The Frequency axis shows how often a content theme has been mentioned while the Impact axis gives us the total impact onto Likelihood-to-recommend when more of this content theme would be mentioned. The size of the bubble represents
the product of Frequency and Impact. It gives us the share for explaining the actual NPS score. Click onto a bubble and you will see example Verbatim randomly selected from the study.
The chart visualizes the power of direct effects. On the left, you can find the driver and context variables. On the right, you can see the final outcome such as Satisfaction. In between is the intermediate variables displayed, such as Sentiment. An intermediate variable is influenced by drivers and at the same time it is a driver for outcome variables. Connections are red, if the impact is negative and they are getting large if the impact is high. By hovering over the lines, you can see the actual impact level. It shows the measure of Average Simulated Effect. It represents the changed impacts that is caused by the driver.There is a reason behind that Key Driver vs. Casual Graph chart show slightly different numbers. While Key Driver chart shows normalized, total Impact values, Casual Graph shows non-normalized, direct (not total) impact values.
This chart explains why the NPS score has changed. It weights the changes in frequencies of content themes between actual and last term with its impact for loyalty. Change happens only when important categories change.
This is a simulator that predicts the resulting NPS score when frequencies of mentioning’s will change. It facilitates internal discussions, gives the opportunity to simulate scenarios and later proved that prediction turn reality. Every slider shows a marker which is the predefined target value for this topic