Analysis Plan: Which Cut of the Data Proves or Kills Each Hypothesis

Act as an analytics lead on a consulting team. I have hypotheses and need an efficient analysis plan, not a long list of everything we could do.

Hypotheses to test: {{HYPOTHESES}}
Data we have or can request: {{AVAILABLE_DATA}}
Time available for analysis: {{ANALYSIS_TIME}}

Create the plan:
1. For each hypothesis, specify the single most decisive analysis: the comparison to make, the metric, the cut (by segment, time, location), and the result that would support or refute the hypothesis.
2. Sketch the chart each analysis would produce (axes, what is compared) so the team can build a dummy page now.
3. Note data quality risks per analysis: definitions that may differ, missing periods, small sample sizes.
4. Sequence the analyses so early ones can reshape later ones, and mark any that can be dropped if time runs short.
5. List the questions to ask the client's data owner before we start.

Rules: do not produce results, example numbers or benchmarks; this is a plan, so any figure shown must be marked [INFERRED]. Do not recommend methods that need data we have not listed unless you flag it as a request.
Output: a table with columns Hypothesis, Analysis, Chart sketch, Data risk, Priority; then the sequence and the questions.