Turned vague 'why is churn rising' into three answerable questions with methods that fit my budget and timeline

You are a research methodology professor at a top university. Help me transform a broad topic into rigorous, answerable research questions with appropriate methods.\n\nBROAD TOPIC/AREA OF INTEREST: {{broad_topic}}\nPRACTICAL CONTEXT: {{why_this_matters — e.g., 'We need to decide whether to enter X market', 'Our churn rate is rising and we don't know why', 'We want to validate our pricing strategy'}}\nCONSTRAINTS: {{constraints — e.g., '$10K budget', '2-month timeline', 'No access to customer data', 'Small team'}}\nINTENDED AUDIENCE: {{who_will_use_the_findings}}\n\nOUTPUT — Research Question Architecture:\n\n## 1. TOPIC DECOMPOSITION\nBreak {{broad_topic}} into 3-5 sub-domains or dimensions:\n\n**Dimension 1: [Name]**\n- What we know: [Summary of existing knowledge]\n- What we don't know: [Key gaps]\n- Why it matters: [Connection to decision/context]\n\n(Same for each dimension)\n\n## 2. RESEARCH QUESTION HIERARCHY\nBuild a question tree from overarching to specific:\n\n**Overarching Question (OQ)**: The single most important question to answer\n\n**Sub-Questions (SQ)** derived from OQ:\n- SQ1: [Specific, answerable question] → connects to decision about [X]\n- SQ2: [Specific, answerable question] → connects to decision about [Y]\n- SQ3: [Specific, answerable question] → connects to decision about [Z]\n\n**Investigative Questions (IQ)** for each sub-question:\n- SQ1 → IQ1.1: [Measurable/observable question]\n- SQ1 → IQ1.2: [Measurable/observable question]\n- SQ1 → IQ1.3: [Measurable/observable question]\n\n**SMART Check for each question**:\n| Question | Specific | Measurable | Achievable | Relevant | Time-bound | Pass? |\n|----------|----------|------------|------------|----------|------------|-------|\n\n## 3. METHODOLOGY MATCHING\nFor each sub-question, recommend the best research method:\n\n| Sub-Question | Primary Method | Secondary Method | Sample Needed | Timeline | Cost Estimate | Data Source |\n|--------------|---------------|------------------|---------------|----------|---------------|-------------|\n\nMethod options include:\n- Quantitative: Survey, Experiment, A/B test, Analytics mining, Correlational study\n- Qualitative: In-depth interview, Focus group, Ethnography, Case study, Delphi\n- Mixed methods: Sequential explanatory, Concurrent triangulation\n- Secondary: Literature review, Meta-analysis, Benchmarking\n\nJustify each method choice based on the question type (exploratory, descriptive, explanatory, predictive).\n\n## 4. FEASIBILITY ASSESSMENT\n\n| Sub-Question | Budget Fit | Timeline Fit | Resource Fit | Access Fit | Risk of Failure | Go/No-Go |\n|--------------|-----------|-------------|-------------|-----------|----------------|----------|\n\n## 5. HYPOTHESIS DEVELOPMENT\nFor confirmatory questions, develop testable hypotheses:\n\n**H1**: [Directional hypothesis with variables clearly defined]\n- Independent variable: [ ]\n- Dependent variable: [ ]\n- Expected relationship: [ ]\n- Statistical test: [ ]\n\n**H2**: [Alternative hypothesis]\n(Same structure)\n\n## 6. RESEARCH DESIGN SYNOPSIS\n- Overall design type: [Exploratory / Descriptive / Causal / Predictive]\n- Sampling strategy: [Probability / Non-probability — specific type]\n- Data collection instruments needed\n- Analysis plan overview\n- Validity threats and how to address them (internal, external, construct, statistical conclusion)\n\n## 7. ETHICAL CONSIDERATIONS\n- Human subjects considerations (if applicable)\n- Data privacy requirements\n- Conflicts of interest to manage\n- IRB/ethics review requirements (if academic)\n\n## 8. DELIVERABLE SPECIFICATION\n- What the final output will look like\n- Format: [Report / Presentation / Dashboard / White paper]\n- Key sections/contents\n- Quality criteria: What makes this research 'good'?