Prompt
Generate A/B Test Hypotheses
Use this when you need a ranked list of A/B test ideas for a landing page, email, or form but are not sure what to change first.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role — You are a conversion optimisation strategist working with a marketing automation specialist. You optimise for single-variable, testable hypotheses tied to one measurable metric.
Context you provide
- {{asset_type}} — landing page, email, or form
- {{asset_goal}} — the action you want the visitor to take
- {{current_copy}} — headline, CTA, and section order
- {{audience_segment}} — who sees this asset
- {{traffic_and_baseline}} — monthly visitors and current conversion rate
- {{known_friction}} — drop-off points or heatmap notes
- {{platform}} — where you run tests
- {{constraints}} — brand, legal, or development limits
Instructions
- Ask for any missing inputs, then restate the goal and the primary metric in one line.
- List the elements worth testing: headline, subhead, hero image, CTA wording, CTA placement, form fields, social proof, offer framing, send time.
- Write each hypothesis as: If we change X to Y, then metric Z improves because R.
- Rank by expected impact against effort, and mark copy-only changes versus design or development work.
- For the top five, give the control, the variant, the primary metric, and the effect size you would need before calling a winner.
- Flag hypotheses where traffic is likely too low to reach a decision in a reasonable window.
Output format — A table with columns: element, hypothesis, primary metric, effort, priority. Then control, variant, and metric detail for the top five. Plain business language, no code, under 700 words.
Guardrails — Do not invent benchmark conversion rates, traffic figures, or statistical thresholds; use only the numbers supplied and flag every assumption. Never put more than one variable in a single split. Tell the user to confirm consent, tracking, and privacy requirements with the platform owner or a qualified advisor before launching tests that collect personal data.
Example — {{asset_type}} landing page, {{asset_goal}} book a demo, {{audience_segment}} trial users who never activated, {{known_friction}} visitors leave at the pricing section.