In common with many research agencies, we’ve been doing our fair share of studies that deliver Net Promoter Score (NPS). I won’t bore you with the full details of what it is, but it’s an arguably neat way of presenting how likely customers are to recommend a brand – using a single figure.
I’ve seen several NPS studies which unfortunately remain just that – just a score. Too often it’s just the numbers reported in each wave, and nothing more – no explanations for the changes in score, no suggested improvements, just ticks in the box. These studies are prime examples of where the investment made in the research is not maximised; they eventually become stale – research for the sake of research is a crime, I’m sure you’ll agree…
That’s not how we do things here. Although tracking NPS can be a very useful measure of a company’s performance, I firmly believe that an NPS study that just picks up the data and reports the numbers is a wasted opportunity. As a minimum, any NPS study should be looking at the reasons behind scores (and most importantly changes in scores) as well as making suggestions on how service and value can be improved, and, as a result, NPS can be improved.
However, there is so much more that can be done with the data that’s typically gathered. There is a wealth of information buried in that ever increasing amount of measurements. We should be constantly looking to interrogate the data, hypothesise, test and suggest improvements. Spending on separate research can sometimes be avoided just by mining data that is readily available. Understanding what’s buried in your NPS study and the value that can be unlocked is often overlooked by clients and agencies alike.
It’s also important not to look at the NPS data in isolation. By integrating NPS with other sources of data, and by looking at how the different sources of data relate to each other we create those powerful “aha” moments of real clarity, which would otherwise remain locked if the data sources were used in isolation…
Let’s face it, running a tracker can seem repetitive, “churning” out results for each wave. But changing thinking to ‘how can I discover more’ brings a sea change in results. I found that automating the “must haves” and starting each analysis wave with “what else can we uncover?” is not only far more interesting for researchers, but also adds tremendous value to our clients.
So don’t forget – get the basics right first and foremost for any NPS study, then put your market research detective hat on, and go find those buried clues in the data!