It could be reasonably argued every organizations wants, or tries, to provide an optimal customer experience. As the saying goes - your competitor is only a mouse click away. A direct result of the ever increasing focus on customer experience has been the development of a number of metrics to determine just how well a company is performing.
Customer satisfaction, or CSAT as it's known in the industry, was the first metric that showed up years ago with the advent of call/contact centers. It's a fairly abstract measurement of whether a customer was happy or disappointed following an interaction with a brand.
Over time, other metrics have come about to try and assess the value of a customer and predict their future value. One important metric is customer lifetime value, or CLV. Figuring out the connection between the level of customer service and how it's tied to customer lifetime value has spurred interest in other metrics like CSAT, Net Promoter Score (NPS), and even measure of customer effort.
All Metrics Aren't Created Equal
Most of these metrics are perceptual—when you ask someone how they feel about something in the moment, you're likely to get a different answer than if you waited until a day or two later. The response could go in either direction, depending on what the customer experienced. For example, think about what would happen if you asked someone how likely they would revisit a store within two weeks (or if they'd be likely to recommend a friend). The answer could change dramatically if the interaction took place on a website or if the customer had spent an extended time with the product.
Customer effort is a different kind of metric because it can actually be measured very concretely. How many times do we just want something to be made easier? Customer effort seems to be a better predictor of loyalty and customer lifetime value than Net Promoter Score or an abstraction like customer satisfaction.
Increase Accuracy With Diligence & Concrete Metrics
I believe these metrics are a bit like a religion - the more committed and methodical you are about collecting your data, the more likely you are to have a meaningful predictor of loyalty and customer lifetime value. Regardless of whether you choose to gather NPS or an abstract metric of customer satisfaction, you'll get more accurate information if you ask the customer shortly after the situation has occurred.
I also greatly prefer concrete measurements rather than abstract measurements based purely on people's impressions or moods. I like to think about how the technology in a contact center is supposed to work. From there, we can apply controlled measurements against targeted response times and overall transaction times from start to finish. How long does it take a customer to navigate an IVR application, for example? Those things can be measured concretely and plotted as a mechanism to understand customer effort. (Remember, everyone would prefer tasks to be easy and fast.)
Meaningful metrics also require a comparison. Voice of the customer feedback and learning how customers feel about their experience is really important. It's also critical to recognize anything based on feeling is subject to change based on the mood of the individual. However, automated interaction with technology is different—if you know what to expect based upon how systems are put together, your company can make concrete measurements about how well the technology is performing on an ongoing basis.
I would love to hear how your organization is measuring customer experience - are you using just the one metric - like NPS - or a combination to get a more comprehensive view? Leave your comments below to share.