Key Metrics to Evaluate the Performance of Your Chatbot
Chatbots are a great tool for any business: they serve multiple customers at once and work around the clock with no extra fees for overworking. Both customers and organizations benefit from them greatly.
However, it is not enough to write a chatbot script once, and hope it will work forever. Time changes and user demands will alter as well. It is important to check up on your bot’s performance to understand whether it meets those demands at the moment. It is essential to update the script and add new questions or update information if needed.
Otherwise, your chatbot might turn useless and obsolete in no time and give users false information which will hurt your business.
Still not convinced? We have found five solid reasons to track your chatbot’s performance and described what metrics to track to monitor its effectiveness.
Reasons to track your chatbot’s performance
We wish there was a way to build a tool once so it worked perfectly fine forever. However, there is no such thing yet and we still have to take care of our business tools after they are already launched.
Here are four reasons why tracking your chatbot’s performance is essential.
#1 Measure chatbot’s effectiveness
The main point of chatbot creation is for it to handle customer inquiries quickly and efficiently. They have to grab customers’ attention, answer as many questions as possible on their own and provide helpful assistance.
Performance metrics help to define whether customers understand how to use the chatbot, how quickly chatbots resolve their issues, and how many common problems this tool can handle without human interference.
#2 Understand customer satisfaction
Before businesses write the bot script, they usually do a lot of research. You can gather all the data you want and make very well-informed decisions but your predictions may still be wrong. What attracts and satisfies customers, in theory, may upset and annoy people in reality. It is important to double-check whether your customers are really enjoying the new service rather than being sure that they must be okay with it.
#3 Measure business ROI
Chatbots take a lot of time, effort, and money to configure properly. However, it seems like nothing compared to all the benefits of chatbots: 24/7 assistance, quicker response time, lower mistakes or disputes possibilities, no need for too big customer support teams, and night shift employees.
Are you sure that you are getting these benefits though? Tracking key performance is the only way to find out. If you notice that ROI is too low, you may want to fix a thing or two to make your efforts matter.
#4 Identify key problems
Performance metrics will not only tell you that there is a problem but help you identify where the fire is. If you track your chatbot, you will notice early signs when something stops working properly or loses its productivity and can further explore and fix it. Is the sentiment wrong? Do you need to update the information or add new frequently asked questions? Do you have to make chatbots more visible? Explain better how to use it? Tracking metrics will definitely help you to get to the core of the problem.
#5 Collect insights about your customers
Modern privacy regulations such as GDPR or CCPA make it hard for businesses to collect any consumer-related data that can be later used to better understand users’ needs and business optimization. However, by analyzing crucial chatbot metrics you get a chance to learn more about your customers as people willingly share their information in a conversation with a chatbot.
13Chats provides critical KPIs
Keep track of your chatbot performance to find the best solutions for your business!
What chatbot analytics metrics to include?
There are well over 20 metrics that you can track but do you need to really? The tracking process does not have to consume all your time, it is just ineffective and you are likely to give up on it quickly.
We have created a list of the main metrics you should track to both spot problems early on and not burn out from the measurements. We have put them into three main categories: user metrics, conversion metrics, and customer satisfaction metrics.
User metrics involve all things users: their number and successful (or unsuccessful) sessions.
- Total number of users. This metric defines how many users have interacted with the chatbot overall. It helps you to understand how attractive your bot is and whether users know about its existence and functionality.
- Engaged users. Engaged users are those who use the bot repeatedly. It means that they either find it extremely useful or just like to interact with it which is also a great sign.
How to calculate: engagement rate = number of users who’ve opened your chatbot/number of users who’ve interacted with it at least twice
- Number of new users. This metric should be saved for the times when you actually promote your new bot or remind customers of its existence. It is a great way to measure whether your advertising methods are working well.
- Bounce rate. Bounce rate is a percentage of people who opened a chatbot but never really interacted. In order to measure it, you need to divide the number of all initiated sessions by the number of sessions where users did not interact with a bot. If the bounce rate is too high, you might want to create a better welcome message: explain what your bot does, how it can help customers, and add buttons with frequently asked questions or actions. The main point is to make the initial step as straightforward and understandable as possible.
How to calculate: bounce rate = number of users who’ve opened your chatbot and didn’t interact with it / total number of users who’ve opened your chatbot
If you choose to create your chatbot with 13Chats, you’ll get access to a variety of tools that would help to analyze such user metrics as total impressions, engagements, dialogues conducted, amount of subscribers, and leads generated.
Conversation metrics are tailored to understand how natural, effective, and engaging your chatbot script is. They include the following metrics:
- Self-service rate. The self-service rate is the percentage of users who did not need human assistance. Customers usually want a real person to speak to if they do not like bots in general or did not find the answer to their questions. You can not do anything with the first type but you can add more frequently asked questions to the chatbot script.
How to calculate: self-service rate = number of users who haven’t requested the connection with human agent / total number of users who’ve interacted with your chatbot
- User sentiment. It is a sentiment analysis that helps you to understand how people respond to your bot: do their messages sound angry, amused, or just neutral. The metric can help you understand whether the bot’s tone of voice works for the customers or needs some changes.
How to analyze: use services such as Natural Language Understanding API
- Average conversation duration. This metric analyzes how long your customers interact with the bot. It helps businesses to define how helpful the bot is. If sessions last for too long, it means that the chatbot fails to recognize the user’s question fast enough. It may result in the customer’s frustration and we want to avoid that. Yet, keep in mind that some people just like to talk with AI so the context is important.
How to calculate: average conversation duration = duration of all chatbot sessions within a period/number of chatbot sessions within a period
- Fallback rate. Fallback rate shows what percentage of users received the message “I do not understand”, meaning that the chatbot did not have the answer to the question in the script. If the fallback rate is too high, you might want to add more answers or keywords by which the bot can recognize a problem.
How to calculate: fallback rate = number of user requests that the chatbot couldn’t answer/total number of user requests within a period
Customer satisfaction metrics
It is basically what it sounds like: these metrics help you understand how satisfied your customers are with the bot.
- Goal completion rate. Goal completion rate is the metric that shows whether customers perform a desired action within the chatbot: sign up for an email list, complete an order, create an application, buy a subscription, go for a free trial, etc. It defines whether your bot is effective and works well as a marketing tool. If your bot just answers common questions, this metric is not that important.
How to calculate: number of users who have completed the desired goal/total number of users
- Confusion rate. This metric tracks the percentage of cases when a chatbot doesn’t understand the question or sends the wrong reply. You need to strive to make this percentage as small as possible and optimize your chatbot for it to better understand the customer’s queries.
How to calculate: confusion rate = number of user requests that were not understood by chatbot within a period/total number of user requests within a period
- Average satisfaction score. At the end of the conversation, it is better to ask customers how satisfied they were with the chatbot on a scale from 0 to 10. Usually, it is done through a simple star rating but you can also ask users who gave one or two stars what was wrong. This is one of the best ways to understand whether your chatbot is performing well.
How to calculate: average satisfaction score = sum of all scores/amount of scores
- Retention rate. Retention rate shows how many users interacted with the bot once again within a given period of time. It indicates that the bot is actually helpful and is pleasant to interact with. However, the metric might be irrelevant for the businesses that offer products that are changed rarely or services that are used once, for example, car or real estate selling businesses and agencies.
How to calculate: retention rate = number of chatbot subscribers at the last day of the period/number of chatbot subscribers at the last day of the period
Chatbots should be regularly updated: you should add new questions and answers, change your welcome message or tone of voice based on user feedback, or simply make it a little bit more visible on the website. You can learn what exactly you should fix based on the metrics that we discussed today. In such a way, your bot will stay relevant as long as possible and show great ROI.
In 13Chats, we wanted to make tracking of these metrics easy and we have automatically structured and visualized statistics for you to enjoy. Start creating chatbots with 13Chats today and benefit from improved analytical functions tomorrow!