The Net Promoter Score is most people's go-to measure for evaluating companies, brands, and business units. However, the standard way of computing the NPS - subtract the promoters from the detractors - is a bit of a pain. This article describes how easy it is to recode the data so that you can compute the NPS by computing the average, and you get exactly the same answer as you do when using the standard way.
For example, the table below shows data for a particular campsite. If we add up the first 7 categories, so 0 through to 6, 18.13% of people in this data set are Detractors. Adding up categories 7 and 8 gives us 28.94% Passives and the remaining 52.94% are Promoters. So, in this data set, the NPS score is 34.8 which is OK.
This QScript looks for likelihood to recommend questions in your project and creates new variables that are recoded to display the NPS score.
- Import a data set: Home > New Data Set (Data) that contains a likelihood to recommend question(s).
- NPS questions are those questions that contain the words likely or likelihood in the question name, or whose value labels contain the string likely, and which are 11-point scales. 10-point scales are also recoded, however, NPS scores strictly only apply for 11-point scales.
- Select the variable set containing the likelihood to recommend data from the Data Sets tree and select Anything > Data > Variable(s) > New > Ready-Made New Variable(s) > Recode Net Promoter Score (NPS) Variable(s). This will create a new variable set with recoded data.
- Recoding is conducted based on numbers found in the category labels. Those categories whose labels contain numbers less than or equal to 6, Detractors, will be recoded with a value of -100, those categories whose labels contain a 7 or 8, Passives, will be recoded to a value of 0, and categories with labels 9 or 10, Promoters, will be recoded to a value of 100. Categories that look like standard Don't Know questionnaire options will be set as missing and will not be included in the calculation of the NPS.
- Drag the variable set onto the page, so that it creates a summary table of the average for each variable in the variable set. This produces a table that shows the Average that is the NPS score.