Monitoring Chatbots

According to IBM Watson, 70% of customers prefer messaging over voice support. That’s why chatbots are being incorporated into many businesses customer service offerings. But when it comes to exploring your options – it can be difficult to know where to start. We’ve broken it down to help you find the best solution for you and to ensure that you get the most from your investment.  

What actually are Chatbots?

A chatbot is a piece of artificial intelligence (AI) software, it can simulate a conversation with a user through messaging applications via websites, mobile apps and over the telephone. They’re being used more and more by businesses, to help them provide customer service support out of hours when customer service agents are unavailable to assist or to simply field to questions that have simple answers.

Having a chatbot can be rewarding, but only if it’s aiding the customer journey, and not hindering it. To make sure your chatbot is performing effectively it’s important to regularly monitor its performance.

To help, here are a handful of metrics you should be looking at, which will help you stay ahead of your competitors and improve customer satisfaction levels.

What to watch… 

Satisfaction Rate

The whole reason for having a chatbot is to service your customers, which in turn should increase overall satisfaction – as long as the query is dealt with effectively. This is why monitoring your satisfaction rate is crucial, it’ll allow you to determine if your bot is performing or not, allowing for alterations to be made. Quite often we see satisfaction rate drop because chatbots don’t sound human enough, or aren’t sophisticated enough to respond reactively – so keep an eye on any feedback and make sure that you are actioning this appropriately.   

Query Completion Rate

Are your customers getting the outcome they wanted them they contacted you? For example, if a customer uses the Chatbot to change their payment details, are they able to do so? If the bot doesn’t have the capacity to do this it should be highlighted to customers when the conversation begins, potentially through a ‘pre-chat survey’, and alternative communications routes should be highlighted, such as a telephone number or email address along with the call centre opening times and estimated email response time. Keep an eye on how many customers have successfully had their queries resolved and keep looking at ways to improve this – from building in more answers, or refining what’s already there. 

Query Completion Time

Customers are keen to use chatbots due to the immediate support they offer. That’s what makes chatbots a great addition to a businesses customer service offering. According to IBM, Watson, AI-powered conversational agents (Chatbots) can successfully resolve 80% of commonly asked questions. However, there are occasions that misunderstanding can occur.  If queries are taking an excessive amount of time to reach completion, this needs to be investigated further. A delayed query completion time can result in high levels of customer dissatisfaction – with many users becoming frustrated. Monitoring and benchmarking your query completion times can help you identify issues and solve them as soon as possible. This might involve deploying a human agent to deal with more complex queries, to increase customer satisfaction. 

Misunderstanding Errors

Are customers repeating themselves constantly and getting frustrated when the chatbot doesn’t understand the context of their query? This can result in high levels of customer dissatisfaction which could be detrimental to the customer’s user experience. It’s important, that along with monitoring query completion time, that the context of the interactions between the users and bot are monitored too. This can be done by randomly reviewing transcripts to detect misunderstandings so they can be rectified – by altering the bots standard responses or transferring specific keywords/topics to a live agent. This will significantly reduce the number of misunderstanding errors, and so improve its functionality.       

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  • Written by Simon Proctor, January 17 2020