Let’s say you have a form with an open comment field, with the question: How could we improve our website? As we are only interested in the feedback items of people who have answered this question, we filter on ‘With comment’ in the feedback inbox. This gives us a first insight of the type of comments people leave. You will probably see that some comments are fairly similar.
Let’s say we see a lot of comments that are related to payments methods. It would be great if we could label/group all these kind of comments. This can be done by automated tagging. Therefore, we create an automated tag:
Then, in the feedback inbox, we filter on this tag:
Our feedback inbox would look like this
We, however, are not only interested in payment method comments, but also in comments regarding the return policy. We create another automated tag condition for the same feedback form and add it as a filter in the inbox:
Similarly, we add the tags ‘Contact’ and ‘UX’.
Now it’s time to visualize our data. This can be done by creating a chart. In the chart, we would like to see how often comments are related to payment methods, return policy, contact and UX.
We add the How could we improve our website? element to the chart, set the data calculation to 'Count', and group against ‘Tags’. As chart type, we use the column chart and colour it by point. Furthermore, to make the chart more readable, we show the data labels in the chart. The resulting graph will look like this:
From the above, we can see that, within the given date range, 13 feedback items were about the payment method, 4 about the return policy, 3 regarding contact, 2 about UX and 7 about something else for which no tag was given.