Net Promoter Score® is the ONE number companies need to grow. At least, as per Fred Reichheld’s seminal paper, the one figure that all companies must focus on isn’t total sales or annual growth. Instead, it is Net Promoter Score®. Although, it is a loyalty metric, is has proven to be a strong predictor of growth. In fact, Net Promoter leaders “outgrow their competitors in most industries by an average of 2.5 times.” (Fry, 2006)
However, there is much more to an NPS® program than just the score. Actually, the score by itself is unimportant. Instead, what’s crucial is what it represents. One must analyse it proficiently to obtain the deep and granular insights that NPS® can provide. Furthermore, it should be used to transform your company by placing ‘Customer service’ at the heart of all marketing activities. NUMR, a customer experience management (CXM) company uses Discriminate and Regression Analysis to analyse our clients’ Net Promoter data. However, to analyse Net Promoter Score® correctly, it must be connected to financial data.
HOW TO CORRECTLY ANALYSE NET PROMOTER SCORE®
Even though, NPS® is famously know as a Loyalty metric, it is also a growth metric. To put it another way, NPS® tracks and predicts revenue growth. For instance, on average, “a 12-point increase in NPS® leads to doubling of a company’s growth rate.”
Thus, the only right way to analyse Net Promoter Score® is to connect it to Financial Data. You must know the effect a 5% increase in your NPS® has on your bottom line.
NPS® is not a statistic collection exercise. Unarguably, it must be used to track and predict the financial outcomes. Any NPS® program is incomplete without associating it with Financials.
Mainly, we use two methods to analyse Net Promoter Score®. Namely, Discriminate and Regression Analysis.
DISCRIMINATE ANALYSIS OF NET PROMOTER SCORE®
This analysis is used to identify the differences in NPS® between various sub-groups. For example, you can divide customers based on demographic data like East/West/North/South and obtain granular insights about each separately.
Additionally, you can compare them to map out trends and formulate targeted strategies.
On the other hand, Regression Analysis helps understand the factors impacting the NPS®. Chiefly, companies use it to discern the impact improving one specific area will have on their NPS®.
Also, to learn how to analyse Net Promoter Score®.
In brief, the only way to correctly analyse the Net Promoter Score® is to link it to your company’s Financial Data. Moreover, it should be used to track and predict financial outcomes. An NPS® program that doesn’t connect NPS® to Financials is lacking and incomplete.
Do you wish to make the most out of your NPS® program and streamline your CX? Contact us.
*Net promoter Score® and NPS® are registered trademarks of Bain & Company, Satmetrix and Fred Reichheld