Analytics setup: a practical guide

It comes up on almost every project, usually later than it should. This guide covers what analytics setup actually involves, where it usually goes wrong, and how to tell whether yours is in reasonable shape.

Data you do not trust is worse than no data, because it gets quoted anyway. Nothing below assumes a large team or a large budget — most of it is a decision somebody has to make and then write down.

Why it matters

Data you do not trust is worse than none. Small and consistent beats large and occasional here. If two people in the business would answer this differently, that gap is the actual problem.

For most businesses the question is not whether this matters but how much of it is worth doing right now. That depends on what you are trying to achieve in the next few months, not on best practice in the abstract. Getting it slightly wrong is survivable. Ignoring it entirely is not.

How we handle it

Filter internal traffic from day one. The teams that handle this well are rarely the ones with the biggest budgets. Check it against what you would want a competitor's site to get wrong.

More dashboards rarely produce more decisions. The version that works in practice is usually less elaborate than the version described in the guides.

Decide what you will act on before you track it. Where this goes wrong is almost never a lack of knowledge. If it only works because one person remembers to do something, it does not work yet.

A working checklist

If you want a quick read on where you stand, work through this. Anything you cannot answer confidently is where to start.

• Data you do not trust is worse than none
• Filter internal traffic from day one
• Decide what you will act on before you track it
• Someone is named as the owner, not just assumed to be
• There is a date in the calendar to review it again
• The decision and the reasoning behind it are written down somewhere findable
• You could explain the current setup to a new hire in five minutes

Common failure modes

The most common failure is not doing this badly. It is doing it once, during a launch, and never revisiting it. Circumstances move, the setup does not, and the gap widens quietly until something breaks or somebody notices the numbers.

• It was configured during a launch and has not been touched since
• Different people in the business believe different things are true about it
• There is no way to tell whether the last change helped or hurt
• The only person who understands it has left, or is about to

Measurement is only useful when someone has agreed in advance what they would do differently. The reasoning matters more than the rule, because the rule has exceptions.

How we approach it

On our projects this gets handled during the build rather than added afterwards, because retrofitting it costs several times more than including it. We write down what was decided and why, so the next person to touch it is not guessing.

If you are working with someone else, the questions worth asking are simple: who owns this, how will we know it is working, and what happens when it needs to change?

Turning this into a decision

Pick the single item from the checklist above that would cause the most trouble if it turned out to be wrong. Fix that one, confirm it worked, then move on. Pick the one that would hurt most if it failed, and start there.