A/B Testing & Experimentation
A/B testing is a controlled experiment that shows two versions of a page, email, or flow to comparable audiences and measures which produces more of a target outcome. Run rigorously, it replaces opinion and HiPPO decisions with statistical evidence about what actually moves a metric. A mature experimentation practice goes beyond one-off tests to a continuous program — a steady stream of hypotheses, each one a small, measured bet that compounds into reliable gains over time.
Why It Matters
Experimentation is how you improve conversion without guessing and without risking the whole funnel on a redesign. Each winning test is a permanent lift on all future traffic, so the gains stack. Companies with a disciplined testing program tend to out-improve competitors who redesign on instinct, because they learn what works for their specific audience and keep what wins.
Problem It Solves
Ends the expensive habit of shipping big changes based on someone's opinion and hoping. Instead of betting the funnel on a redesign that might hurt, you test the change on a slice of traffic, measure the real effect, and roll out only what demonstrably wins — removing risk and politics from optimization.
How We Approach It
Melexsoft runs structured experimentation as part of every growth system — clear hypotheses, proper statistical thresholds, and one variable at a time so results are trustworthy. Our +38% average conversion lift after the first iteration comes from testing, not guessing. Let us build your experimentation engine.
Related Terms
Frequently Asked Questions
How much traffic do I need to run A/B tests?
- Enough to reach statistical significance in a reasonable timeframe — as a rough guide, a few hundred conversions per variation. Low-traffic sites can still experiment by testing higher up the funnel or running tests longer, and Melexsoft scopes the testing approach to your actual volume.
How long should an A/B test run?
- Until it reaches a pre-set significance threshold and covers full business cycles, usually at least one to two weeks to avoid day-of-week skew. Stopping early when a result looks good is one of the most common ways teams fool themselves with noise.
What is the difference between A/B testing and CRO?
- CRO is the broad discipline of improving conversion; A/B testing is the primary method it uses to prove which changes work. Experimentation is the rigorous engine inside a CRO program that separates real wins from lucky-looking noise.
Can I test more than one change at a time?
- You can with multivariate testing, but it needs much more traffic to isolate each effect. For most companies, clean A/B tests changing one variable at a time give faster, more trustworthy answers, which is the approach Melexsoft favors.
How does Melexsoft keep test results trustworthy?
- We set the hypothesis and significance threshold before the test, change one variable at a time, run across full business cycles, and avoid peeking-and-stopping. This discipline is why the lifts we report hold up on live traffic rather than vanishing after launch.
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The Problem
Ends the expensive habit of shipping big changes based on someone's opinion and hoping. Instead of betting the funnel on a redesign that might hurt, you test the change on a slice of traffic, measure the real effect, and roll out only what demonstrably wins — removing risk and politics from optimization.
How We Solve It
Melexsoft runs structured experimentation as part of every growth system — clear hypotheses, proper statistical thresholds, and one variable at a time so results are trustworthy. Our +38% average conversion lift after the first iteration comes from testing, not guessing. Let us build your experimentation engine.
14 days
Average time to first results
3×
Average conversion uplift
0
Long-term contracts required