Different metrics exist to measure customer satisfaction. Here we will discuss 3 of them.
When discussing ->Product-Led Growth, we have explained how important referrals are for sustained growth. Word-of-mouth is a key aspect to win more customers while keeping customer acquisition costs low. A popular metric for that is Net Promoter Score (NPS).
The NPS score tells you how likely your customers are to recommend your business to others they interact with. In that way, the metric not only helps win new customers but is also a predictor for retention because a happy customer is unlikely to churn. The data for the score can be obtained with a single question to users:
The scale ranges from “0 = not all all likely” to “10 = extremely likely” based on which the NPS score is calculated as follows:
Thus, the NPS can range from -100 to +100, a higher value indicating a better result. As per industry standards, scores above 20 are OK-ish, above 50 are considered excellent, and above 80 are world-class.
While a widely used tool in Marketing, the NPS comes with a number of disadvantages specifically for Product Managers:
It is crucial that the NPS is calculated on a large enough sample size. Specifically for companies in B2B, it may turn out to be challenging to convince enough users to provide that feedback, however simple it is.
The NPS is a statement about the complete product. Specifically for larger products with lots of modules and functions, it is impossible to derive insights about a specific area inside the product that needs improvement.
Oftentimes, the NPS survey comes out of the blue for the users. As the product vendor, you don’t understand the specific situation, such as: Which tasks were users trying to complete? Have they been in a stressful situation when responding to the NPS survey? Did they just have a bad argument with their boss? All of that will surely influence whether they act as a Promoter or not.
Imagine you are using a tool to report major damages or even human casualties. Suddenly an NPS survey shows up. How will you feel? The tool might be perfect for that scenario – but it is just inappropriate to ask such a question in these situations.
As the name indicates, the Customer Satisfaction Score (CSAT) is another metric for customer satisfaction. However, different than NPS, the CSAT allows one to collect feedback on a specific interaction, such as a completed task, a customer support interaction, or a purchase.
The actual calculation of the CSAT is less standardized but typically a simple scale is offered (as with NPS) ranging from “0 = very dissatisfied” to “5 = very satisfied” based on which the CSAT is determined as follows:
Since the CSAT allows measuring customer satisfaction in relation to specific customer interactions, it allows taking actions accordingly in order to optimize the product or service.
The Customer Effort Score (CES) is another metric that allows to narrow down to specific functions or features of a product. Of course, there are also usage scenarios in other areas, such as “how easy was it to return your purchase?” However, for product teams, the main benefit of CES is that it can be applied to any task immediately after the user has completed that task.
Based on responses along this Likert scale, the CES score can simply be calculated via
As with CSAT, there is no universal benchmark for the CES due to the different ranges used in measuring. A few more aspects make the CES worth considering by product teams:
The notion that companies must go above and beyond in their customer service activities is so entrenched that managers rarely examine it. But a study of more than 75,000 people interacting with contact-center representatives or using self-service channels found that over-the-top efforts make little difference: All customers really want is a simple, quick solution to their problem.
There’s a reason why moving junk food to a hard-to-reach shelf might help us eat less of it: the location is impractical, it’s going to take effort to reach it, and—unless the motivation is really strong—most of the time we end up not actually bothering.