatbot error messages are also readable, which means they're quickly and easily understandable by the user.
While writing the bot fallback message, you should avoid technical terms, ambiguous words, lengthy metaphors, or slang, as they might confuse the user or even make them frustrated in a stressful situation.
A polite conversation design respects the user and doesn’t blame them for the communication breakdown. Instead of saying, “I don’t understand, can you repeat,” you can say, “Sorry, I’m just a simple bot, and I don’t understand this question.”
In the latter example, the bot fallback response clearly states that the issue goes beyond its capability, and that’s why the problem occurs.
Going on, the good error message is precise, which means it briefly explains why the problem occurred.
Of course, it is not always possible for a chatbot to precisely communicate why it can’t provide the proper answer. However, you can improve the bot’s accuracy by creating contextual error messages. You’ll learn about them later in the text.
Last but not least, user-friendly error messages provide constructive advice and guide the user toward a resolution.
For instance, the bot can ask the user to formulate their question, suggest which problems it’s designed to solve, or provide a human handover in the form of a ticket or chat.
The last information is especially important. Studies have shown that users get frustrated when stuck in a bot conversation, but they find out they could have asked for a handover earlier.
Sorry, I’m just a simple bot, and I don’t understand this question. Could you reformulate this question?
If that’s not enough I can also help you with:
Create support ticket Transfer chat to agent
While dealing with communication breakdowns, it’s useful to create more than one global default response that is shown anytime miscommunication happens. Nothing stands in the way of preparing separate, customized chatbot error message for each story flow.
For instance, if an error occurs in a flow that aims to help the user sign up for your newsletter, you can make contextual references in your message to make it more natural.
What’s more, you can several error messages for each problem so that when the chatbot finds it challenging to answer user questions more than once, it won’t send the same message repeatedly. This way, you can make the conversation less robotic.
Last but not least, even if you create user-friendly error messages for your chatbot, you can still do your best to reduce communication blockers in the story. How?
Apply proven conversation design techniques while writing your script. We’ve already covered that topic in our blog’s articles about How to Write Chatbot Scripts.
Train your chatbot on how to answer general questions.
For instance, let’s say you use the bot to let users make reservations in your beauty salon. Apart from training the bot to answer questions concerning making reservations, you can teach it to answer simple questions regarding your brand, the services you offer, and the location. You can also provide some information about your bot, its name, and its avatar, as many users ask such questions just out of sheer curiosity.
Surely, you don’t have to proactively suggest these questions to the user, but it’ll be helpful if you prepare your bot to answer them at any stage of the story.
Inform the user what response you expect them to provide. If you want them to select a button, say it clearly, so that they don’t try to type an answer. Otherwise, prepare the bot to react both to text and button inputs.
Last but not least, when people go off script, they probably need more information than your offer. You can easily verify what’s missing in your script by reviewing the chatbot's archives, and then you can add missing information to your story.
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