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Understanding Impact Analysis by NPS
Understanding Impact Analysis by NPS

Learn how Impact Analysis enables you to understand how different themes contribute to your NPS

Euan Moore avatar
Written by Euan Moore
Updated over a week ago


When we receive a new comment in your Chattermill Project, our powerful AI automatically applies one or more themes to it in order to help you understand how your customers feel about your product. Impact analysis allows you to see which themes contribute positively to your NPS and which have a negative effect, making it easier to decide where your attention needs to be focused to improve customer experience.

Reinterpreting your NPS

The theoretical minimum that your NPS can be is -100, so the positive part of your NPS is the difference between your NPS and the minimum. Using the example in the graph above, you can think of it as if you have 151 NPS points.

The theoretical maximum that your NPS can be is +100, so the negative part of your NPS is the difference between your NPS and the maximum. Using the example in the graph above, you can think of it as if you have lost out on 49 NPS points.

The positive and negative parts of your NPS are then split among the positive coefficient themes proportional to their individual total effects.

Interpreting the sums

The "contribution to NPS" for the positive coefficient themes should sum up to the positive part of the NPS and the same for the negative coefficient themes for the negative part of the NPS.

If you sum up the absolute values of the NPS points you have gained and the ones you have lost out on, you should get the theoretical maximum amount of NPS points you can obtain, which is 200 since there are 200 points on the NPS scale.

Our analysis can tell you which themes were responsible for the gains and losses on this scale.


Using contribution in comparisons

You can use Impact Analysis to compare two periods of time and the score contributions that different themes had to your NPS over time, as shown in the following model.


Do you include all responses (inc without a comment) when calculating Impact Analysis?

We calculate scores using all responses (with and without responses).

What is the minimum number of responses I need to run an Impact Analysis?

There is no hard minimum threshold, but we would advise having at least a total of 500 responses. Additionally, themes with less than ten responses are filtered out.

Some themes have scores greater than 100; isn't that higher than the theoretical maximum NPS score?

Theme contribution scores can be greater than 100 or lower than -100 because of the way Impact Analysis is calculated. For example, when calculating the positive drivers of CX, we start at -100 (the largest negative number for NPS) to calculate a theme's impact on NPS and vice versa for negative drivers.

I am getting a 'Sample size exceeds maximum limit' error. What does this mean?

The maximum response limit for single Impact Analysis is 150,000 and 300,000 for multiple Impact Analysis. If you reach this limit, we advise adding filters to reduce sample size or contacting [email protected] for a manual export.

Can I add the Impact Analysis chart to dashboards the same way as reports?

Yes. You can add the chart to dashboards as you would with your reports. Once you have made your changes, add a title to the report and click 'Save report'. You will then find this report in the list of reports when adding to a dashboard.

Can I share the Impact Analysis chart with my colleagues or externally?

Yes. Once your chart has been saved as a report, you can share this the same way as your other reports. You will find the share icon in the top right of the app, and you can select your teammates to share with internally or use the link to share externally (those without a Chattermill account will then have read-only access).

I can select Impact Analysis by NPS or Net Sentiment. What is the difference between the two metrics?

The main difference between both metrics is that Net Sentiment reflects the positivity and negativity of comments without taking the score into account, whereas Impact Analysis by NPS also explains the score because we have both sentiment and score used within the calculation.

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