What KPIs Should You Track for Chatbot Success?

What KPIs Should You Track for Chatbot Success?

Entire customer service departments are automated these days with chatbot systems.

The advantages of chatbots are numerous for both businesses and customers and streamline the customer experience and business operations alike.

Benefits of having a chatbot

Chatbots, in a nutshell, are software programs that leverage artificial intelligence to communicate with humans.

From the business’s perspective, it benefits by decreasing or completely eliminating the cost otherwise incurred by building out a fully-fledged customer service department and hiring representatives to fill those roles.

On the customer’s end, the benefits include not having to wait in an annoying phone queue for hours on end. Now you will be getting your answers immediately. If the customer has simple inquiries about the product or service in questions, they can get a nearly instantaneous response.

Also consider that chatbots work 24 hours a day, so the customer doesn’t have to worry about the hours of operation.

Chatbot technology is becoming so seamless and sophisticated that many customers don’t even realize they aren’t talking with a human being.

Unfortunately, implementing a chatbot system isn’t as easy as installing an app on your computer. And, contrary to the assumptions of many business owners, chatbots aren’t a set-it-and-forget-it technology, and they require management and oversight.

Before we take a look at key metrics, otherwise known as Key Performance Indicators (KPIs), let’s talk about what a chatbot is and what goals to set.

Crucial KPIs to monitor

There are a myriad of KPIs to track to determine if your chatbot is functioning at an effective and optimal level.

You still need to know what the most important KPIs are, and whether they coincide with the goals you set forth for your chatbot.

  • Conversation length – Unsurprisingly, this metric tracks the total amount of time a user spends interacting with your chatbot.

Longer conversations aren’t necessarily better; remember, if your chatbot’s chief purpose is to provide customer service, you want to handle customer inquiries as quickly and efficiently as possible.

If the time is too long, figure out why. Is the chatbot struggling with the query? Is it giving the wrong information? Can it elevate the issue so a human representative takes over?

  • Retention rate – The retention rate KPI measures the percentage of customers or users who have already had a conversation with the chatbot and return to ask it more questions.

A high retention rate is a signal that your chatbot is succeeding and that the chatbot’s audience is satisfied.

  • Bounce rate – A chatbot’s bounce rate is similar to the bounce rate on a web page. Essentially, it measures the percentage of users who made an inquiry to the chatbot system then immediately abandoned the conversation because it failed to properly address their question.

To reduce the bounce rate, you will need to give your chatbot a wider set of data to improve its adaptability and knowledge.

  • Message rate – Another positive indicator that your chatbot is succeeding is a healthy message rate, which measures the average number of messages exchanged among all conversations.

Generally speaking, a high message rate means high levels of engagement from your users.

An inordinately high message rate could indicate that your user’s issues and inquiries aren’t being offered the most relevant solution.

  • No response rate – The “no response” rate is a key indicator of whether or not your chatbot needs more content. Basically, it measures the number of times your chatbot outright failed to provide any response at all to a customer inquiry because it didn’t understand what the user wanted.

Improve the no response rate by sampling what questions didn’t yield responses and preparing the right answers to them.

  • Response rate – This metric is the opposite of the “no response” rate and tracks the number of times your chatbot successfully answered questions.

If your chatbot software seems to be going to fallback responses often, there might be knowledge gaps in natural language processing to address. 

  • Goal completion rate – Perhaps the most important KPI to track, the goal completion rate is a measurement of the percentage of times the chatbot met the goal you set for it as well as the number of times it failed.

The usual goals are clicking a CTA, a successful purchase, filling out a form. If the goals are not met, you will have to find out whether it was because the bot offered it too early or too late.

  • User satisfaction – How satisfied are the users with the bot? You can get this metric with exit surveys where you urge visitors or customers who interacted with the chatbot to rate their experience.

Keep the surveys simple, and just ask whether the bot did well (Yes/No). This way you’ll get direct feedback. In case the user picks “No,” you can provide a form where they could write why they weren’t satisfied. Just make sure the form is optional. 

All of these KPIs will tell you how well your chatbot is doing its job, and whether there is something you might have to tweak.

The problem is, however, that manually trying to measure and track each metric is a time-gobbling and tedious chore.

But, just as you can automate your business operations with a chatbot, you can also use a custom software to automate the tracking of KPIs.

It will do exactly what you need—track every metric that’s relevant. it can do all the heavy lifting for you and notify you about possible issues and areas of improvement.

Setting goals for chatbots

Primarily, businesses use chatbots as customer support tools, but there are many applications.

For example, other applications include acting as a recruiter, an insurance agent, and other assistant-centric roles. There are a lot of Twitch personalities who use chatbots to poll their audience and even run giveaways.

But chatbots, despite the advancements in artificial intelligence, don’t inherently have goals or a direction. Instead, it’s the job of the business owner or implementer of the chatbot to define the chatbot’s overall goal.

More often than not, if you’re using a chatbot as a customer service entity, your general goal is going to be to help customers with their problems. However, that’s a vague and ambiguous goal that needs to be refined.

You must identify repetitive tasks that eat up your time (or your employees’ time) that can be automated, and you have to consider things from your customer’s point of view.

For instance, do a large percentage of customers pose the same repetitive questions regarding a feature of your product or incessantly inquire about a current promotion?

If so, we can refine our general goal of providing customer service to something more concrete, such as explaining how the product’s features work.

Some chatbots function as little more than an interactive Frequently Asked Questions (FAQ) directories, while some are orders of magnitude more flexible.

Only after you have defined your goals can you then measure the performance of the chatbot and tweak it so it’s a complete success.

Conclusion

Chatbot technology is still maturing, though implementing a chatbot solution provides numerous benefits for your business. The only problem is that tracking KPIs manually is a time-consuming chore and you might miss some key insights.

If you want to implement a chatbot system, think about using a solution that will automate the KPI tracking process too. That way, you will know exactly what you need to tweak for your chatbot to perform well.

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Heather Redding

Heather Redding is a content manager for rent, hailing from Aurora. She loves to geek out writing about wearables, IoT and other hot tech trends. When she finds the time to detach from her keyboard, she enjoys her Kindle library and a hot coffee. Reach out to her on Twitter.

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