What is Net Promoter Score?
Net Promoter Score (NPS) is a key performance indicator (KPI) of customer satisfaction. All you need is to ask your customers one question: “How likely is it that you would recommend [brand] to a friend or colleague?”
Anyone who scores a 9 or 10 is considered a “promoter”, while all the unhappy people from 0 to 6 are “detractors”. The NPS is calculated by subtracting the percentage of detractors from the percentage of promoters.
The score is an index ranging from -100 (if you have 100% detractors) to +100 (if you have 100% promoters).
Example: 60% of your survey respondents are promoters and 30% detractors. You subtract 30 from 60, giving you a Net Promoter Score of +30.
It sounds easy enough, but knowing the best way to use and act upon this information is a more challenging step.
How can I use my Net Promoter Score?
As the Net Promoter Score is often used as a Key Performance Indicator for customer satisfaction, it is generally tracked over time to understand if the organization is getting better at overall customer experience or not. It is also common to compare the score to other companies within the same industry to see if you are performing better or worse than your competitors.
What the Net Promoter Score can’t do is to tell you why a certain score was given, and what your customers actually think about you beyond that scale of 0-10. This perhaps one of the most obvious flaws of the Net Promoter Score framework: you won’t know the actual drivers of the score, because that often requires the analysis qualitative data.
So what is the best way to understand the drivers of your Net Promoter Score?
Analyze the drivers of your Net Promoter Score with Explorer
A key feature of our AI-driven text analysis software Explorer is the functionality to analyse texts annotated with metadata. This allows you to tie your text data analysis – the “why” – to a Net Promoter Score metric, directly connecting your insights to the relevant customer score.
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So when working on your next Net Promoter Score survey, add one open text question where you ask for the “why”, for example:
- What made you choose that score?
- How can we provide a better service for you?
- What changes would we have to make for you to give us a higher rating?
Then, when analyzing the answers, you can sort customer responses by score and see answers coming from promoters and detractors separately, or combine them the way you want. It allows an analyst to see the most relevant topics for different categories of customers – what makes promoters happy and loyal, what irritates the detractors most, and what can still be improved to convert more slightly satisfied customers into very satisfied customers.
To summarize: Get more actionable insights about the drivers of your business by simply adding AI-driven text analysis to your next Net Promoter Score project.
Read more about our text analysis software Explorer here.