Ecommerce A/B testing that reaches significance.
Most A/B tests are called too early on too little data. We run research-led experiments to real statistical significance and only ship what the numbers back.
A/B testing is a discipline, not a button.
Running an A/B test is easy. Running one that gives you a trustworthy answer is not. Tests get called on a hunch, on a good week, or before they have the sample size to mean anything, and brands ship changes that quietly lose money.
We treat experimentation as the discipline it is: a research-backed hypothesis, a clean implementation, and a result measured to statistical significance against a real control, so you roll out only what genuinely won.
What you actually get
Research-led hypotheses
Analytics, session replay and heuristics find the real friction before we test, so we test what matters.
Run to significance
Z-score-aware reporting and proper sample sizes. No calling a winner on a hunch or a good week.
Clean implementation
Variants built and QA-d across devices with no flicker and no broken tracking, so the data is trustworthy.
Verified uplift
Results measured against a real control in Intelligems and GA4, reported in revenue, not vanity metrics.
How an engagement runs
Research
We map the funnel and pull the data to build a ranked backlog of test ideas worth running.
Hypothesize
Each idea becomes a hypothesis scored by impact, confidence and effort, so the biggest levers run first.
Test
We build the variant, QA it, and launch a clean split with proper traffic allocation.
Measure
When the test reaches significance you get a plain-English report: won, lost, or inconclusive.
Real tests. Real significance.
Client names withheld.
These are live A/B test results from our CRO program, measured with Intelligems. The numbers are real. The brands are agency-partner and white-label clients, so we describe them but never name them.
Sticky add-to-cart on product pages
Volume discount display on PDP
Quantity selector badge on PDP
Above-the-fold product page redesign
Product trust tags on PDP
Trust section on product pages
Every winner is measured to statistical significance in Intelligems before we count it - and before we bill on performance. Results shown are per-variant lift over control.
We work under NDA, so brand names stay masked. The numbers are from real A/B tests, and we walk you through the full reports on a discovery call.
Common questions
How much traffic do I need for ecommerce A/B testing?
As a rough floor, a few hundred conversions a month lets most tests reach significance in a reasonable window. With less, we lead with higher-impact redesign work and qualitative research first.
How long until an A/B test reaches significance?
It depends on your traffic and the size of the effect. Many tests read in two to four weeks. We do not stop a test early just because it looks good on day three.
What should I A/B test first?
Not button colors. We prioritize high-traffic, high-friction steps: product pages, cart and checkout, and offer presentation, where a win moves real revenue.
How do you know a test actually won?
We run each experiment to statistical significance against a control using z-score-aware tooling, and report the lift and the probability it beats baseline before anything ships.
What A/B testing tools do you use?
We commonly run tests through Intelligems and validate with GA4, and we build variants properly in code so there is no flicker or tracking loss.
Run A/B tests you can actually trust.
Book a 30-minute call. We will look at your funnel live and show you the first experiments worth running, and how we measure a real win.
Start testing