Customer demands for fast, round-the-clock customer service have led to increased adoption of chatbots. In fact, Business Insider predicts that consumer retail spend via chatbots will reach $142 billion worldwide by 2024, representing a massive increase over $2.8 billion in 2019.

For those who recognize the benefits of chatbots, this comes as no surprise. Not only do chatbots improve the customer experience by eliminating wait times and quickly answering questions, they also reduce the number of repetitive inquiries agents must address, creating a better outcome for everyone involved in the customer service ecosystem. But simply implementing a chatbot on your website doesn’t necessarily mean you will immediately see benefits. Like any other marketing, sales, or customer service channel, chatbots require consistent monitoring and refinement to ensure that they are performing effectively. 

In order to adequately measure and improve the performance of chatbots, brands should pay attention to metrics in two categories: chat-specific metrics related to usage and success at resolving problems, as well as impact to key customer service KPIs that brands already track.

Measuring Chatbot Success with Chat-Focused Metrics

There are a number of data points brands can extract from their chatbots to identify how well they’re representing the brand and helping to solve customer problems.

Chat volume: The first key metric is fairly simple: the number of chats involving your bot. You should regularly review the quantity of conversations, especially in comparison to your overall traffic on pages where the bot is available. Tracking chat volume over time helps inform how intuitive your product or solution is to use, and can indicate whether or not other customer service channels, such as self-service support articles, are doing a good job of solving problems.

Chat abandonment: Measure how many chat sessions end before a resolution is reached. High chat abandonment rates can mean that your chatbot isn’t effectively communicating with your customers or making it easy for them to solve their problems.

Conversation duration: How long do users typically spend engaged with your bot? While you don’t want your customers to feel like they’re wasting their time, lower conversation durations aren’t necessarily better, either. While the ideal length of a conversation varies by problem and industry, regularly reviewing this metric can help inform how effectively your bot is doing its job.

Self-service resolution rate: Perhaps the most important metric of all. How effectively is your chatbot solving problems without ever involving a live agent? While it’s unlikely that chatbots will fully eliminate the need for live agent involvement altogether, measuring the resolution rate tells you how much time your bot is saving your agents by resolving customer issues on its own. If your resolution rate is consistently low (again, this varies on industry, but generally anywhere below 40%), that likely means it’s time to rethink your chatbot script and identify how it can better solve problems.

Measuring Chatbot Success with Customer Service Metrics

Measuring the success of your chatbot doesn’t mean only tracking a handful of new metrics. If the ultimate goal of a chatbot is to improve customer satisfaction, over time you should see an impact on the metrics you already use to measure this.

Ticket volume: Like chat volume, ticket volume helps inform how intuitive it is to use your solution. By implementing a chatbot, you should be able to see a decrease in ticket volume over time, as chatbots take common, easy-to-answer inquiries off of your agents’ plates.

Customer satisfaction ratings (CSAT): There are many reasons a brand might think to implement a chatbot, but all of those reasons boil down to providing better customer service. As a result, measuring how your CSAT score changes over time once a chatbot is implemented can indicate how successfully your chatbot is improving the overall customer experience. If customers are able to receive timely, accurate support more consistently thanks to chatbots, they are in turn more likely to be satisfied with your solution. 

Agent satisfaction rate: Keeping your customers happy starts with keeping your customer success team happy. As chatbots increasingly route repetitive questions and tasks away from agents, you should aim to see a positive impact on your agents’ well-being and overall workplace satisfaction. 

Improving Chatbot Performance

When measuring the success of your chatbot, it can be easy to get lost in the raw numbers, but remember to ask yourself what those numbers mean. It’s critical to measure KPIs over time and evaluate trends, as that is how you will ultimately understand if your overall customer success strategy is working or not.

And if you’re looking to take your chatbot strategy to the next level and improve global customer service metrics, then you can’t afford not to have a multilingual customer support strategy in place. Luckily, Language I/O’s translation management software makes it easy to turn your monolingual agents and chatbot into polyglots. To learn more, contact us or request a demo.