Reporting & Insights

Report – Net Promoter Score (NPS)

NPS

This article is part of our tutorial about how to get the most from your Emolytics report. We will go through each chart visible in the “Net Promoter Score (NPS)” section of your Emolytics report.

Net Promoter Score (NPS) is a famous marketing KPI focussing on likelihood of customers to recommend a brand. It focus on promoters and detractors of the brand.

Here is the list of insights you can find:

Distribution of “Likelihood to recommend” (LTR)

This chart presents the distribution of the “likelihood to recommend” (LTR) given by the user, from 0 to 10, while answering the question “How likely are you to recommend us?”. The NPS score computation focuses on promoters (LTR of 9 to 10) and detractors (LTR inferior or equal to 6).

In this example, many customers are located between 7 and 8 and won’t affect your NPS. Those customers appreciate your brand and will probably buy again but they are not ready to recommend it to peers. Improvement should be done in order to convert them into promoters.

NPS score by device and referrer

This matrix view helps you visualize which traffic source and/or device type performs high or low in terms of NPS. When working on specific points and strategy, you should keep an eye on this graphic and notice positive changes in this matrix.

The greener the color, the higher the NPS. Mousing over each cell allows you to view specific data such as total respondents.

In this example, the NPS is negative. Therefore, results are really bad.

N.B. Some referral category might not be detected and therefore the sample size might differ from the global sample size.

NPS evolution

This shows the evolution of the NPS over time. These data can be viewed by Days / Weeks / Months by using the filter above.

When working on specific points and strategy, you should keep an eye on this graphic and notice positive changes in this matrix.

Number of respondent (NPS) – Evolution

This shows the amount of votes collected over time for the NPS question. These data can be viewed by Days / Weeks / Months by using the filters above.

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