Understanding your customer effort score (and how to improve it!)

Abigail Sims

June 22, 2021

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We talk a lot about the customer effort score (CES). Between our work in customer experience, the research that went into The Effortless Experience, and our own effort measurement score, the subject comes up, well, kind of a lot. But if you’re new to the conversation about low-effort experiences, you may be wondering… What is a customer effort score? Why does it matter? What do any of these numbers really mean? Is my score good or bad? How can I improve my effort score? 

Not to worry. Let’s break down some of the most common questions about the customer effort score…and what you can do about them. 

What is your customer effort score?

One of the most common questions about the research around effort is, “What is a customer effort score?” The answer to this is simple. We define customer effort as the work required for a customer to do business with your company, so a customer effort score would then be the score that measures the effort required to do business with your company. This score stands in contrast to the two other major scores in the customer service space—Net Promoter Score (NPS) and Customer Satisfaction (CSAT)—in that it measures work, not relationships. 

Fun fact: The customer effort score was born just a little over ten years ago, as part of research performed by CEB, now Gartner. Matt Dixon, Chief Research & Innovation Officer here at Tethr, was a part of this original research that led to the birth of CES. 

Now that we’ve established what an effort score is, let’s take a look at how to measure it. 

How can I measure effort? 

There are lots of ways to measure customer effort in this day and age! You can create or purchase hyper-specific effort surveys, add an effort-specific question to the end of existing surveys, or utilize and score data you already have to arrive at a CES. These solutions usually rank the effort on a call on a scale from 1-15. In addition, many companies are now moving to voice analytics solutions to measure effort, as a more automated way to record and track customer conversations.

Here at Tethr, we hang our hat on the Tethr Effort Index (TEI). This iteration of customer effort measurement utilizes our machine-learning-backed platform to identify which customer interactions are high or low-effort. Then, we use TEI to score those interactions accordingly. With a research department dedicated entirely to providing reliable metrics for success, and cutting-edge technology delivering insights on every call, chat, and case, we’re confident TEI is the solution to the problem of identifying areas of customer effort. 

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Now that we know how to measure effort, let’s look at what to do with that information, once you have it.

If you have a high effort score...

Utilizing TEI, if you have a high score… congratulations! If your TEI score is in the green, between 7-10, that’s a high score. This indicates a low effort call. You can rest assured that call went well, and that you can learn from the good agent behaviors exhibited in this call. There was probably advocacy, some proactive guidance, closing the loop, all the behaviors that you want to see on these calls. If you’re using a different customer effort score method, any positive score fits under this umbrella. 

What to do about it?

Don’t rest on your laurels! If you have a call that’s scored well, use it as a learning opportunity. Dig in and find out what’s working, and use those calls as examples to help agents whose calls are slipping into the red. 

If you have a medium effort score...

Again looking at TEI, if your call is in the middle of the spectrum, that’s a medium effort score. We mark these calls as yellow, and their scores are usually between 4-7 on the 1-10 Tethr Effort Index. Many calls hover in this middle ground, and it’s tempting to ignore them in favor of the scores lower down on the scale. Don’t fall into this trap! 

What to do about it?

For medium effort calls, you can often easily improve these calls with just a little extra effort. Often, these middle-of-the-road calls could easily have been low-effort calls with a score between 7-10… But the agent just didn’t do anything to engineer a low-effort experience, so the call is left in the middle. Improve a medium customer effort score by coaching agents on low-effort behaviors, the same as you would for a low effort score. 

If you have a low effort score...

If your TEI scores are coming back red, don’t panic. A low customer effort score, indicated in TEI by a score that is between 1-3, shows that your customer has had to do a lot of work in order to do business with you. These calls usually make up around 10-15% of customer calls, so a few low scores is normal. There are, however, things you can do to reduce the number of low TEI scores you receive in a given day. 

What to do about it?

There are several ways to address poor effort scores both before and after the call. Training agents to better address tough customer situations, improving business processes to mitigate the sources of frustration, and even closing the loop with upset customers are all options. (We call these the Tethr ABCs.) By taking actions like these, you can both follow up after low scoring calls and try to make things right, and learn from those calls in order to improve future calls. 

And there you have it. This has been the short and sweet (well, sort of short) explanation of how to understand your customer effort score and how to improve it. Regardless of what metric you use, however, measuring effort is essential. 

If you’re serious about improving your customer effort scores, we’d be remiss if we didn’t strongly recommend utilizing the Tethr Effort Index. As the industry standard in effort measurement, your TEI scores will predict customer loyalty, shine a light on your top performers, and indicate areas for improvement in the business all with just one number. Now that’s an effective customer effort score. 

To learn more about Tethr, TEI, or to see our platform in action, request a demo today. 

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