One key reason for a Customer Service Manager to look at individual agents performance is to see what can be done to improve overall customer satisfaction and keep customers happy.

Agent interaction is an important part of customer’s perception of your company and its products, so a good place to start is to naturally look at and assess agents performance, and how they score in terms of customer satisfaction.

But how?

For each support ticket closed, a survey is generally sent out asking the customer to rate their interaction with this specific agent. When enough surveys come back from customers, then a satisfaction rating can be applied to each agent. Bad agents need training, good agents need rewards. Et voila.

Sounds easy? Well, not so fast…

There is certainly some truth to be found in this data, but what if some agents had to handle more difficult issues than others did, such as order not received, customer overcharged, refund never paid, and so on?

Obviously, these agents are bound to get much worse satisfaction ratings and performance than other agents that just had to confirm the opening hours of a specific store, or whether a product is back in stock.


To be fair, and real, a Customer service Manager has to look at the diversity of issues that are handled across its agents group, and try and compare his agents performance against the same issues.

Again, this sounds easy.

The Customer Service Manager simply decides to run a report across agents for one specific ticket category, generally identified by a tag or a custom field. But then a new challenge appears: unfortunately, even if the reports look good, sampling a few tickets quickly shows that the ticket tags or fields are not correctly applied by your customer service agents.

In short, the tickets are not correctly categorised, and the report is worthless. And this will probably always be the case, whatever new categorisation or tagging system you put in place.

The next step is then for the Service Manager to read tickets manually over the weekend hoping to come up with enough similar tickets for each agent to compare them and detect which ones need coaching. That might happen one weekend, but that’s it. It won’t happen again.

But do not despair….there is a simpler and much more effective way to do this: use AI to read and classify your tickets.

Cx MOMENTS does this automatically, for new and past tickets. We detect what topics, issues, queries, problems were raised by your customers in each of their support tickets. We then map these topics against tickets volumes, trends and… customer satisfaction.

Once you have that, the next steps are sooooo easy!

First, focus on an important and meaningful topic. Depending on your specific business challenges, this could be one of most recurring issues (e.g. product not being delivered), one of the fastest trending ones (e.g. Poor performing new app release), or one with poor satisfaction rating (e.g. refund not processed). Whatever your criteria are, select the topic you are interested in by clicking on it.


This is in effect a one-click filter to compare how your agents perform against this specific topic:


And if it’s time for a one-2-one coaching discussion, another click will give you all the tickets this specific agent has processed for this specific topic.


With Cx MOMENTS, performance assessment, QA and coaching of customer service agents can focus on the precise topics and issues that specific agents need help on.

And it does this in just a few clicks. Try it here!