A/B Testing That Actually Moves Revenue

Most teams run A/B tests wrong — peeking at results early, stopping when they see a "winner," implementing changes based on statistical noise. We do it properly: 800+ tests, zero tolerance for false positives.

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800+ tests run · 95%+ significance threshold · No false positives

How Our A/B Testing Works

Every test follows the same rigorous process — from research-backed hypothesis to statistically verified win.

1

Research

We audit your analytics, run heatmaps, and study session recordings to form data-backed hypotheses — not gut-feel guesses.

2

Design

Test variants are designed around psychological principles and CRO frameworks. Sample sizes are calculated before a single line is written.

3

Run

Tests run for the required sample size and time — never stopped early, never peeked mid-test. We control for day-of-week effects and novelty bias.

4

Analyse

Full segment analysis by device, traffic source, new vs. returning. We extract learning whether the test wins, loses, or is inconclusive.

5

Compound

Winners get implemented. Every finding feeds the next hypothesis. After 50+ tests, your test log is a competitive moat no competitor can replicate.

What We Test — and in What Order

We always start where the data shows the biggest leverage — not where it's easiest to change something.

Headlines & Value Proposition

The single highest-leverage element on any page. A headline rewrite that fundamentally improves message clarity consistently outperforms button colour tests.

CTA Copy & Placement

Button text, position, size, and surrounding copy. First-person CTAs ("Start My Trial") outperform second-person ("Start Your Trial") in the majority of tests.

Social Proof Architecture

Where testimonials are placed, which proof formats work for your audience, and how to position proof at the moment of maximum decision anxiety.

Checkout & Form Optimisation

Field count, order, error messaging, guest checkout, and payment options. Checkout is typically where the biggest revenue leaks are — and where tests have the most impact.

Want to Understand A/B Testing Before We Talk?

Read our comprehensive guide on running A/B tests correctly — sample sizes, statistical significance, segmentation, and the exact mistakes that produce false positives.

Read: A/B Testing Best Practices

A/B Testing Questions, Answered

How many A/B tests can you run each month?
We typically run 3–6 concurrent tests depending on your traffic volume and number of testable pages. We prioritise by expected revenue impact — fewer, higher-leverage tests outperform a high volume of trivial ones every time.
How long does a typical A/B test take?
Most tests run 14–28 days. We calculate exact sample sizes upfront — we never stop tests early or peek at mid-test results, which is how most teams accumulate false positives. Duration depends on your traffic volume and the minimum detectable effect we're targeting.
What if our site doesn't have enough traffic to A/B test?
Below roughly 1,000 monthly conversions on the target page, standard A/B tests produce unreliable results. We focus instead on heuristic CRO — qualitative audits, session recordings, and direct implementation that produce real lifts without requiring statistical testing.
What elements do you test first?
Headlines and value proposition first — highest leverage on any page. Then CTAs, hero sections, social proof placement, and checkout/form design. We always prioritise by traffic × estimated impact, so the exact sequence varies by your funnel.
Do you need developer access to run tests?
Usually not. Most tests run through a tool (VWO, AB Tasty) that modifies pages via JavaScript — no code deployments needed. For server-side or complex tests, we coordinate with your dev team. The vast majority of CRO tests are tool-based.
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Ready to Run Tests That Actually Matter?

Book a free strategy call. We'll review your current testing setup and show you exactly what we'd test first and why.

  • Free audit — no credit card
  • Results within 30 days
  • No long-term contracts