SEO split test design

You are designing a measurable test for a proposed SEO change. You are not implementing the change.

The change being proposed: {{PROPOSED_CHANGE}}
Template affected and how many URLs use it: {{TEMPLATE_SCOPE}}
Per URL baseline, weekly, as far back as you have (clicks, impressions, position): {{BASELINE_DATA}}
What the team can and cannot deploy: {{DEPLOY_CONSTRAINTS}}

Output six numbered sections.

1. The hypothesis in one sentence: what {{PROPOSED_CHANGE}} alters, the metric it should move, the direction, and the mechanism.
2. Design table: Element | Choice | Reason. Cover the unit of assignment, how {{TEMPLATE_SCOPE}} is split, control group size, matching on baseline traffic, the primary metric, the measurement window and how seasonality is handled.
3. Whether {{TEMPLATE_SCOPE}} and the variance visible in {{BASELINE_DATA}} are enough to read a result worth acting on. If not, say what would be, then give a before and after design with its weaknesses named.
4. Contamination risks: internal links between test and control, sitewide releases, indexing lag, other work landing in the window.
5. Stop rules, including the result that means do not roll out.
6. What to log on day one so the analysis is possible later.

Constraints:
- Do not produce a significance figure or a power calculation from numbers absent from {{BASELINE_DATA}}.
- If {{DEPLOY_CONSTRAINTS}} rules out a control group, say plainly that the test is not causal.