Customer Support Metrics: The Other Side of CSAT

Support Ops

Uncover root causes of dissatisfaction and develop actionable improvement plans.

Collecting CSAT (Customer Satisfaction) data is Customer Support 101. It can be an invaluable tool for understanding customer sentiment and improving operations, and almost every team includes it in their suite of top metrics. 

But CSAT can easily become a vanity metric that doesn’t drive real change. If it’s just a number that you watch go up and down week after week without digging deeper, then you’re not learning anything, and you have no power to move the needle in a positive direction. 

Only looking at aggregate data and focusing on your overall rating means that you’re losing valuable feedback and dooming yourself to keep repeating the same mistakes. When you repeat those mistakes, the result is more unhappy customers, more churn, and more stress for your team.

However, with proper examination, you can find the underlying drivers of dissatisfaction and create actionable plans for improvement. This is next level — Customer Support 202. 

Sometimes called DSAT (Dissatisfaction) analysis, the process takes a little bit of work, but it’s a labor of love that benefits you and your customers immensely. Here’s how to do it.

DSAT Analysis Step 1: Collect

If you don’t already have a CSAT survey in place, then get that sorted first. Make sure you have an open-ended input where customers can provide explanations for their ratings. You could provide a set of drop-down choices to make analysis slightly easier, but the downside is that you limit potential answers and risk biasing the customer into providing an answer they wouldn’t have otherwise. In any case, without giving customers some way to indicate why they’ve rated poorly, a DSAT analysis is impossible.

As you gather data, be consistent. Sending the same question on the same cadence for everyone means that your data can be more reliably compared over time.

Next, determine what qualifies as a “poor” rating in your book. Part of this will depend on the scale you’re using to measure CSAT and part of it will depend on your standards. 

For example, one team might think that a rating of 6 on a 10-point scale is good because it’s slightly above the mid-point. Another team who has been doing DSAT for a while and wants to raise its standards might consider it an “F” rating that needs to be addressed.

DSAT Analysis Step 2: Codify

After your survey is properly set up and you’ve got a queue of poor ratings, you can take the qualitative feedback from the comments and turn it into quantitative data. Review each rating and comment. 

As you comb through, you’ll notice trends in the commentary that you can use to create a category system. At first, your category hierarchy might be flat, but over time you could assign both a broader category and a more specific one. 

Broad categories could include things like support operations, product, or company policies. Specific categories could break those down into things like response time, a particular bug, or a refund policy.

Based on each comment, assign at least one category. Yes, it’s time-consuming. But it’s time well spent  —  because this approach will equip you with the intel you need to fix mistakes and pain points, resulting in happier customers, a higher CSAT score, and a stronger customer support team. 

Aside from providing you with a clear map of what’s causing dissatisfaction that you can use to reduce customer woes, you can also gain insights on individual employee performance. If someone is struggling to meet standards, you can develop a more precise plan based on exactly what’s going wrong.

Because there is some subjectivity involved in translating the customer comment into a defined category, it’s best to either assign one owner for this process or to go through calibration exercises to make sure your team is on the same page for how things should be classified. Otherwise, your data may not be entirely reliable because the opinions of different owners will skew the results.

DSAT Analysis Step 3: Analyze and Act

On a regular and frequent cadence, pull all of your data together and organize it to show which categories are causing the highest percentages of the total low ratings. A spreadsheet table will suffice, but visualization in the form of a Pareto chart (which includes bars and a line) can make a big statement and help everyone get the picture more quickly.

Based on the results, find the root cause of the issue and devise a plan of attack. Sometimes getting to the bottom of things will be easy, like when customers cite a specific problem with your website. Other times, it takes a bit more research. 

For example, if you have a lot of low ratings because your team is giving out incorrect information, it could be that they need more training, that your knowledge base needs an update, or even that your team feels pressured to meet unrealistic resolve goals influencing them to rush through conversation. In this scenario, talking to your team and doing additional research should lead you to solutions.

Low ratings often have nothing to do with the service and will be focused on something that another team has control over fixing. But going through DSAT arms you with the data you need to effect change with those teams. Showing in context how many dissatisfied ratings are happening because of a particular issue is extremely powerful. 

As you go through the process of implementing DSAT, it’s also a good time to put a policy into place for responding to poor ratings where there’s opportunity to clear up a miscommunication, provide additional guidance, or otherwise rectify the situation. 

95% of customers will give you a second chance if you handle their complaint successfully and in a timely manner, so it’s worth the extra effort. Just make sure to carefully review your tone so there’s no chance that your outreach will be mistaken as defensiveness.

When you’re ready for Customer Support 303, you can start crossing your CSAT data points with other ones like response time, number of touches, retention, referrals, and more to see how these factors are interrelated. But that’s a lesson for another day!

For now, there’s a wealth of insights waiting to be discovered through DSAT. Make it a regular part of your support operations and soon you’ll see happier customers and a happier team.

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