A/B-Testing Agency for Online Shops

A/B-testing is the only method that tells you with certainty what works. Not opinions, not gut feeling, not “that looks better”. An A/B-testing agency that merely operates a tool delivers test results. We deliver an experimentation programme that changes your revenue — designed, prioritised and evaluated by specialists who do nothing else.

An experimentation programme, not single-test tooling

Many agencies sell A/B-testing as tooling: set up a licence, run a few tests, send a monthly report. The outcome is usually disappointing — not because the tool is bad, but because a test without a system is a lottery. No research, no good hypotheses. No prioritisation, the wrong tests first. No statistical discipline, winners that aren’t.

We run testing as a programme: a continuous loop of research, hypotheses, tests and implementation. The question is never “Can we test that?” but “Which test delivers the biggest provable revenue now?” The first test goes live 3–5 working days after onboarding.

What we test

We test where revenue is created or lost — platform-neutral, from checkout to category page:

Checkout

The most sensitive part of every shop: guest checkout vs. customer account, number of steps, payment method order, trust signals, mobile input friction. A checkout test is often the test with the highest direct revenue impact.

Product page (PDP)

Images, price presentation, CTA text and position, social proof, delivery information. The product page decides whether a visitor clicks into the cart — we test it against real users instead of internal opinions.

Category and listing pages

Filters, sorting, product density, image sizes, quick view. Category pages are the most underestimated test area — here it is decided whether visitors reach a product page at all.

Pricing and payment

Price presentation, tiers, payment method order, fee transparency. The most delicate testing area — and therefore the one that benefits most from clean methodology.

Methodology: hypotheses, duration, statistics

Every test follows the same logic: hypothesis instead of assumption (“We observe X, we suspect Y, we measure Z”), isolated variables instead of full redesigns, and statistical significance as the only stopping criterion. No test is stopped early because a variant “looks good”.

Test duration is not a gut call: it depends on traffic, conversion rate and expected effect size. Our A/B-test duration calculator shows you before the start how long your test realistically needs to run. The methodological foundation is covered in our A/B-testing hub — from statistics to the most common testing errors.

Proof: testing as a system

Instead of promising numbers, we point to documented cases — anonymised, but complete in structure:

• Testing system for a gift shop — our reference case for building a running experimentation programme instead of scattered single tests.
• Mobile checkout optimisation — how targeted tests on the mobile checkout remove the biggest conversion hurdle.
• CRO system for a natural products shop — hypotheses, prioritisation and clean evaluation working together.

Costs and model

A/B-testing as a service scales with your result, not with our time: 0 € setup, 10% of the provable revenue increase. You only pay for tested, proven improvements — never for test runs, activity or reports without impact. How to compare providers in general and what testing should cost is covered in our comparison of CRO agencies and their costs.

The testing programme is embedded in our overall model — the A/B-tests deliver the proof, the system makes sure the winners actually get implemented.

How we start

• Book a call — we check in a direct conversation whether your traffic supports a statistically sound testing programme.
• A/B-test duration calculator — see upfront which test durations are realistic in your shop.
• Shop audit — we show you the three test levers with the highest expected impact before you commission anything.

Common questions about an A/B-testing agency

Do I need an agency for A/B-testing, or is a tool enough?

A tool is enough to run tests. It is not enough to test the right things. The quality of a testing programme is decided before the tool: at the research question, the hypothesis quality and the prioritisation. That is exactly where an agency works — tooling is the easy part.

Which A/B-testing tools do you use?

We test platform-neutrally with our own testing stack, grown over thousands of tests. If needed, we continue with your existing tool — methodology matters more than licences.

How long does an A/B-test run?

As long as statistics requires — at least one full business-cycle week, typically 2–4 weeks. The exact duration depends on your traffic and baseline conversion; the duration calculator gives you the number before the start.

What happens to losing tests?

They are evaluated and archived. A losing test is not a failure — it proves what does NOT work and sharpens the next hypothesis. You only ever pay for provable revenue increase, never for testing activity.

How much traffic do I need for A/B-testing?

As a rule of thumb: from roughly 1,000 visitors per week with clearly measurable conversions. Below that, runtimes stretch beyond what is reasonable — research and a structured before/after measurement are the better route then. The first call will tell you honestly where you stand.