In this article
What is NPS
NPS is a trademarked metric that reports a number between -100 and 100 and captures in aggregate the propensity of a company's customers to attract and refer new business and/or repeat business. NPS is not expressed as a percentage, but as an absolute number lying between -100 and +100. For instance, if you have 25% Promoters, 55% Passives, and 20% Detractors, the NPS will be +5.
How to Calculate NPS
Each respondent needs to be assigned a value of either -100, 0, or 100, depending on the rating they gave to the “likely to recommend” question.
We then calculate an average that sums the value for each respondent. The sum is then divided by the number of respondents that gave a value. This calculated average is the NPS
In Infotools Harmoni, there are a couple of options for calculating this average:
Option 1 - Values in a Standard Axis
For this, you first need to create netsLearn more about constructions. , in the 11-point scale variable.
Then, you need to assign valuesLearn more about assign values for average calculations. to the Promoter, Passive and Detractor Nets.
For example:
| Item |
Net |
Value
|
|
Promoter |
Top 2 - Usually 9 and 10 | 100 |
|
Passive |
Next 2 - Usually 7 and 8 | 0 |
|
Detractor |
Bottom 9 - Usually 0 to 6 |
-100 |
Watch the GIF to see the Promoters, Passives and Detractors created in a user created axis.
Please note that when analyzing your NPS score you may need to select Total (qualified) in order to exclude the missing values, in other words, those respondents who did not give an answer to the Likelihood to Recommend question.
Option 2 - Values in a Measure
The advantage of a measure is that you can apply the value to the body of the table, e.g. have Age x Gender, with the NPS being what is shown in each cell. Having a measure is also useful when you want to look at NPS applied to a variable that has values assigned to its elements (e.g. exact age).
For this, you first need to create a measureLearn more about how to create measures. to assign the appropriate -100, 0 and 100 values to each respondent. Records to be excluded from the measure’s count need to be assigned a NULL value.
Use If statements to assign the values to the responses within the “likely to recommend” question.
i.e. if(Recommend.(9 or 10), 100,if(Recommend.(7 or 8), 0,if(Recommend.(0,1,2,3,4,5,6),-100,null)))
Where to from here?
Learn more about Smart Analysis.