Are you getting everything you can from your Net Promoter Score?

For many organisations, the Net Promoter Score (NPS) is a critical measure of customer experience and satisfaction. NPS is a measurement of advocacy, asking customers how likely they would be, on a scale from zero to ten, to recommend that company to others. Yet we often see companies wasting their NPS measurement programs and missing out on much of the insight they can provide.

NPS works for many companies for good reason – it’s a single number that is easy to collect and easy to understand. Those involved in the day to day management of NPS often realise that while distilling customer satisfaction to a single metric makes tracking and sharing simple, this simplicity comes at a cost: it’s not always simple to know what drives your NPS. So while you might have a score, you are left with no idea of why your customers scored you the way they have or what you can do to improve.

Some try to overcome this with a follow up open-ended question asking why the customer scored that way. An open-ended question allows customers to provide feedback on their terms, using their own words, which can reveal a wide range of issues and even identify problems that you may not have anticipated.

However, analysing and understanding open-ended text data can be time consuming and difficult. Coding or word clouds might be convenient but they only reduce the rich, qualitative nature of open text responses to simplistic measures that lack the quality and depth of insight of the originals. In the worst cases it’s just too hard and the responses are ignored completely – and all that insight is lost!

This is where text mining comes in. Text mining automates the sorting and classification of text data, allowing you to quickly identify themes, phrases and words that occur throughout the responses.

It’s important to remember that text mining does not provide all the answers and is not a black box – it requires human input to ensure the classifications make sense and to interpret the outputs. Edentify’s approach involves building customised rules, specific to your brand and category, then monitoring and refining these to continually improve the analysis.

Perhaps the most powerful aspect of our approach is that once these classifications and themes are in place, Edentify’s online toolbox allows our clients to refer to the original responses, meaning the depth and insight of the customer’s own words becomes simple to read and interpret.

What text mining does best is to take care of most of the manual, repetitive tasks quickly, freeing the human expert to focus on learning and deriving insight. The result is that large unwieldy volumes of diverse text responses become a valuable, usable data source that can add a new level of understanding to your company’s NPS score.

While having one number to measure customer satisfaction is appealingly simple, it is rarely enough to provide the insight needed to take action. To extract real meaning we need to look beyond the numbers to truly understand what customers think.