Measuring NPS is simply a case of asking the following question:
‘How likely is it that you would recommend [Organisation X/Product Y/Service Z] to a friend or colleague?’
It uses a scale of 0 (not at all likely) to 10 (extremely likely) and based on their responses, customers fall into one of 3 categories:
- Promoters respond with a score of 9 or 10
- Passives respond with a score of 7 or 8
- Detractors respond with a score of 0 to 6
The NPS score is calculated by subtracting the % of detractors from the % of promoters while ignoring the passives. For example, if 10% of respondents are detractors, 20% are passives and 70% are promoters, your NPS score would be 70-10 = 60.
See the simulation below to see how NPS changes as detractors are turned to promoters through your program.
Designing an NPS survey – think about more than just one question
Measuring NPS alone isn’t particularly useful, other than giving you a benchmark score for your customer experience.
But how do you improve it? And how do you understand what’s driving your NPS score?
This is where key drivers come in. By understanding your customers experiences in more detail, you can establish the most important aspects of the experience that influence that score.
Say for example you’re an online retailer. When a customer has completed a purchase with you, you serve them with a customer survey. As well as asking how likely they are to recommend your company, you might ask them:
- How easy was it to find the product you were looking for?
- What made you buy from us today [multiple choice]
- How easy were the following parts of your journey? [multiple choice]
How easy were the following parts of your journey? [multiple choice]
But further than this, you could also use operational data form things like your website analytics to layer in elements like:
- Time on page
- Referral url
- No. of pages viewed
- Page load speed
That’s just a snapshot of the kind of data you could pull in – the more you include, the more data points you have to identify what’s really driving your NPS score.
Once you have the data points you need, you can run analyses like Key Driver Analysis or multivariate regression to identify the priority areas to focus on to improve the customer experience and your NPS scores.