Use this workflow to generate clear, testable conversion hypotheses for one page, funnel step, or campaign journey.

### Required Input
- Page or Funnel Step: [Describe the specific asset or step. Example: pricing page, webinar signup page, checkout step, demo request form]
- Conversion Goal: [State the desired action. Example: increase demo bookings, raise trial starts, reduce checkout abandonment]
- Target Audience: [Describe the audience segment. Example: HR leaders at companies with 50-300 employees]
- Current Performance Data: [Share available metrics. Example: 4.8% CTA click rate, 1.2% form completion rate, 52% scroll depth]
- Visitor Behaviour Observations: [Describe what users appear to do. Example: many visitors click pricing FAQ but few start checkout]
- Traffic Source or Segment: [Describe source. Example: paid search for competitor terms, email nurture traffic, organic product comparisons]
- Offer or Message: [Summarise the main offer. Example: free consultation for payroll compliance review]
- Constraints: [List limits. Example: cannot change price, limited developer time, must keep approved compliance wording]

### Input Validation
Review all required inputs before generating hypotheses. If any required information is missing, unclear, or too broad, ask specific clarification questions and pause. Do not continue until the inputs are complete enough to create useful hypotheses.

### Instructions
Create hypotheses that connect a specific observed problem to a likely visitor belief, concern, or motivation. Do not create generic ideas such as "improve the CTA" unless the hypothesis explains why the change should affect behaviour.

For each hypothesis:
- Tie it to the provided data or observation
- State the suspected conversion barrier
- Explain the expected behavioural change
- Suggest a realistic test or change
- Identify the metric that would validate or reject it

Keep the recommendations suitable for a small team without paid research tools.

### Output
Return the hypotheses in this structure:
1. Situation Summary
- Summarise the conversion goal, audience, and strongest signal from the data

2. Hypothesis List
Create a table with these columns:
- Hypothesis
- Supporting Signal
- Visitor Concern or Motivation
- Proposed Change
- Primary Metric
- Confidence: High, Medium, or Low
- Effort: Low, Medium, or High

3. Strongest 3 Hypotheses
Rank the top 3 hypotheses and explain why each deserves priority.

4. Test Design Notes
For each top hypothesis, provide:
- Test version or implementation idea
- Control version
- Success metric
- Minimum observation period recommendation

5. Risks and Watchouts
List possible misreads, data gaps, or side effects.

6. Next Actions
Provide a short ordered list of what to do next.