How can I analyse the organisational results of an engagement survey?

You can find the results of your engagement surveys clicking on 'Organisation' at the top of the bar and then on 'Engagement' on the left. Here you will find a dashboard where you can view the results for each survey. In this article, we explain how to read this dashboard and analyse the results.


General scores, filters and exports

The scores in the dashboard lie between 0 and 100. All scores below 65 turn red. Not because this is insufficient, but because it gives you quick insight into the themes or questions which you can improve most.

The eNPS score is calculated differently and lies between -100 and +100. A negative eNPS is coloured red and a positive eNPS is coloured green. In this article, you can read how the eNPS is calculated.

You can also create an export the results. If you click 'Export', an Excel is downloaded with the results, based on the selected filters. You can use this, for example for an overview of all written comments per question, or calculate the average grade of the eNPS (this often gives extra context to the eNPS score).


At the top of the dashboard, you can see the overall scores, based on the selected filters. You can filter the dashboard by survey, by teams, and by functions.

  • Engagement: here you see the total engagement scores, based on all answered questions
  • eNPS: this shows the total eNPS score
  • Participation: here you see the number of employees who have filled in the survey

Furthermore, you can also see the overall scores per theme. If you click on one or more themes, the overview below is filtered based on the selected themes.


Analysing results

You can analyse the results in depth using the various overviews. You can set the overview on the heatmap, per theme, per question, and per answer. Below we explain how to analyse the results per overview. The most valuable overviews are the heatmap and the overview per question.

Results are always displayed anonymously. In this article you can read how anonymity is ensured in Dialog.



Via the heatmap, you can view the results per team or per department. This gives you quick insight into which teams score high on certain themes and which teams still can still improve the most in certain themes.

If you have clicked on a theme in the overview per theme, the heatmap shows the results of only the selected theme.

When you click on one of the boxes, a screen opens on the right-hand side where you can see the written explanations for a theme. This is very valuable as it provides context on why employees have given a particular score. You also have the option here to respond to answers via the 'Comment' button below an answer.


Per theme

When you set the overview per theme, you get to see the results by theme. You can click on the arrows left of the themes to see the scores per sub-theme, and even per question. This overview gives you quick insight into which (sub)themes score the highest, and which themes can improve the most.

Again, when you click on a theme or question, you will see all written explanations.



Per questions

When you put the overview per question, you get to see the scores of all the questions asked. This view is extremely valuable to be able to see very specifically what topics to focus on. By clicking on the heading 'Score' you can sort the questions from high to low and low to high. That way, you can immediately see which questions have scored the highest and which the lowest. This helps you to get started with your analysis and want to make a top list of topics to work on.

When you click on a question, another screen opens again where you can see the written explanation for each question. This gives you extra context on how the score was arrived at.


Per answer

Finally, you can also display the overview per answer. You then see all written explanations of the questions. You can also arrange the overview to show all answers, including those without written remarks. You can respond to answers anonymously via the 'Comment' button. For example, on all questions with a low score.


Was this article helpful?
1 out of 1 found this helpful