5 AI Chatbot Metrics to Track for Better User Experience

AI chatbot metrics

5 AI Chatbot Metrics to Track for Better User Experience

Chatbots play the most vital role in providing exceptional customer support and experience on your website. The development and deployment of a chatbot are quite essential for providing quick assistance and answering questions when you are busy with your regular tasks and all.

AI chatbot provides the best way to proactively engage and communicate with your new visitors and customers and encourage them to purchase by clearing their doubts in no time. It is the present and future of online marketing, improving user experience to simplify the business process.

But implementing the chatbots in the right way is a bit challenging task as it requires to set-up the best metrics based on what your audience love about the chatbot and what they expect in response to answer their questions.

Well, in this article, you will learn about the top 5 AI chatbot metrics to track better user experience and provide excellent customer support. If you implement these 5 AI chatbot metrics in your website, I assure you will be able to optimize your chatbot for a better user experience.

Let’s get started!

The following is a list of top 5 AI Chatbot Metrics that you need to track for improving better user experience;

1. Number of users reached

Try to identify the total number of users attracting and engaging with AI Chatbots. If your chatbot can interact with thousands of users within a week, your chatbot is quite optimized for a better user experience.

On the other hand, if the chatbot doesn’t interact with more users then, you need to optimize it further. To do so, you need to set up the right metrics based on the number of users interacting with AI Chatbot on your website.

2. Time Session with Chatbot

Once you identified the total number of users that are interacted with the chatbot, you can move forward to the next step to take an idea of how to use AI chatbot to improve the best user experience in a better way. Time session is the best metric of AI chatbot to help you identify the results, but it solely depends on the specific industry and situations.

That’s because most chatbots designed with the sole intent of answering questions and providing assistance to clients should have a short session. On the contrary, chatbots designed to help people in placing their orders or telling a story might be considered a longer session.

3. Response time

In today’s busy world, users want a quick and fast response to their questions. They expect it to be given within a few seconds, and this is the reason many businesses are not able to interact with more customers to their chatbots.

To make it more effective, you need to ensure that your chatbot provides the users the quickest and fastest answers in an instant. Furthermore, you can test it to see how long it takes to answer your questions and optimize the chatbot accordingly for improving a better user experience.

4. Sessions per user

In most cases, around 40 in 100 people interact with a chatbot, which symbolizes that it was not able to provide the answers of these users they have been looking for. It is extremely important to keep an eye on the number of sessions per user as it can help to determine whether the chatbot is doing the right job or not properly.

Go through the conversions and try to identify the session per user where users interacted and reasons to leave the session. Keeping an eye on the session per user can help you to find the top reasons for interacting and distracting with chatbot so that you can optimize the chatbot to provide the best customer support and experience for your customers.

5. Confusion Triggers

Keeping an eye on the way users interact with chatbots alone can not help to optimize it for a better user experience. You need to take an extra step to understand how your chatbots behave when they face difficulties in answering difficult questions and requests.

Users ask various types of questions in different ways, and if your chatbot is not able to answer such questions, it is more likely to respond in such a way; “I don’t understand.” To avoid these issues, you need to analyze and count down the number of confusion triggers shown by chatbot so that you can optimize it to avoid such problems in the future.

To Sum Up

Thus, developing and deploying a successful chatbot requires you to measure the right metrics based on user behavior and experience that can engage with more users in the right way. Your chatbot can provide the best user experience for your customers if you implement the most useful metrics, including the total number of users reached, time session with a chatbot, response time, session per user, and confusion triggers.

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Ramesh Chandra
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