What Are Confettis And How To Understand Them

Confetti, or click maps, are visual representations that show the interaction of visitors on our website. We observe points for each click made by a visitor. In addition, each click has a color that represents a specific category within the different types of areas in which it can be classified.

Confetti from Nelio A / B Testing pricing page.
Confetti from Nelio A/B Testing pricing page.

When you create a heatmap test on a WordPress page, Nelio A/B Testing will track the visitors who access that page and the interaction they make with the mouse. The clicks that visitors make can be seen in the confetti that you find in the results of the heatmap test.

In the confetti you will see the hotspots of your website, which are those that receive the highest number of clicks from your visitors. To interpret the results you must take into account that areas with more points indicate a greater degree of interaction, and therefore relevance, in the different elements of the page.

For example, imagine that you have a button on your page that you want your visitors to see and click on. If when you see the results of the confetti on that page you do not see points above the button, something is not working as it should on your page. Nobody clicks that button.

The confetti helps you see clickable elements that are not being clicked and non-clickable areas that are being clicked by mistake. In this way you can make the changes you think appropriate to see if you get visitors to click where you want. Of course, these changes should be tested with an A/B test.

Different filters that you can select in the confetti to see the clicks.

As we have said before, the results can be filtered by the following areas of interest:

  • Web browser used
  • Country
  • Day of the week
  • Device type used
  • Operating system
  • Time of the day
  • Time to click since the visitor lands on the page
  • Window width

Changing the filter from the right sidebar of the confetti you can vary the points that are seen in the report as well as their color. With all this information you can extract ideas of possible changes to test in A/B tests and thus improve the conversion of your website.