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A/B Testing for Landing Pages & Ads

A/B Testing for Landing Pages & Ads is our service for running structured experiments — comparing two or more versions of a page or ad to see which one actually performs better with real visitors, instead of guessing based on opinion.

A useful A/B test starts with a clear hypothesis — what you're changing and why you think it'll help — enough traffic to reach a meaningful result, and only one meaningful variable changed at a time so you can tell what actually caused the difference. We identify which pages or ads are worth testing, design variants with a real hypothesis behind them, and run the test long enough to reach statistical confidence before drawing conclusions.

Hypothesis-Driven Test Design

Every test built around a specific hypothesis and a single meaningful variable, so results are actually interpretable.

Landing Page & Ad Variant Creation

Alternate versions of pages or ad creative built to test against the original in a controlled way.

Statistical Significance Monitoring

Tests run long enough and with enough traffic to reach a meaningful result, rather than calling a winner too early.

Results Analysis & Implementation

Winning variants explained in plain language and implemented as the new default once a test concludes.

How it Works

Identify & Hypothesize

We review analytics to find pages or ads worth testing and form a specific hypothesis for what change might improve performance.

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Build & Run the Test

We build the variant, set up the test with proper traffic splitting, and let it run long enough to gather a meaningful sample.

Analyze & Implement

We analyze the results, explain what happened and why, and implement the winning version if the test reached a clear result.

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Frequently Asked Questions

No — a test's purpose is to find out what actually works, and sometimes the original version wins or the result is inconclusive. That's a legitimate outcome, not a failure.
It depends on your traffic volume — low-traffic pages need longer to reach a statistically meaningful result. We'll give you a realistic timeframe based on your numbers.
We usually recommend starting with high-traffic, high-impact pages like your main landing page or top-performing ad, where a change has the most potential effect.
It depends on how many tests and pages are involved and whether we're also building the variants. Contact us for a quote.
Access to your analytics and the pages or ads you want to test, plus a sense of your monthly traffic so we can estimate realistic test timelines.
Yes — once a test reaches a clear result, we implement the winning version as the new default, as part of the service.
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Before the First Test

Picking Tests Worth Running

Not every page or idea is worth testing — low-traffic pages rarely reach a meaningful result in a reasonable time. We prioritize tests based on traffic volume and potential impact rather than testing whatever seems interesting at the moment.

  • High-traffic, high-impact pages prioritized first
  • Low-traffic pages flagged as unlikely to reach significance
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Reading Results Honestly

When a Test Doesn't Produce a Clear Winner

An inconclusive result is a normal, legitimate outcome of testing, not a failure of the process. We resist the temptation to call a winner early on partial data just because a change is wanted, and report honestly when a test simply doesn't reach a clear answer.

  • Inconclusive results reported honestly, not dressed up as wins
  • Early data resisted until statistical confidence is reached
Our Reviews

What Clients Say

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"They told us honestly when a test came back inconclusive instead of spinning it into a win."

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Growth Marketing Lead

Client

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"Clear about how long a test would realistically need to run given our traffic, so we knew what to expect."

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E-commerce Manager

Client

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"The hypothesis behind each test was explained clearly before it even launched."

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Product Manager

Client

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