Dabish Digital
Analytics

A short guide to attribution

There is no clever trick in this one, just a handful of decisions worth making deliberately. Everything we would tell a client about attribution in the time it takes to drink a coffee.

More dashboards rarely produce more decisions. It rarely shows up as a line item, which is exactly why it slips.

The reason this keeps coming up

Last-click attribution overvalues the final touch. There is a version of this that is over-engineered, and it is worth avoiding. If it only works because one person remembers to do something, it does not work yet.

The practical version

No model is correct, some are useful. Getting it slightly wrong is survivable. Ignoring it entirely is not. Write the reasoning down alongside the decision, because the reasoning is what changes first.

The mistakes we see most

Use it to allocate budget, not to settle arguments. Where this goes wrong is almost never a lack of knowledge. It is worth deciding this deliberately rather than inheriting whatever the last person set up.

In practice

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

  • Someone can say what the current setup is without going to look
  • Use it to allocate budget, not to settle arguments — and you know whether that is true here
  • There is a way to tell whether the last change to this helped

Worth checking on your own setup before it becomes someone else's problem to fix.