Almost every organization has an interest in customer satisfaction scores, net promoter scores, or customer sentiment score. It’s important to understand the purpose of each of these scores and why they are important. All three of these are proxy metrics which highlight different benefits.
A customer satisfaction score (CSAT) measures how satisfied a customer is with the product or service they purchased. If members get quick responses to questions in the community, learn how better to use the products, and find a like-minded group of fans, their satisfaction with the product is likely to rise. This score can be collected via a simple survey asking members to rank on a scale of 1 to 10 how satisfied they are with the product or service.
The customer sentiment score measures attitudes towards the brand. Whereas CSAT determines how satisfied a customer is with a product, the customer sentiment score measures attitude towards the brand. Whereas CSAT is predictive of a customer continuing to purchase that product, the sentiment score is predictive of a customer buying future (new) products and services from the brand. In practice, brands are more likely to rely on CSAT or NPS scores.
The net promoter score (NPS) score measures whether a customer is likely to refer others to also purchase the product from the brand. The NPS score is often considered predictive of company growth (although some consider CSAT a better measure). Clearly, the two are closely related.
Any time you receive an email asking you to rate, on a scale of 1 to 10, how satisfied you are with the product/service, how you feel towards the brand, or how likely you are to recommend a product/service to a friend, you can be sure it’s from an organization trying to measure one of the above.
Fortunately, the methods for calculating CSAT, NPS, or CES are identical and follow the same pattern from before. The only challenge is converting these scores into a financial value. This is because the relationship between these scores and revenue is curvilinear (i.e. it follows a curve). For example, a customer satisfaction score going from a 2 to a 4 is not going to have a big impact. The customer still won’t purchase the product again.
However, a customer satisfaction score rising from a 7 to a 9 is going to have a big impact. This takes a product from the realm of just average to highly satisfied. This means they are likely to become devoted customers. This curvilinear relationship makes identifying the value of increasing the satisfaction score difficult. It’s possible to calculate the increase and convert it into a financial value, but you need an advanced understanding of statistics to do it. M .
In our research, we discovered that most organizations do not directly convert the customer satisfaction score into a value metric. Most executives are happy enough to learn the increase in these scores as a % rather than as a financial value. We also measure increased customer retention and spending through more direct channels. Therefore, in this single situation, we are looking for the average increase in score (as a %) as opposed to a direct financial value.
Using CSAT as our example (you can convert this to NPS/sentiment easily), we have outlined the following process.
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