Marketplace

pm-discovery

Product discovery frameworks for PMs - customer interviews, assumption mapping, JTBD, RICE prioritization, and opportunity solution trees. Transforms research into product decisions.

$ Installer

git clone https://github.com/majesticlabs-dev/majestic-marketplace /tmp/majestic-marketplace && cp -r /tmp/majestic-marketplace/plugins/majestic-company/skills/pm-discovery ~/.claude/skills/majestic-marketplace

// tip: Run this command in your terminal to install the skill


name: pm-discovery description: Product discovery frameworks for PMs - customer interviews, assumption mapping, JTBD, RICE prioritization, and opportunity solution trees. Transforms research into product decisions. triggers:

  • pm discovery
  • product discovery
  • customer interview
  • assumption mapping
  • rice prioritization
  • ice scoring
  • jobs to be done
  • jtbd
  • opportunity solution tree
  • feature prioritization
  • product hypothesis

PM Discovery

Product discovery frameworks for turning research into product decisions. Use after market research, before implementation planning.

When to Use

  • After customer interviews, before synthesizing insights
  • When prioritizing features or opportunities
  • When validating product hypotheses
  • When mapping assumptions to test
  • When structuring discovery findings for stakeholders

Discovery Frameworks

1. Customer Interview Synthesis

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]

2. Assumption Mapping

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]

3. Jobs-to-be-Done (JTBD)

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]

4. Feature Prioritization

RICE Scoring:

RICE Score = (Reach × Impact × Confidence) / Effort
FactorDefinitionScale
ReachUsers affected per quarterActual number
ImpactEffect on users3=Massive, 2=High, 1=Medium, 0.5=Low, 0.25=Minimal
ConfidenceHow sure are you?100%=High, 80%=Medium, 50%=Low
EffortPerson-months to shipActual 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
FactorScale
Impact1-10 (potential value)
Confidence1-10 (certainty of impact)
Ease1-10 (implementation simplicity)

5. Opportunity Solution Tree

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]

6. Product Hypothesis

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]

Discovery Synthesis

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-Patterns to Avoid

Anti-PatternWhy It FailsInstead Do
Leading questionsConfirms bias, not truthAsk open-ended, follow with "why"
Hypothetical pricingPeople lie about future spendingAsk about current spending
Feature requests as truthUsers describe solutions, not problemsDig for underlying need
Small sample size decisionsAnecdotes ≠ patternsRequire 5+ signals minimum
Skipping competitor analysisReinventing existing solutionsResearch before ideating

Integration with Other Skills

  • Before PM Discovery: Use problem-research for market pain points
  • Before PM Discovery: Use customer-discovery to find user communities
  • After PM Discovery: Use /majestic:prd to document requirements
  • After PM Discovery: Use /majestic:plan for implementation planning

Repository

majesticlabs-dev
majesticlabs-dev
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majesticlabs-dev/majestic-marketplace/plugins/majestic-company/skills/pm-discovery
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Updated5d ago
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