Although more and more companies are using chatbots in their customer service, this does not imply that all of them are improving customer satisfaction and user experience.
On the contrary. You often read about experiences in which a user receives incorrect answers. Either they get repetitive messages or unrelated responses. So it’s no wonder that many users end the conversation and develop a negative perception towards chatbots.
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However, this doesn’t mean chatbots can’t contribute to user-friendly customer service. Companies just need to be more structured in their development and pay attention to a few essential points.
In this article, you’ll learn more about the 5 reasons why chatbots fail and what you can do to avoid it in the first place.
Why chatbots fail sometimes
1. Intelligence of Chatbots
There are two groups of chatbots: rule-based and AI-based bots. For bots that are rule-based, a list of rules is established in advance. The list determines how the bot responds to different requests. Usually, a user request is searched for specific keywords. If a keyword is found in the request, the answer for this particular keyword can be displayed to the user. If there is no defined answer, a rule-based bot can’t answer the question. Frustrated users are pre-programmed.
The situation is different with AI-based bots. They are also set up with a list of rules at the beginning, however, they are able to learn from each interaction with a customer and thus continuously improve the quality of their answers.
Unfortunately, rule-based chatbots are much more common at the moment. AI bots are more complex and more expensive to implement. However, they are an investment that will pay off.
2. Inappropriate use cases
Although everyone is talking about chatbots, this does not mean that they are the right tool for every business. Many companies are so enthusiastic about the new technology that they want to introduce it without thinking about benefits for the user.
But this is exactly what you need to do. Before you build a chatbot think about whether you have a good use case for it. Chatbots are usually well suited to answer standardized questions. However, they are often not suitable for complex customer problems or individual complaints. For this kind of support live chats or even a combination of live chat and chatbot can make sense.
3. No transparency
When companies use chatbots they should be transparent about it. For many users, it’s quite frustrating when they think they’re talking to a human employee and then realize that it’s actually a bot.
Therefore, you shouldn’t create false expectations. If you are using a bot in your communication, indicate it at the beginning. If you hand over the conversation to a human employee let the user know. That way the user knows to whom he is talking to at all times.
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4. No clear scope
Many chatbots try to solve all problems for everyone. Unfortunately, that causes problems. A chatbot needs a clear scope of the topics and use cases it can cover. If a bot tries to answer questions around several topics or a use case that is too broad, it will hardly be able to provide a satisfactory user experience.
For instance, a limitation could be that the bot only assists with booking flights or is responsible for your car rentals. Such highly specialized use cases are much easier to think through and implement at the beginning.
5. Lack of analysis functions
Like any other software, chatbots need continuous analysis and a structured process to further improve their functionality. Many companies are not aware of this aspect.
Once a bot is launched, it is often assumed that the work is done. In reality, it just starts after the launch. The data basis for improvements can be conversation protocols, usage statistics as well as user surveys after the conversation. Your aim should be to continuously analyze the available data and implement appropriate measures for improvement.
Knowing why chatbots usually fail can help you prevent those mistakes. At Onlim, we are happy to support you with your chatbot and we let our 20+ successfully implemented chatbot projects speak for themselves. Learn more here.
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