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A/B Testing a Low-Traffic Site Without Fooling Yourself

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October 26, 2026

7 min read

With a few thousand visitors a month, most A/B tests can only detect enormous differences, and most "winners" are noise. The arithmetic, what to test instead of button colours, how to count exposures properly, and the rules we use on our own site.

A/B testing
Experimentation
Analytics
Conversion
Statistics

The arithmetic nobody wants to do

To detect a change from a 3% conversion rate to 4.5%, a 50% improvement, with the usual 95% confidence and 80% power, you need about 2,500 visitors in each variant. To detect 1% becoming 1.5%, about 7,700 each. A site with 3,000 visitors a month testing a 1% conversion would wait five months for one answer, and a 10% improvement would never be detectable at all.

This is why most small-site tests "find" winners: they stop when the chart looks good, and with small numbers the chart looks good by chance a lot of the time.

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Test big things

  • The offer: a free assessment against a fixed-price package.

  • The positioning: a senior individual against a team — the test we are running on our own hero line.

  • Which service leads the home page.

  • Whether pricing is shown.

Differences this large can move conversion by tens of percent, which a small site can detect in weeks. Button colours and microcopy cannot.

Count exposures, not page loads

A visitor who never scrolled to the variant did not see it. Counting them dilutes both arms equally and hides a real difference, so record an exposure only when the variant is actually on screen — we record it once per page view when half the slot is visible. Assign by a hash of the visitor id so the same person always sees the same variant, and analyse per visitor, not per page view, so one enthusiastic reader cannot swing the result.

Our rules

  1. Decide the sample size and the success event before starting, and do not look at significance until you reach it.

  2. Report a range, not a single number: if the two variants' 95% ranges overlap, the honest answer is "not yet".

  3. Use a leading metric when the real goal is rare — clicks toward booking alongside bookings — but decide on the real goal.

  4. One test per page at a time.

  5. When a test ends inconclusive, keep the variant you prefer for other reasons. "No detectable difference" is a result.

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As of October 26, 2026. Provided as is, for general information, and accurate to the best of our knowledge on the date shown. Not legal, compliance, tax, financial or other professional advice. Prices, limits and vendor services change; check current vendor documentation before relying on anything here. Terms of use.