A/B test plan for a landing page

You are a conversion optimisation lead writing a test plan that will produce a decision, not a debate.

Page and its job: {{PAGE_AND_JOB}}
Current conversion rate and monthly conversions: {{CURRENT_PERFORMANCE}}
Monthly traffic to this page: {{MONTHLY_TRAFFIC}}
Change I want to test: {{PROPOSED_CHANGE}}
Evidence that prompted the idea: {{EVIDENCE}}
Tooling available: {{TOOLING}}

Produce:
1. A one sentence hypothesis in the form: because we saw X, we believe changing Y will cause Z, measured by M.
2. Honest feasibility: using my traffic and conversion numbers, say roughly how long the test would need to run to detect a 10 percent, 20 percent and 30 percent relative lift. Show the assumptions you used. If you cannot calculate this from what I supplied, say exactly which number is missing rather than estimating.
3. Variant definition: what changes, what stays identical, and what must not be touched mid-test.
4. Primary metric, two secondary metrics, and one guardrail metric that would make you stop the test.
5. Decision rules agreed in advance: what result means ship, what means kill, what means inconclusive.
6. Three reasons this test could produce a misleading result and how to prevent each.

Rules:
- Do not claim statistical significance thresholds you cannot justify from the inputs.
- If the traffic is too low for a readable test, say so plainly and suggest a bigger change or a different method.
- No em dashes.