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10 wrong ways to use conversational AI for chatbots | by Kevin White | Apr, 2021

Kevin White

Artificial intelligence algorithms are widely used in e-commerce. For example, when creating chatbots. Technologies provide automated, prompt, and high-quality solutions to customer problems. Accordingly, they help to increase sales.

However, this is only relevant if chatbots are used correctly. Some mistakes completely negate the possibilities of technology. Today we will tell you about them. Find out 10 common mistakes companies make and how to fix them.



Internet trolls often entertain themselves by asking inappropriate, incorrect, or stupid questions. The chatbot must be able to identify this. And in such a way that the conversation ends. Programming to repeat the question, or send yes / no answers if the request is not understood, does not improve the quality of service. It damages the brand.

Chatbots answer user questions based on specific previously learned prompts. These are the given statements and words. Also, semantics can be used by spoken artificial intelligence agents. It allows you to understand the context without learning a specific formulation.

To eliminate misunderstanding, teach the chatbot the maximum number of words, situations, and expressions. Use crowdsources to collect additional data. Track engagement and continue regular training for the program.

It’s easier for people to process small messages. Therefore, instead of several large paragraphs of text, limit the chatbot’s responses to a couple of sentences, or even one.

You can fix this by mapping out detailed conversation trees. Just take the time to do this. Managing expectations can also improve the quality of customer service by informing users about the limitations of chatbots.

1. Chatbot Trends Report 2021

2. 4 DO’s and 3 DON’Ts for Training a Chatbot NLP Model

3. Concierge Bot: Handle Multiple Chatbots from One Chat Screen

4. An expert system: Conversational AI Vs Chatbots

Therefore, machine learning programs must be dealt with. It is part of the supporting ecosystem. By investing in them, the company is accelerating the training of artificial intelligence.

The difficulty is that people express thoughts in different ways. It is necessary to systematically train chatbots using the conversation history. The more examples the program learns, the faster and more accurately it will be able to determine the client’s intent.


Provide the chatbot with answers to all possible customer questions. For example, after analyzing the previously set. Try to expand the list of possible answers by providing examples. Remember that a chatbot must communicate not only efficiently, but also competently.

Grammar errors in messages can spoil the support experience. To prevent this from happening, use services like Ivory Research. This guarantees literacy, readability, and consistency of answers.

Also, introduce the AI ​​to customer intent. This will help the program understand exactly where it needs help. Consequently, the chatbot will be able to determine how this can be done.

Conversational AI is great for situations where the task is time-consuming. And so much so that the use of a tone menu or graphical interface will make it unnecessarily cumbersome.

Remember one rule: if a task cannot be completed using a fixed set of inputs, then conversational AI is needed. Most often these are nonlinear processes.

However, too many functions confuse them. Optimally, there should be 3–4 of them. Highlight the key tasks of chatbots and then they will perfectly cope with their duties.

The connecting function of chatbots in business communication with customers is the ability to understand questions and provide accurate answers. This creates sustainable values. Only after getting a positive impression of the company can the data from users be used to achieve better results.

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