Product discovery frameworks for PMs - customer interviews, assumption mapping, JTBD, RICE prioritization, and opportunity solution trees. Transforms research into product decisions.
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Product discovery frameworks for turning research into product decisions. Use after market research, before implementation planning.
Interview Question Bank:
## Problem Discovery
- "Walk me through the last time you [did X]..."
- "What's the hardest part about [doing X]?"
- "Why is that hard?" (ask 3x)
- "What have you tried to solve this?"
- "What happened when you tried that?"
## Current Solution Analysis
- "How do you handle [X] today?"
- "How often do you do this?"
- "What would happen if you couldn't do this?"
- "How much time/money does this cost you?"
## Switching Signals
- "Have you looked for other solutions?"
- "What would make you switch?"
- "What's stopping you from switching now?"
## Value Discovery
- "If you could wave a magic wand, what would change?"
- "What would that be worth to you?"
- "Who else cares about this problem?"
Interview Synthesis Template:
## Interview: [Customer Name/Segment]
**Date:** YYYY-MM-DD | **Duration:** X min | **Role:** [Title]
### Problem Quotes (verbatim)
> "[Exact quote about the problem]"
> "[Another revealing quote]"
### Current Behavior
- Does [X] using [current solution]
- Frequency: [daily/weekly/monthly]
- Time spent: [X hours/month]
### Pain Intensity: [1-5]
- 1: Mild annoyance
- 3: Significant friction
- 5: "Hair on fire" problem
### Willingness to Pay Signal
- [ ] Actively searching for solutions
- [ ] Has budget allocated
- [ ] Named a specific price point: $___
- [ ] Would switch immediately if solved
### Key Insight
[One sentence capturing the non-obvious learning]
Riskiest Assumption Test (RAT):
## Assumption Map
### Desirability (Will they want it?)
| Assumption | Evidence For | Evidence Against | Risk Level |
|------------|--------------|------------------|------------|
| [Users want X] | [data] | [data] | High/Med/Low |
### Viability (Will it work for the business?)
| Assumption | Evidence For | Evidence Against | Risk Level |
|------------|--------------|------------------|------------|
| [Users will pay $X] | [data] | [data] | High/Med/Low |
### Feasibility (Can we build it?)
| Assumption | Evidence For | Evidence Against | Risk Level |
|------------|--------------|------------------|------------|
| [We can integrate with X] | [data] | [data] | High/Med/Low |
### Riskiest Assumption to Test Next
**Assumption:** [The one with highest risk + least evidence]
**Test:** [Cheapest way to validate/invalidate]
**Success Criteria:** [Specific threshold]
**Timeline:** [Days/weeks]
Job Statement Format:
When [situation/trigger],
I want to [motivation/goal],
so I can [expected outcome].
JTBD Canvas:
## Job: [Core functional job]
### Trigger/Situation
- When does this job arise?
- What context are they in?
### Functional Job (what they're trying to do)
[Action verb] + [object] + [clarifying context]
Example: "Organize customer feedback by theme before the weekly product meeting"
### Emotional Job (how they want to feel)
- Feel [emotion] about [situation]
Example: "Feel confident presenting insights to leadership"
### Social Job (how they want to be perceived)
- Be seen as [perception] by [audience]
Example: "Be seen as data-driven by the exec team"
### Current Solutions
| Solution | Hiring Criteria | Firing Criteria |
|----------|-----------------|-----------------|
| [Tool/workaround] | [Why they use it] | [Why they'd stop] |
### Outcome Metrics
What does "job done well" look like?
- Speed: [Complete X in Y minutes]
- Quality: [Z accuracy/completeness]
- Confidence: [Feel certain about decision]
RICE Scoring:
RICE Score = (Reach × Impact × Confidence) / Effort
| Factor | Definition | Scale |
|---|---|---|
| Reach | Users affected per quarter | Actual number |
| Impact | Effect on users | 3=Massive, 2=High, 1=Medium, 0.5=Low, 0.25=Minimal |
| Confidence | How sure are you? | 100%=High, 80%=Medium, 50%=Low |
| Effort | Person-months to ship | Actual estimate |
RICE Table:
| Feature | Reach | Impact | Confidence | Effort | RICE Score |
|---------|-------|--------|------------|--------|------------|
| [Feature A] | 5000 | 2 | 80% | 2 | 4000 |
| [Feature B] | 1000 | 3 | 50% | 1 | 1500 |
ICE Scoring (simpler alternative):
ICE Score = Impact × Confidence × Ease
| Factor | Scale |
|---|---|
| Impact | 1-10 (potential value) |
| Confidence | 1-10 (certainty of impact) |
| Ease | 1-10 (implementation simplicity) |
Structure:
Outcome (measurable business goal)
├── Opportunity 1 (unmet customer need)
│ ├── Solution 1a
│ │ └── Experiment: [test]
│ └── Solution 1b
│ └── Experiment: [test]
├── Opportunity 2 (another need)
│ └── Solution 2a
│ └── Experiment: [test]
└── Opportunity 3
└── ...
OST Template:
## Outcome
**Goal:** [Measurable objective]
**Current:** [Baseline metric]
**Target:** [Target metric]
**Timeline:** [By when]
## Opportunity Map
### Opportunity 1: [Customer need/pain point]
**Evidence:** [Interview quotes, data]
**Size:** [How many users affected]
**Solutions considered:**
1. **[Solution A]**
- Effort: [S/M/L]
- Experiment: [How to test cheaply]
- Success metric: [What to measure]
2. **[Solution B]**
- Effort: [S/M/L]
- Experiment: [How to test cheaply]
- Success metric: [What to measure]
**Selected:** [Which and why]
Hypothesis Format:
## Hypothesis: [Short name]
**We believe that** [building this feature/making this change]
**For** [target user segment]
**Will result in** [expected outcome/behavior change]
**We will know we're right when** [measurable success criteria]
### Riskiest Assumption
[The assumption that if wrong, invalidates the hypothesis]
### Minimum Test
[Cheapest/fastest way to validate]
- Type: [Prototype/Fake door/Concierge/etc]
- Duration: [X days/weeks]
- Sample size: [N users]
### Decision Criteria
- **Ship if:** [specific threshold met]
- **Iterate if:** [mixed signals, specify]
- **Kill if:** [specific threshold not met]
After gathering insights, synthesize into:
## Discovery Summary: [Feature/Initiative]
### What We Learned
1. [Key insight with evidence]
2. [Key insight with evidence]
3. [Key insight with evidence]
### User Segments & Their Jobs
| Segment | Primary Job | Pain Intensity | Size |
|---------|-------------|----------------|------|
| [Segment A] | [JTBD] | [1-5] | [N users] |
### Prioritized Opportunities
| Rank | Opportunity | Evidence | RICE |
|------|-------------|----------|------|
| 1 | [Opp] | [Quote/data] | [Score] |
### Recommended Next Step
**Do:** [Specific action]
**Test:** [What to validate]
**Success looks like:** [Measurable outcome]
### What We Still Don't Know
- [ ] [Open question to investigate]
- [ ] [Assumption still untested]
| Anti-Pattern | Why It Fails | Instead Do |
|---|---|---|
| Leading questions | Confirms bias, not truth | Ask open-ended, follow with "why" |
| Hypothetical pricing | People lie about future spending | Ask about current spending |
| Feature requests as truth | Users describe solutions, not problems | Dig for underlying need |
| Small sample size decisions | Anecdotes ≠ patterns | Require 5+ signals minimum |
| Skipping competitor analysis | Reinventing existing solutions | Research before ideating |
problem-research for market pain pointscustomer-discovery to find user communities/majestic:prd to document requirements/majestic:plan for implementation planning