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skills/discovery-interviews-surveys/resources/evaluators/rubric_discovery_interviews_surveys.json

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+{
+  "criteria": [
+    {
+      "name": "Research Objective Clarity",
+      "description": "Is the research objective clearly defined with specific learning goals and hypotheses?",
+      "scoring": {
+        "1": "Vague objective ('learn about users'). No specific learning goals. Hypotheses missing. No connection to decision.",
+        "3": "Objective stated but could be more specific. Some learning goals identified. Hypotheses present but may lack precision. Decision somewhat clear.",
+        "5": "Crystal clear objective with specific learning goals. Testable hypotheses documented. Clear connection to decision to be informed. Success criteria defined."
+      }
+    },
+    {
+      "name": "Participant Targeting & Recruitment",
+      "description": "Are target participants well-defined with appropriate screening and recruitment strategy?",
+      "scoring": {
+        "1": "Participant criteria vague or missing. No screening questions. Recruitment strategy not specified. Sample size not justified.",
+        "3": "Participant criteria identified but may lack specificity. Basic screening questions. Recruitment strategy mentioned. Sample size roughly appropriate.",
+        "5": "Precise participant criteria (demographics, behaviors, firmographics). Comprehensive screening questions. Clear recruitment strategy with channels. Sample size justified by method (5-15 for qual, 100+ for quant, 30+ per segment)."
+      }
+    },
+    {
+      "name": "Question Quality & Bias Avoidance",
+      "description": "Are questions well-designed, open-ended, behavior-focused, and free of leading bias?",
+      "scoring": {
+        "1": "Many leading or hypothetical questions ('Would you...?', 'Don't you think...?'). Closed yes/no questions dominate. No behavior focus. Confirmation bias obvious.",
+        "3": "Mix of open and closed questions. Some behavior focus but also hypotheticals. Minor leading language. Some bias-avoidance techniques attempted.",
+        "5": "Exemplary questions: open-ended, behavior-focused ('Tell me about the last time...'), use 'show me' requests, avoid hypotheticals, no leading language. Systematic bias-avoidance techniques applied throughout."
+      }
+    },
+    {
+      "name": "Interview Guide / Survey Structure",
+      "description": "Is the research instrument well-structured with logical flow and appropriate depth?",
+      "scoring": {
+        "1": "Poor structure. No logical flow. Too shallow (only surface questions) or too narrow (missing key areas). Inappropriate question types.",
+        "3": "Decent structure with some flow. Covers main topics but may miss areas. Question types mostly appropriate. Could use refinement.",
+        "5": "Excellent structure: warm-up, core questions, concept test (if applicable), wrap-up. Logical flow from general to specific. Appropriate depth and breadth. Question types match objectives (open-ended for discovery, scaled for validation). Includes follow-up probes."
+      }
+    },
+    {
+      "name": "JTBD / Problem Discovery Focus",
+      "description": "For discovery research, does it focus on jobs-to-be-done, problems, and context (not just features)?",
+      "scoring": {
+        "1": "Feature-focused ('Do you want feature X?'). No JTBD exploration. Missing context about problems, workflows, or triggers. Hypothetical focus.",
+        "3": "Some problem exploration. Brief JTBD elements. Context partially explored. Mix of problem and feature questions.",
+        "5": "Deep JTBD focus: hiring/firing triggers, desired outcomes, current workarounds, pain points, context. Timeline reconstruction for switchers. Problems before solutions. 'Show me' requests for workflows."
+      }
+    },
+    {
+      "name": "Sample Size & Statistical Rigor",
+      "description": "Is sample size appropriate for method and are statistical considerations addressed for surveys?",
+      "scoring": {
+        "1": "Sample size inappropriate (e.g., 3 interviews claiming statistical significance, or 20-person survey). No power analysis. No consideration of statistical validity for quantitative claims.",
+        "3": "Sample size roughly appropriate but not justified. Some statistical awareness for surveys (e.g., descriptive stats). May lack power analysis or significance testing.",
+        "5": "Sample size justified: 5-15 for qualitative themes, 100+ for survey stats, 30+ per segment for comparisons. Power analysis for surveys (margin of error, confidence level). Statistical tests specified (t-test, chi-square, etc.). Saturation check for interviews."
+      }
+    },
+    {
+      "name": "Analysis Plan & Rigor",
+      "description": "Is there a clear, systematic analysis plan with rigor techniques?",
+      "scoring": {
+        "1": "No analysis plan. Unclear how data will be processed. No mention of systematic approach, coding, or statistical tests. Risk of cherry-picking.",
+        "3": "Basic analysis plan. For interviews: thematic coding mentioned. For surveys: descriptive stats mentioned. Some structure but may lack rigor techniques.",
+        "5": "Comprehensive analysis plan. For interviews: systematic thematic coding, affinity mapping, frequency counting, saturation check, negative case analysis. For surveys: descriptive stats, inferential tests, segmentation, open-end coding. Pre-specified to avoid p-hacking."
+      }
+    },
+    {
+      "name": "Facilitation & Execution Guidance",
+      "description": "For interviews, is there guidance on facilitation techniques (active listening, probes, silence)?",
+      "scoring": {
+        "1": "No facilitation guidance. Script-only approach with no flexibility. Missing techniques like probing, silence, active listening.",
+        "3": "Some facilitation guidance. Probes included for some questions. Brief mention of techniques. Could be more comprehensive.",
+        "5": "Detailed facilitation guidance: active listening, follow-up probes ('Tell me more', 'Why did that matter?'), embrace silence (3-5 sec pause), mirroring, 'show me' requests, non-verbal cue awareness. Recording and note-taking protocol."
+      }
+    },
+    {
+      "name": "Ethics & Consent",
+      "description": "Are ethical considerations addressed (informed consent, privacy, compensation)?",
+      "scoring": {
+        "1": "No mention of consent, privacy, or compensation. Ethical considerations ignored.",
+        "3": "Brief mention of consent or compensation. Some privacy awareness. May lack detail on implementation.",
+        "5": "Comprehensive ethics: informed consent script, explicit recording permission, anonymization in reports, secure data storage, fair compensation specified, opt-out option. Privacy-first approach."
+      }
+    },
+    {
+      "name": "Insights Documentation & Actionability",
+      "description": "Is there a clear template or plan for documenting insights with evidence and recommendations?",
+      "scoring": {
+        "1": "No insights documentation plan. Unclear how findings will be communicated. Missing connection to actionable recommendations.",
+        "3": "Basic insights template. Some structure for documenting findings. Recommendations mentioned but may lack specificity. Somewhat actionable.",
+        "5": "Comprehensive insights document template: executive summary, methodology, key findings with evidence (quotes/stats), surprises, recommendations (specific actions), confidence level, limitations. Actionable and decision-ready."
+      }
+    }
+  ],
+  "minimum_score": 3.5,
+  "guidance_by_research_type": {
+    "Problem Discovery Interviews": {
+      "target_score": 4.0,
+      "focus_criteria": [
+        "Question Quality & Bias Avoidance",
+        "JTBD / Problem Discovery Focus",
+        "Facilitation & Execution Guidance"
+      ],
+      "sample_size": "8-15 participants",
+      "key_requirements": [
+        "Open-ended, behavior-focused questions",
+        "Focus on past behavior, not hypotheticals",
+        "'Show me' requests for workflows",
+        "Problem before solution",
+        "Current workarounds explored",
+        "Systematic thematic coding planned"
+      ],
+      "common_pitfalls": [
+        "Asking 'Would you use...' instead of 'Tell me about the last time you...'",
+        "Jumping to solutions before understanding problems",
+        "Not probing deeply enough (stopping at surface answers)",
+        "Selection bias (only interviewing enthusiasts)"
+      ]
+    },
+    "Jobs-to-be-Done Research": {
+      "target_score": 4.2,
+      "focus_criteria": [
+        "JTBD / Problem Discovery Focus",
+        "Question Quality & Bias Avoidance",
+        "Interview Guide / Survey Structure"
+      ],
+      "sample_size": "10-15 recent switchers",
+      "key_requirements": [
+        "Recruit recent switchers (last 3-6 months)",
+        "Timeline reconstruction (first thought → current state)",
+        "Forces of progress (push, pull, anxiety, habit)",
+        "Hiring/firing triggers identified",
+        "Desired outcomes vs current capabilities",
+        "Context and constraints explored"
+      ],
+      "common_pitfalls": [
+        "Interviewing people who switched too long ago (memory fades)",
+        "Not reconstructing timeline (missing trigger events)",
+        "Ignoring anxieties and habits (forces resisting change)",
+        "Focusing only on product features, not job to be done"
+      ]
+    },
+    "Concept Testing (Qualitative)": {
+      "target_score": 3.8,
+      "focus_criteria": [
+        "Question Quality & Bias Avoidance",
+        "Interview Guide / Survey Structure",
+        "Participant Targeting & Recruitment"
+      ],
+      "sample_size": "10-15 target users",
+      "key_requirements": [
+        "Comprehension check ('In your own words, what is this?')",
+        "Target audience validation ('Who is this for?')",
+        "Use case exploration ('When would you use it?')",
+        "Value perception (pricing anchors, comparisons)",
+        "Concerns and objections surfaced",
+        "Avoid leading ('Don't you think this is great?')"
+      ],
+      "common_pitfalls": [
+        "Testing with wrong audience (not actual target users)",
+        "Leading participants to 'correct' answer",
+        "Not exploring concerns (only positive feedback)",
+        "Mistaking 'sounds interesting' for 'will actually use'"
+      ]
+    },
+    "Quantitative Surveys": {
+      "target_score": 4.1,
+      "focus_criteria": [
+        "Sample Size & Statistical Rigor",
+        "Question Quality & Bias Avoidance",
+        "Analysis Plan & Rigor"
+      ],
+      "sample_size": "100+ overall, 30+ per segment",
+      "key_requirements": [
+        "Sample size justified (power analysis, margin of error)",
+        "Mix of scaled questions and open-ends",
+        "Avoid leading language in questions",
+        "Randomize option order",
+        "Pilot test with 5-10 people",
+        "Statistical tests pre-specified (t-test, chi-square, etc.)",
+        "Segmentation plan for subgroup analysis"
+      ],
+      "common_pitfalls": [
+        "Too small sample for statistical claims (n < 30 per segment)",
+        "Leading questions ('How much do you love our product?')",
+        "No pilot test (discovering issues after launch)",
+        "Cherry-picking significant results (p-hacking)",
+        "Ignoring non-response bias"
+      ]
+    },
+    "Continuous Discovery": {
+      "target_score": 3.7,
+      "focus_criteria": [
+        "Interview Guide / Survey Structure",
+        "Facilitation & Execution Guidance",
+        "Insights Documentation & Actionability"
+      ],
+      "sample_size": "3-5 conversations per week",
+      "key_requirements": [
+        "Lightweight process (15-30 min conversations)",
+        "Rotating team members (product, eng, design)",
+        "Shared notes repository",
+        "Flexible guide based on current focus",
+        "Monthly synthesis of patterns",
+        "Relationship building with customers"
+      ],
+      "common_pitfalls": [
+        "Making it too formal (blocks adoption)",
+        "Only product team participates (team stays disconnected)",
+        "No shared documentation (insights lost)",
+        "No periodic synthesis (patterns missed)",
+        "Stopping after a few weeks (not continuous)"
+      ]
+    }
+  },
+  "common_failure_modes": [
+    {
+      "failure": "Hypothetical questions ('Would you...?')",
+      "symptom": "Questions like 'Would you pay $X?', 'Would you use feature Y?', 'If we built Z, would you switch?'. Participants describe future intent, not past behavior.",
+      "detection": "Look for 'would', 'if', 'imagine'. Check if questions focus on actual past behavior vs hypothetical scenarios.",
+      "fix": "Reframe to past behavior: 'Tell me about the last time you [needed this]', 'What have you tried?', 'Show me your current workflow'. Use 'have you' not 'would you'."
+    },
+    {
+      "failure": "Leading questions (telegraphing desired answer)",
+      "symptom": "Questions like 'Don't you think...?', 'Isn't it true that...?', 'How much do you love...?'. Bias obvious.",
+      "detection": "Check if question suggests 'right' answer. Would neutral observer detect researcher's opinion from question?",
+      "fix": "Use neutral phrasing: 'What's your experience with...?', 'Walk me through...'. Let participant form own opinion, don't guide."
+    },
+    {
+      "failure": "Insufficient sample size for claims",
+      "symptom": "Statistical claims from tiny samples ('80% of users want X' from 5 interviews). Surveys with n < 30 per segment claiming significance.",
+      "detection": "Check sample size vs type of claim. Interviews → themes only. Surveys → need n ≥ 30 per segment for stats.",
+      "fix": "For interviews: Report themes ('8/12 mentioned Y'), not percentages. For surveys: Ensure n ≥ 100 overall, 30+ per segment. Run power analysis."
+    },
+    {
+      "failure": "Wrong participants (selection bias)",
+      "symptom": "Interviewing only enthusiasts, or only detractors. Convenience sample (co-workers, friends). Not screening for target criteria.",
+      "detection": "Check recruitment strategy. Are criteria specific? Is sample diverse? Any obvious biases?",
+      "fix": "Define precise inclusion/exclusion criteria. Screen with survey. Recruit diverse sample (enthusiasts AND detractors, various demographics). Avoid convenience sampling."
+    },
+    {
+      "failure": "No systematic analysis (cherry-picking)",
+      "symptom": "No coding or analysis plan. Quotes selected to support pre-existing belief. Contradictory evidence ignored or dismissed.",
+      "detection": "Check for analysis plan. Is there systematic coding? Are contradictory findings presented? Does report feel one-sided?",
+      "fix": "Pre-specify analysis approach: thematic coding, affinity mapping, frequency counting. Actively look for disconfirming evidence. Present contradictions. Use inter-rater reliability."
+    },
+    {
+      "failure": "Surface-level probing (stopping too early)",
+      "symptom": "Accepting first answer without follow-up. Not asking 'Why did that matter?', 'Tell me more', 'What else?'. Missing deeper motivations.",
+      "detection": "Check interview guide for follow-up probes. Are there '5 whys' style follow-ups? Does guide encourage depth?",
+      "fix": "Add systematic probes: 'Tell me more', 'Why did that matter?', 'What else?', 'Walk me through what happened next'. Train interviewers to dig deeper."
+    },
+    {
+      "failure": "Feature-focused (not problem-focused)",
+      "symptom": "Questions about features ('Do you want dark mode?') instead of problems ('Tell me about when poor visibility is an issue'). Solutions before problems.",
+      "detection": "Count feature mentions vs problem mentions. Are questions about 'what we could build' or 'what problems you face'?",
+      "fix": "Reframe to problems: 'What challenges do you face with...?', 'When does [current solution] break down?', 'What workarounds have you tried?'. Problems first, solutions later."
+    },
+    {
+      "failure": "No ethics/consent",
+      "symptom": "Recording without permission. No informed consent. PII not anonymized. No compensation. Participants feel exploited.",
+      "detection": "Check for consent script, recording permission, anonymization plan, compensation details.",
+      "fix": "Add consent script. Explicitly ask to record. Anonymize in reports (P1, P2). Offer fair compensation ($50-150 for 60 min). Respect opt-outs."
+    }
+  ]
+}

skills/discovery-interviews-surveys/resources/methodology.md

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+# Discovery Interviews & Surveys - Advanced Methodology
+
+## 1. Jobs-to-be-Done (JTBD) Switch Interviews
+
+**When to use**: Understanding why users switch products, identifying hiring/firing triggers.
+
+**Process**:
+1. Recruit recent switchers (adopted product in last 3-6 months—memory is fresh)
+2. Reconstruct timeline from first thought to current state (forces of progress)
+3. Identify push (problems with old solution), pull (attraction to new), anxiety (concerns about new), habit (inertia keeping old)
+
+**Forces of progress framework**:
+- **Push**: What problems pushed you away from old solution?
+- **Pull**: What attracted you to new solution?
+- **Anxiety**: What concerns almost stopped you?
+- **Habit**: What kept you using old solution despite problems?
+
+**Key questions**:
+- "When did you first realize [old solution] wasn't working?" (First thought—passive)
+- "What event made you start actively looking?" (Trigger—active)
+- "What did you consider? How did you evaluate?" (Consideration)
+- "What almost made you not switch?" (Anxiety)
+- "What was the deciding factor?" (Decision moment)
+
+**Output**: Hiring triggers, firing triggers, evaluation criteria, anxieties, decision drivers.
+
+---
+
+## 2. Kano Analysis (Feature Prioritization)
+
+**When to use**: Deciding which features to build based on satisfaction impact.
+
+**Categories**:
+- **Must-have** (basic): Dissatisfaction if absent, no extra satisfaction if present
+- **Performance** (linear): More is better—satisfaction increases linearly
+- **Delight** (exciter): Big satisfaction if present, no dissatisfaction if absent
+- **Indifferent**: No impact either way
+- **Reverse**: Some users want it, others don't
+
+**Survey approach**:
+For each feature, ask 2 questions:
+1. "How would you feel if [feature] WAS present?" (Functional)
+   - I like it / I expect it / I'm neutral / I can tolerate it / I dislike it
+2. "How would you feel if [feature] WAS NOT present?" (Dysfunctional)
+   - I like it / I expect it / I'm neutral / I can tolerate it / I dislike it
+
+**Classification matrix**: Cross-reference functional vs dysfunctional responses to categorize feature.
+
+**Prioritization**:
+1. Must-haves first (absence causes dissatisfaction)
+2. Performance features second (linear satisfaction gain)
+3. Delighters third (differentiation, but not required)
+
+---
+
+## 3. Thematic Coding for Interview Analysis
+
+**Process**:
+1. **Familiarization**: Read all transcripts once without coding
+2. **Open coding**: Highlight interesting quotes, note initial themes (bottom-up)
+3. **Axial coding**: Group codes into broader themes
+4. **Selective coding**: Identify core themes, relationships between themes
+5. **Frequency counting**: How many participants mentioned each theme?
+6. **Saturation check**: Did new interviews reveal new themes, or just confirm existing?
+
+**Rigor techniques**:
+- **Inter-rater reliability**: Two coders independently code subset, compare agreement
+- **Negative case analysis**: Actively look for quotes that contradict main themes
+- **Thick description**: Provide rich context, not just quotes
+- **Audit trail**: Document coding decisions
+
+**Software tools**: NVivo, Atlas.ti, or spreadsheet with color-coding.
+
+---
+
+## 4. Statistical Analysis for Surveys
+
+**Descriptive statistics**:
+- **Central tendency**: Mean, median, mode
+- **Spread**: Standard deviation, range, interquartile range
+- **Distribution**: Histogram, check for normality
+
+**Inferential statistics**:
+- **t-test**: Compare means between two groups (e.g., users vs non-users)
+- **ANOVA**: Compare means across 3+ groups
+- **Chi-square**: Test association between categorical variables
+- **Correlation**: Relationship between two continuous variables (Pearson's r)
+
+**Sample size requirements**:
+- **Minimum for statistical power**: n ≥ 30 per segment
+- **Margin of error**: ±5% at 95% confidence requires n ≈ 400 (for population > 10K)
+- **For small populations**: Use finite population correction
+
+**Segmentation**:
+- Divide sample by demographics, behavior, or attitudes
+- Compare segments on key metrics (e.g., satisfaction, willingness to pay)
+- Ensure each segment has n ≥ 30 for valid comparisons
+
+---
+
+## 5. Bias Mitigation Techniques
+
+**Common biases**:
+- **Confirmation bias**: Seeking evidence that confirms pre-existing beliefs
+- **Leading questions**: Telegraphing desired answer
+- **Social desirability bias**: Participants say what they think you want to hear
+- **Selection bias**: Non-representative sample
+- **Recency bias**: Overweighting recent experiences
+- **Hindsight bias**: Rewriting history post-hoc
+
+**Mitigation strategies**:
+1. **Avoid leading questions**: Bad: "Don't you think our UI is confusing?" Good: "Walk me through using this feature."
+2. **Focus on behavior, not attitudes**: Bad: "Do you value security?" Good: "Tell me about the last time security mattered in your decision."
+3. **Use concrete examples**: Bad: "How important is speed?" Good: "Show me your current workflow. Where do you wait?"
+4. **Recruit diverse sample**: Include detractors, not just enthusiasts. Screen for demographics and behaviors.
+5. **Blind analysis**: Analyze data without knowing which participant is which (if possible).
+6. **Pre-register hypotheses**: Document what you expect to find before data collection.
+
+---
+
+## 6. Participant Recruitment Strategies
+
+**Approaches**:
+
+**For existing users**:
+- **In-app invite**: Email or in-app message to random sample
+- **Behavior-triggered**: Invite after specific action (e.g., canceled subscription, completed onboarding)
+- **Support tickets**: Recruit from users who contacted support
+- **Incentive**: Gift card, product credits, donation to charity
+
+**For non-users/prospects**:
+- **User testing platforms**: UserTesting, Respondent, User Interviews
+- **Social media**: LinkedIn, Twitter, Facebook groups
+- **Snowball sampling**: Ask interviewees to refer others
+- **Panel providers**: Qualtrics, Prolific (for surveys)
+- **Community forums**: Reddit, Slack communities, Discord
+
+**Screening**:
+- Use short survey (3-5 questions) to qualify
+- Check for disqualifiers (competitors, never used category, outside target)
+- Over-recruit by 20-30% to account for no-shows
+
+**Sample size guidance**:
+- **Qualitative interviews**: 5-15 (themes emerge by interview 5-8, saturation by 12-15)
+- **Quantitative surveys**: 100+ for basic stats, 400+ for ±5% margin of error, 30+ per segment for comparisons
+
+---
+
+## 7. Interview Facilitation Best Practices
+
+**Before interview**:
+- Review objectives and guide
+- Set up recording (with participant permission)
+- Prepare backup note-taking system
+- Join 5 min early to check tech
+
+**During interview**:
+- **Active listening**: Focus on what they say, not your next question
+- **Follow the energy**: If they get excited or frustrated, dig deeper
+- **Embrace silence**: Pause 3-5 seconds after asking. Let them think.
+- **Use mirroring**: Repeat last few words to encourage elaboration
+- **Ask "why" sparingly**: Can sound accusatory. Use "What prompted..." "What mattered..."
+- **Probe with "tell me more"**: When they hint at something interesting
+- **Show don't tell**: Ask to screen-share, demonstrate, show artifacts (spreadsheets, tools)
+- **Watch non-verbal**: Hesitation, confusion, workarounds reveal truth
+
+**After interview**:
+- Debrief: Write 3-5 key takeaways immediately
+- Save recording and transcript
+- Thank participant, send compensation
+- Update sampling tracker (did they fit profile? Any biases?)
+
+---
+
+## 8. Survey Design Best Practices
+
+**Question types**:
+- **Likert scale** (1-5 agreement): "I am satisfied with [product]"
+- **Semantic differential** (bipolar): Fast [1-7] Slow
+- **Multiple choice** (single select): "Which do you prefer?"
+- **Checkbox** (multi-select): "Which of these have you used?"
+- **Ranking**: "Rank these features 1-5"
+- **Open-ended**: "What is the biggest challenge you face?"
+- **Matrix**: Rows = items, columns = rating scale
+
+**Order effects**:
+- Start with engaging, easy questions (not demographics)
+- Group related questions
+- Randomize option order (except ordered scales)
+- Put demographics at end
+- Avoid fatigue: Keep surveys < 10 min (15-20 questions)
+
+**Response scales**:
+- **5-point** (standard): Very dissatisfied, Dissatisfied, Neutral, Satisfied, Very satisfied
+- **Odd vs even**: Odd (5-point) allows neutral, even (4-point) forces choice
+- **Labeled vs numeric**: Fully labeled preferred for clarity
+
+**Pilot testing**:
+- Test with 5-10 people before launch
+- Check for confusing questions, technical issues, time to complete
+- Iterate based on feedback
+
+---
+
+## 9. Continuous Discovery Practices
+
+**Weekly interview cadence**:
+- Schedule 3-5 customer conversations per week (15-30 min each)
+- Rotate team members (product, design, eng)
+- Focus rotates based on current priorities (new features, onboarding, retention, etc.)
+
+**Process**:
+1. **Recruiting**: Automated email to random sample, quick scheduling link
+2. **Conducting**: Lightweight interview guide, record main points
+3. **Sharing**: Post key quotes/insights in shared Slack channel or doc
+4. **Synthesis**: Monthly review of patterns across all conversations
+
+**Benefits**:
+- Continuous learning loop
+- Early problem detection
+- Relationship building with customers
+- Team alignment (everyone hears customer voice)
+
+**Tools**: Calendly for scheduling, Zoom for calls, Dovetail or Notion for notes.
+
+---
+
+## 10. Mixed Methods Approach
+
+**Sequential**:
+- Phase 1 (Qual): Interviews to discover problems and generate hypotheses (n=10-15)
+- Phase 2 (Quant): Survey to validate findings at scale (n=100-500)
+
+**Example**:
+- Interviews: "Users mention pricing confusion" (theme in 8/12 interviews)
+- Survey: Test hypothesis—"65% of users find pricing page confusing" (validated at scale)
+
+**Concurrent**:
+- Run interviews and surveys simultaneously
+- Use interviews for depth (why), surveys for breadth (how many)
+
+**Triangulation**:
+- Interviews: What users say
+- Surveys: What users report
+- Analytics: What users do
+- Convergence across methods = high confidence
+
+---
+
+## 11. Ethical Considerations
+
+**Informed consent**:
+- Explain research purpose, how data will be used
+- Get explicit permission to record
+- Allow opt-out at any time
+
+**Privacy**:
+- Anonymize participant data in reports (use P1, P2, etc.)
+- Store recordings securely, delete after transcription (or per policy)
+- Don't share personally identifiable information
+
+**Compensation**:
+- Fair compensation for time ($50-150 for 60 min interview, $10-25 for survey)
+- Offer choice (gift card, donation, product credit)
+- Pay promptly (within 1 week)
+
+**Vulnerable populations**:
+- Extra care with children, elderly, disabled, marginalized groups
+- May require IRB approval for academic/medical research

skills/discovery-interviews-surveys/resources/template.md

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+# Discovery Interviews & Surveys - Template
+
+## Workflow
+
+```
+Research Template Progress:
+- [ ] Define objectives and hypotheses
+- [ ] Design screening and recruitment
+- [ ] Create interview guide or survey
+- [ ] Plan analysis approach
+- [ ] Document research plan
+```
+
+---
+
+## Interview Guide Template
+
+### Research Objective
+**What we're trying to learn**: [Specific learning goal]
+
+**Key hypotheses**:
+1. [Hypothesis 1]
+2. [Hypothesis 2]
+
+### Participant Criteria
+**Must have**:
+- [Criterion 1—e.g., used competitor product in last 6 months]
+- [Criterion 2—e.g., decision-maker for this purchase]
+
+**Nice to have**:
+- [Optional criterion]
+
+**Sample size**: [5-15 for qualitative themes]
+
+### Interview Script
+
+**Introduction** (2 min):
+"Thanks for joining. I'm researching [topic]. There are no right/wrong answers—I want to understand your experience. I'll record this for note-taking (with your permission). Any questions before we start?"
+
+**Warm-up** (3 min):
+- Tell me about your role and what you're responsible for.
+- [Context-setting question relevant to topic]
+
+**Problem Discovery** (20-30 min):
+
+Core questions (open-ended, behavior-focused):
+
+1. **Recent experience**: "Tell me about the last time you [specific behavior related to problem]. Walk me through what happened."
+   - Follow-up: "What prompted that?" "What happened next?" "How did that feel?"
+
+2. **Current solution**: "How do you handle [problem] today? Show me if possible."
+   - Follow-up: "How long have you done it this way?" "What works well?" "What's frustrating?"
+
+3. **Workarounds**: "What have you tried to solve [problem]?"
+   - Follow-up: "How did that go?" "What made you stop/continue?"
+
+4. **Pain points**: "What's the most frustrating part of [workflow]?"
+   - Follow-up: "How often does this happen?" "What's the impact when it does?"
+
+5. **Desired outcome**: "If you could wave a magic wand and fix [problem], what would be different?"
+   - Follow-up: "Why would that matter?" "What would that enable?"
+
+6. **Willingness to change**: "What would need to be true for you to change how you [workflow]?"
+   - Follow-up: "What's the cost of changing?" "What's the cost of not changing?"
+
+**Concept Test** (10 min, if applicable):
+
+Show concept (mockup, landing page, description):
+
+1. **Comprehension**: "In your own words, what is this?"
+2. **Audience**: "Who do you think this is for?"
+3. **Use case**: "When would you use this?" "What would you use it for?"
+4. **Value perception**: "How much would you expect to pay for this?" "Why?"
+5. **Comparison**: "How is this different from [competitor/current solution]?"
+6. **Concerns**: "What concerns you about this?" "What would hold you back?"
+
+**Wrap-up** (5 min):
+- "Is there anything I should have asked but didn't?"
+- "Who else should I talk to?" (snowball sampling)
+- "Can I follow up if I have more questions?"
+
+**Thank and compensate**: [Gift card, donation, etc.]
+
+---
+
+## Survey Template
+
+### Survey Structure
+
+**Screener** (qualify participants):
+1. [Demographic filter—e.g., age, location]
+2. [Behavioral filter—e.g., used product X]
+3. [Decision-making filter—e.g., influence on purchase]
+
+**Main Survey**:
+
+**Section 1: Current Behavior** (establish baseline)
+1. Which of the following [products/services] do you currently use? (Select all that apply)
+   - [Option 1]
+   - [Option 2]
+   - None of the above
+
+2. How often do you [key behavior]?
+   - Daily / Weekly / Monthly / Rarely / Never
+
+3. What do you use [product/service] for? (Open-end)
+
+**Section 2: Satisfaction & Problems** (identify pain points)
+4. How satisfied are you with your current [solution]? (1-5 scale)
+   - Very dissatisfied / Dissatisfied / Neutral / Satisfied / Very satisfied
+
+5. What are the biggest challenges you face with [current solution]? (Open-end)
+
+6. How important is [feature/capability] to you? (1-5 scale)
+   - Not at all important / Slightly important / Moderately important / Very important / Extremely important
+
+**Section 3: Feature Prioritization** (for product roadmap)
+7. Please rate the importance of each feature: (Matrix—rows = features, columns = 1-5 importance)
+   - [Feature 1]
+   - [Feature 2]
+   - [Feature 3]
+
+8. If you could only have 3 of these features, which would you choose? (Rank order, top 3)
+
+**Section 4: Concept Test** (if applicable)
+
+Show concept (image, description):
+
+9. In your own words, what is this product/service? (Open-end)
+
+10. How likely are you to use this if it were available? (1-5 scale)
+    - Very unlikely / Unlikely / Neutral / Likely / Very likely
+
+11. What would you be willing to pay per month? (Price sensitivity)
+    - Less than $X / $X-$Y / $Y-$Z / More than $Z / I wouldn't pay
+
+12. What concerns do you have about this concept? (Open-end)
+
+**Section 5: Demographics** (for segmentation)
+13. Company size (if B2B): [ranges]
+14. Industry: [options]
+15. Role: [options]
+
+**Thank you**: "Thank you! [Incentive details if applicable]"
+
+---
+
+## Jobs-to-be-Done Interview Template
+
+Focus on recent switchers (adopted your product or competitor in last 3-6 months).
+
+**Timeline reconstruction**:
+
+1. **First thought** (passive looking): "When did you first realize you had a problem with [old solution]? What happened?"
+
+2. **Trigger event** (active looking): "What made you start actively looking for alternatives? What changed?"
+
+3. **Consideration** (evaluation): "What options did you consider? How did you evaluate them?"
+   - Follow-up: "What criteria mattered most?" "What sources did you trust?"
+
+4. **Anxiety** (concerns): "What almost stopped you from switching?" "What made you hesitate?"
+
+5. **Decision** (commitment): "What made you ultimately choose [product]? What was the deciding factor?"
+
+6. **First use** (onboarding): "Walk me through your first experience using [product]. What stood out?"
+
+7. **Habit formation** (ongoing): "How has your use evolved? What's different now vs. early days?"
+
+8. **Outcome** (job fulfillment): "What's better now compared to before? What job is [product] doing for you?"
+
+9. **Tradeoffs**: "What did you give up by switching? What's worse now?"
+
+---
+
+## Question Design Principles
+
+**DO:**
+- ✅ Ask about past behavior: "Tell me about the last time..."
+- ✅ Request demonstrations: "Can you show me how you..."
+- ✅ Dig deeper: "Why did that matter?" "Tell me more" "What else?"
+- ✅ Embrace silence: Pause after questions. Let participant think.
+- ✅ Use open-ended questions: "What..." "How..." "Tell me about..."
+- ✅ Focus on specifics: "Walk me through..." "What happened next?"
+
+**DON'T:**
+- ❌ Ask leading questions: "Don't you think...?" "Isn't it true that...?"
+- ❌ Ask hypotheticals: "Would you...?" "If we built..."
+- ❌ Ask multiple questions at once: Confuses participants
+- ❌ Interrupt or finish sentences: Let them talk
+- ❌ Explain or defend: You're learning, not selling
+- ❌ Ask "why" repeatedly: Sounds accusatory. Use "What prompted..." "What mattered..."
+
+---
+
+## Screening Questions
+
+**For B2B SaaS**:
+1. What is your role? [Job title dropdown]
+2. What is your company size? [Employee count ranges]
+3. Do you influence or make purchase decisions for [product category]? Yes/No
+4. Are you currently using [competitor product]? Yes/No/Used in the past
+5. How long have you been using [product]? [Duration ranges]
+
+**For Consumer**:
+1. Which age range are you in? [Ranges]
+2. Do you currently [key behavior]? Daily/Weekly/Monthly/Rarely/Never
+3. When did you last [specific action]? [Time ranges]
+4. Which of the following have you used? [Product list, select all]
+
+**Disqualifiers** (screen out):
+- Competitors (unless research is competitive analysis)
+- Never used category (for product-specific research)
+- Outside target demographic
+
+---
+
+## Analysis Templates
+
+**For Interviews: Thematic Coding**
+
+1. **Transcribe**: Convert recordings to text (automated tool or manual)
+2. **Initial coding**: Read transcripts, highlight key quotes, note themes
+3. **Affinity mapping**: Group similar quotes/observations
+4. **Theme identification**: Name each cluster (e.g., "Onboarding confusion", "Pricing concerns")
+5. **Frequency counting**: How many participants mentioned each theme?
+6. **Quote extraction**: Pull representative quotes for each theme
+
+**Output format**:
+```
+Theme: [Name]
+Frequency: X/Y participants
+Representative quotes:
+- "Quote 1" (P3)
+- "Quote 2" (P7)
+Insight: [What this means]
+Recommendation: [What to do]
+```
+
+**For Surveys: Statistical Analysis**
+
+1. **Data cleaning**: Remove incomplete responses, check for quality
+2. **Descriptive stats**: Mean, median, mode, distribution for scaled questions
+3. **Cross-tabulation**: Compare segments (e.g., users vs non-users)
+4. **Statistical significance**: Chi-square (categorical) or t-test (continuous)
+5. **Open-end coding**: Categorize open-ended responses, count frequencies
+6. **Visualization**: Charts for key findings (bar charts, distribution plots)
+
+**Key metrics**:
+- CSAT (Customer Satisfaction): Average rating (1-5 scale)
+- NPS (Net Promoter Score): % Promoters (9-10) minus % Detractors (0-6)
+- Feature importance vs satisfaction: 2x2 matrix (importance on Y, satisfaction on X)
+- Sample size check: n ≥ 30 per segment for statistical power
+
+---
+
+## Insights Document Template
+
+```markdown
+# Research Insights: [Study Name]
+
+## Executive Summary
+[2-3 sentences: key findings, decision recommendation]
+
+## Research Objective
+**What we wanted to learn**: [Objective]
+**Key questions**: [Questions]
+
+## Methodology
+- **Method**: [Interviews/Survey/Mixed]
+- **Participants**: [N, demographics]
+- **Dates**: [When conducted]
+
+## Key Findings
+
+### Finding 1: [Theme Name]
+**Evidence**: X/Y participants mentioned [pattern]
+**Quotes**:
+- "Quote 1" (P3)
+- "Quote 2" (P7)
+**Insight**: [What this means]
+
+### Finding 2: [Theme Name]
+[Same structure]
+
+## Surprises & Contradictions
+[What didn't match expectations? Outliers?]
+
+## Recommendations
+1. [Action 1—specific, based on findings]
+2. [Action 2]
+3. [Action 3]
+
+## Confidence & Limitations
+- Confidence level: [High/Medium/Low] based on [sample size, consistency, etc.]
+- Limitations: [Sampling bias? Small sample? Anything that limits generalization?]
+
+## Next Steps
+- [Follow-up research needed?]
+- [Decision to be made?]
+```