Conversion optimisation

More revenue from the same visitors: measure, test and ship what works.

Sending more traffic to a leaking shop only makes the leak more expensive.

We start where purchase intent gets lost. What is someone trying to understand or do, where do doubt or friction appear, and why?

Then we improve and test where it can make a difference: from category and product pages to cart and checkout.

Not a list of a hundred tips, but a few targeted changes, and we want to know whether they actually improve anything.

We map where people drop off and where the biggest commercial friction seems to be.

We combine behaviour and data with what we see on the site and form hypotheses about why something happens.

We tackle the most important hypotheses one by one: through a test, or a targeted improvement when testing does not make sense.

We look at what changed, what we learn from it and which improvements we roll out for good.

Low conversion does not automatically mean your checkout, product page or button is wrong. The problem can just as well be in traffic, offer, price, stock or expectations.

That is why we first find out where the problem really is before we optimise anything.

Sometimes you have enough traffic to test a hypothesis in a controlled way. Sometimes a problem is so clear that waiting for statistical significance mostly costs time.

We test where it makes sense. We improve where it is logical. And we measure what happens next.

RIT sets direction. M&E moves with it.

We do not start with the button. We start where purchase intent gets lost, and why. Only then do we decide what needs to change, how we test it and what we learn from it.