Conversion rate optimisation has a reputation as something only large companies with massive traffic can do properly. The reasoning is that A/B tests need statistical significance, and statistical significance needs volume. That is true for some tests. It is not true for all of them.

What you can test with low traffic

With fewer than 5,000 monthly visitors, traditional A/B tests are slow to reach significance. But qualitative methods work at any traffic level. Session recordings, heatmaps, and five-question exit surveys can tell you why people are leaving a page without needing a large sample. We use Hotjar for session recordings and a simple Typeform for exit surveys. The insights are often more actionable than a split test result.

The one metric that matters first

Before you run any experiment, you need to know your baseline conversion rate and what counts as a conversion. For most small business sites, a conversion is an enquiry form submission or a phone call. Set up goal tracking in Google Analytics 4 before you do anything else. If you do not know your current rate, you cannot know whether anything you change is working.

The highest-impact changes for most sites

In our experience, the changes that move conversion rates most reliably are: a clearer headline on the homepage (one that names the problem, not the company), a shorter contact form (three fields convert better than seven), and a faster page load time on mobile. These are not exciting findings. But they are consistent. We see them on almost every site we audit.

How we structure a CRO retainer

Each month we run one structured experiment. We write a hypothesis (changing X should increase Y because Z), implement the change, measure for four weeks, and write a one-page report on what moved and what did not. The hypothesis log is cumulative, so after six months you have a record of what works on your specific site with your specific audience. That is more valuable than any single test result.

When to bring in paid traffic

If your organic traffic is too low to generate meaningful data, paid traffic can accelerate the learning. But we recommend fixing the obvious structural problems first. Sending paid traffic to a slow, confusing site is expensive. Get the site to a baseline standard, then use paid traffic to speed up the experiment cycle.

Start with what you can see. Session recordings, a clear baseline, and one honest hypothesis. That is enough to begin.