Many companies use Net Promoter Score® to measure and manage Customer Experience. Additionally, it is widely accepted as an accurate predictor of Growth, and with good reason. However, the score on its own is insignificant. It is important to note that there is much more to an NPS® program than just the score.
According to Numr, a customer experience management (CXM) company, one of the most common mistakes that companies make is focusing on only the overall score. In fact, companies sometimes miss many crucial aspects of an NPS® program that can provide deep insights. Moreover, this data can be hard to interpret.
Therefore, we have explained below how you should analyse Net Promoter Score®.
How do you analyse Net Promoter Score®?
Mainly, there are two significant types of analysis that companies must implement to utilise NPS® effectively. Furthermore, these steps will help you get the most out of your NPS® program. They are-
- Discriminate Analysis
- Regression Analysis
While, overall NPS® assesses general Brand Health, Discriminate Analysis procures specific insights. In short, it identifies the differences in the NPS® between various subgroups. Furthermore, dividing customers into subgroups based on demographic data leads to granular insights. For instance, you can divide customers into Premium and Non-Premium to prioritise them accordingly. Also, you can also make subgroups based on customer location, i.e. North vs East vs West vs South.
In general, this kind of analysis lets companies map out ongoing trends and formulate strategies specific for each subgroup.
Regression Analysis of Net Promoter Score®
On the other hand, Regression Analysis helps in understand the factors impacting the NPS®. Mainly, it identifies the key drives that are affecting your Net Promoter Score®. This is extremely important. Moreover, a company should know the impact improving one specific area will have on its NPS®. After all, the end goal of any NPS® program is optimising Customer Experience and boosting Growth.
Therefore, performing Regression Analysis is essential to obtain highly actionable data from an NPS® program.
Evidently, as echoed by Forbes, poor customer service costs businesses billions of dollars. In fact, a report revealed that it costs businesses more than $75 billion a year. However, a well-implemented NPS® program can help companies streamline their Customer Experience.
*Net promoter Score® and NPS® are registered trademarks of Bain & Company,
Satmetrix and Fred Reichheld