Funnel analysis: a practical guide

This is cheap to get right at the start and expensive to retrofit. This guide covers what funnel analysis 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 this earns attention

The biggest drop-off is the best place to work. 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.

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. It is worth being explicit about, because assumptions differ quietly.

What good looks like

Segment by device before drawing conclusions. None of that requires a large budget, only a decision and someone to own it. Anything you cannot measure here, you are deciding by taste, which is fine as long as everyone knows it.

Measurement is only useful when someone has agreed in advance what they would do differently. The version that works in practice is usually less elaborate than the version described in the guides.

A leaky funnel wastes every pound of ad spend. None of that requires a large budget, only a decision and someone to own it. The teams that stay on top of it are the ones who put it on a calendar rather than a wish list.

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.

• The biggest drop-off is the best place to work
• Segment by device before drawing conclusions
• A leaky funnel wastes every pound of ad spend
• 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

Where it usually goes wrong

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

More dashboards rarely produce more decisions. Small and consistent beats large and occasional here.

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. If you are not sure where your systems currently stand on this, it takes us about an hour to find out.