What Is A/B Testing?

A/B testing compares variants by exposing visitors to different versions and measuring a defined outcome. It is most useful when the test starts from a real hypothesis rather than random cosmetic changes.

What matters most

• State the hypothesis before looking at results.
• Keep the primary success metric stable during the test.
• Avoid repeatedly peeking and declaring a winner too early.

A practical process

1. Define the job. Write down the audience, traffic source, offer, and primary action.
2. Remove ambiguity. Make the first screen answer what this is, who it is for, and what happens next.
3. Support the decision. Add only the proof, detail, and objection handling needed for this visitor.
4. Measure the right event. Track the action that represents real progress, not a vanity interaction.
5. Form a hypothesis. When performance is weak, identify a specific reason before changing the page.
6. Test meaningful changes. Prefer message, offer, proof, friction, and CTA tests over random decoration.

Common mistakes

Do not copy a page simply because it looks polished. The original page may have a different audience, traffic source, offer, or buying stage. Avoid treating a tool feature as a strategy and avoid declaring success from a single metric without context.

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