discovery-interviews-surveys

What this skill does

# Discovery Interviews & Surveys

## Table of Contents
- [Workflow](#workflow)
- [Common Patterns](#common-patterns)
- [Guardrails](#guardrails)
- [Quick Reference](#quick-reference)

## Workflow

Copy this checklist and track your progress:

```
Discovery Research Progress:
- [ ] Step 1: Define research objectives and hypotheses
- [ ] Step 2: Identify target participants
- [ ] Step 3: Choose research method (interviews, surveys, or both)
- [ ] Step 4: Design research instruments
- [ ] Step 5: Conduct research and collect data
- [ ] Step 6: Analyze findings and extract insights
```

**Step 1: Define research objectives**

Specify what you're trying to learn, key hypotheses to test, success criteria for research, and decision to be informed. See [Common Patterns](#common-patterns) for typical objectives.

**Step 2: Identify target participants**

Define participant criteria (demographics, behaviors, firmographics), sample size needed, recruitment strategy, and screening questions. For sampling strategies, see [resources/methodology.md](resources/methodology.md#participant-recruitment).

**Step 3: Choose research method**

Based on objective and constraints:
- **For deep problem discovery (5-15 participants)** → Use [resources/template.md](resources/template.md#interview-guide-template) for in-depth interviews
- **For concept testing at scale (50-200+ participants)** → Use [resources/template.md](resources/template.md#survey-template) for quantitative validation
- **For JTBD research** → Use [resources/methodology.md](resources/methodology.md#jobs-to-be-done-interviews) for switch interviews
- **For mixed methods** → Interviews for discovery, surveys for validation

**Step 4: Design research instruments**

Create interview guide or survey with bias-avoidance techniques. Use [resources/template.md](resources/template.md) for structure. Avoid leading questions, focus on past behavior, use "show me" requests. For advanced question design, see [resources/methodology.md](resources/methodology.md#question-design-principles).

**Step 5: Conduct research**

Execute interviews (record with permission, take notes) or distribute surveys (pilot test first). Use proper techniques (active listening, follow-up probes, silence for thinking). See [Guardrails](#guardrails) for critical requirements.

**Step 6: Analyze findings**

For interviews: thematic coding, affinity mapping, quote extraction. For surveys: statistical analysis, cross-tabs, open-end coding. Create insights document with evidence. Self-assess using [resources/evaluators/rubric_discovery_interviews_surveys.json](resources/evaluators/rubric_discovery_interviews_surveys.json). **Minimum standard**: Average score ≥ 3.5.

## Common Patterns

**Pattern 1: Problem Discovery Interviews**
- **Objective**: Understand user pain points and current workflows
- **Approach**: 8-12 in-depth interviews, open-ended questions, focus on past behavior and actual solutions
- **Key questions**: "Tell me about the last time...", "Walk me through...", "What have you tried?", "How's that working?"
- **Output**: Problem themes, frequency estimates, current workarounds, willingness to change
- **Example**: B2B SaaS discovery—interview potential customers about current tools and pain points

**Pattern 2: Jobs-to-be-Done Research**
- **Objective**: Identify why users "hire" products and what triggers switching
- **Approach**: Switch interviews with recent adopters or switchers, focus on timeline and context
- **Key questions**: "What prompted you to look?", "What alternatives did you consider?", "What almost stopped you?", "What's different now?"
- **Output**: Hiring triggers, firing triggers, desired outcomes, anxieties, habits
- **Example**: SaaS churn research—interview recent churners about switch to competitor

**Pattern 3: Concept Testing (Qualitative)**
- **Objective**: Test product concepts, positioning, or messaging before launch
- **Approach**: 10-15 interviews showing concept (mockup, landing page, description), gather reactions
- **Key questions**: "In your own words, what is this?", "Who is this for?", "What would you use it for?", "How much would you expect to pay?"
- **Output**: Comprehension score, perceived value, target audience clarity, pricing anchors
- **Example**: Pre-launch validation—test landing page messaging with target audience

**Pattern 4: Survey for Quantitative Validation**
- **Objective**: Validate findings from interviews at scale or prioritize features
- **Approach**: 100-500 participants, mix of scaled questions (Likert, ranking) and open-ends
- **Key questions**: Satisfaction scores (CSAT, NPS), feature importance/satisfaction (Kano), usage frequency, demographics
- **Output**: Statistical significance, segmentation, prioritization (importance vs satisfaction matrix)
- **Example**: Product roadmap prioritization—survey 500 users on feature importance

**Pattern 5: Continuous Discovery**
- **Objective**: Ongoing learning, not one-time project
- **Approach**: Weekly customer conversations (15-30 min), rotating team members, shared notes
- **Key questions**: Varies by current focus (new features, onboarding, expansion, retention)
- **Output**: Continuous insight feed, early problem detection, relationship building
- **Example**: Product team does 3-5 customer calls weekly, logs insights in shared doc

## Guardrails

**Key requirements:**

1. **Avoid leading questions**: Phrase questions neutrally rather than telegraphing the "right" answer. Instead of: "Don't you think our UI is confusing?" use: "Walk me through using this feature. What happened?"

2. **Focus on past behavior, not hypotheticals**: What people did reveals truth; what they say they'd do is often wrong. Instead of: "Would you use this feature?" use: "Tell me about the last time you needed to do X."

3. **Use "show me" over "tell me"**: Actual behavior is more reliable than described behavior. Ask to screen-share, demonstrate current workflow, show artifacts (spreadsheets, tools).

4. **Recruit right participants**: Screen carefully. Wrong participants waste time. Define inclusion/exclusion criteria and use screening surveys.

5. **Sample size appropriate for method**: Interviews: 5-15 for themes to emerge. Surveys: 100+ for statistical significance, 30+ per segment if comparing.

6. **Seek disconfirming evidence**: Actively look for evidence against your hypothesis. If 9/10 interviews support the hypothesis, focus heavily on the 1 that does not.

7. **Record and transcribe (with permission)**: Memory is unreliable. Record interviews, transcribe for analysis. Take notes as backup.

8. **Analyze systematically**: Use thematic coding, count themes, and present contradictory evidence rather than cherry-picking supportive quotes.

**Common pitfalls:**

- ❌ **Asking "would you" questions**: Hypotheticals are unreliable. Focus on "have you", "tell me about when", "show me"
- ❌ **Small sample statistical claims**: "80% of users want feature X" from 5 interviews is not valid. Interviews = themes, surveys = statistics
- ❌ **Selection bias**: Interviewing only enthusiasts or only detractors skews results. Recruit diverse sample
- ❌ **Ignoring non-verbal cues**: Hesitation, confusion, workarounds during "show me" reveal truth beyond words
- ❌ **Stopping at surface answers**: First answer is often rationalization. Follow up: "Tell me more", "Why did that matter?", "What else?"

## Quick Reference

**Key resources:**

- **[resources/template.md](resources/template.md)**: Interview guide template, survey template, JTBD question bank, screening questions
- **[resources/methodology.md](resources/methodology.md)**: Advanced techniques (JTBD switch interviews, Kano analysis, thematic coding, statistical analysis, continuous discovery)
- **[resources/evaluators/rubric_discovery_interviews_surveys.json](resources/evaluators/rubric_discovery_interviews_surveys.json)**: Quality criteria for research design and execution

**Typical workflow time:**

- Int