A/B & Multivariate Testing

Make revenue decisions based on real user data, not educated guesses.

Conversion rate optimisation runs on statistical proof, not opinion. We pit real variations of your site against each other until we know - not guess - what actually converts.

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Why guessing is expensive

"I think this version is better" isn't a strategy.

Every unvalidated design decision on a live site is a bet with your traffic as the stake. A headline that feels stronger. A button that looks more prominent. Without a real test, you're guessing - and guessing wrong costs you conversions you'll never know you lost.

Testing replaces opinion with evidence. Not "we think," but "we measured."

What we run

Built on evidence, not instinct.

  • Hypothesis formulation.

    Data analysis to identify the high-impact test opportunities across your actual conversion paths - not random elements picked because they’re easy to change.

  • A/B split testing.

    A direct comparison of two distinct page variations, run until the result is real - not called early because one number looked good on day two.

  • Multivariate testing.

    Simultaneous testing of multiple page variables at once, for environments with enough traffic to support it - finding the winning combination, not just the winning single change.

  • Statistical validation.

    Rigorous analysis before we call a result. A test that "feels" like it’s winning and a test that’s statistically proven to win are different things - we only act on the second.

What it changes

Real impact, not vanity metrics.

Higher conversion rates from the traffic you already have. Lower customer acquisition costs, because you're converting more of what you're already paying to attract. Maximum return on the traffic investment you've already made - before spending another rand on more of it.

FAQ

Common questions

How long does a test need to run?

Until it reaches statistical significance - which depends on your traffic volume and the size of the effect you’re testing. We won’t call a winner early just because a deadline is approaching.

What if a test doesn’t win?

Still a result. You’ve learned what doesn’t move the needle, cheaply, before rolling it out sitewide. A testing programme that only ever "wins" isn’t testing rigorously enough.

Do I need huge traffic to test?

A/B testing needs meaningfully less traffic than multivariate testing. If your volume is limited, we’ll recommend A/B over multivariate, or focus testing on your highest-traffic pages first.

What’s the difference between A/B and multivariate testing?

A/B tests one change at a time, isolating its effect cleanly. Multivariate tests several variables simultaneously to find the best combination - but needs significantly more traffic to reach reliable conclusions.

Contact

Stop guessing. Start testing.

We'll look at your highest-value pages, identify where a real test could move the needle, and show you what a testing programme built on actual statistical rigour looks like.