Dabish Digital
Analytics

Heatmaps, explained without the jargon

Teams tend to reach for this after something has already gone wrong. Here is heatmaps without the vocabulary that usually surrounds it.

More dashboards rarely produce more decisions. The teams that stay on top of it are the ones who put it on a calendar rather than a wish list.

The short version

They show where attention goes, not why. Getting it slightly wrong is survivable. Ignoring it entirely is not. If it only works because one person remembers to do something, it does not work yet.

Why people complicate it

Most of the confusion comes from tooling rather than from the idea itself. Getting it slightly wrong is survivable. Ignoring it entirely is not.

Best used to generate hypotheses. None of that requires a large budget, only a decision and someone to own it. The practical test is whether someone new to the project could tell, in a minute, that it had been handled.

Making it stick

Combine with recordings for context. None of that requires a large budget, only a decision and someone to own it. It is the sort of thing that looks like polish right up until it costs you an enquiry.

What this looks like day to day

Data you do not trust is worse than no data, because it gets quoted anyway. Three things worth confirming about heatmaps before you move on:

  • Someone can say what the current setup is without going to look
  • Combine with recordings for context — and you know whether that is true here
  • There is a way to tell whether the last change to this helped

If any of that sounds like a description of your current setup, it is fixable.