技能备份 - 2026-04-15 (40个技能)
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# Product Management Frameworks
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Comprehensive reference for prioritization, discovery, and measurement frameworks.
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---
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## Table of Contents
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- [Prioritization Frameworks](#prioritization-frameworks)
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- [RICE Framework](#rice-framework)
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- [Value vs Effort Matrix](#value-vs-effort-matrix)
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- [MoSCoW Method](#moscow-method)
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- [ICE Scoring](#ice-scoring)
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- [Kano Model](#kano-model)
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- [Discovery Frameworks](#discovery-frameworks)
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- [Customer Interview Guide](#customer-interview-guide)
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- [Hypothesis Template](#hypothesis-template)
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- [Opportunity Solution Tree](#opportunity-solution-tree)
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- [Jobs to Be Done](#jobs-to-be-done)
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- [Metrics Frameworks](#metrics-frameworks)
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- [North Star Metric](#north-star-metric-framework)
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- [HEART Framework](#heart-framework)
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- [Funnel Analysis](#funnel-analysis-template)
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- [Feature Success Metrics](#feature-success-metrics)
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- [Strategic Frameworks](#strategic-frameworks)
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- [Product Vision Template](#product-vision-template)
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- [Competitive Analysis](#competitive-analysis-framework)
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- [Go-to-Market Checklist](#go-to-market-checklist)
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---
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## Prioritization Frameworks
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### RICE Framework
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**Formula:**
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```
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RICE Score = (Reach × Impact × Confidence) / Effort
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```
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**Components:**
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| Component | Description | Values |
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|-----------|-------------|--------|
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| **Reach** | Users affected per quarter | Numeric count (e.g., 5000) |
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| **Impact** | Effect on each user | massive=3x, high=2x, medium=1x, low=0.5x, minimal=0.25x |
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| **Confidence** | Certainty in estimates | high=100%, medium=80%, low=50% |
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| **Effort** | Person-months required | xl=13, l=8, m=5, s=3, xs=1 |
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**Example Calculation:**
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```
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Feature: Mobile Push Notifications
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Reach: 10,000 users
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Impact: massive (3x)
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Confidence: medium (80%)
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Effort: medium (5 person-months)
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RICE = (10,000 × 3 × 0.8) / 5 = 4,800
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```
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**Interpretation Guidelines:**
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- **1000+**: High priority - strong candidates for next quarter
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- **500-999**: Medium priority - consider for roadmap
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- **100-499**: Low priority - keep in backlog
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- **<100**: Deprioritize - requires new data to reconsider
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**When to Use RICE:**
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- Quarterly roadmap planning
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- Comparing features across different product areas
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- Communicating priorities to stakeholders
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- Resolving prioritization debates with data
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**RICE Limitations:**
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- Requires reasonable estimates (garbage in, garbage out)
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- Doesn't account for dependencies
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- May undervalue platform investments
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- Reach estimates can be gaming-prone
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---
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### Value vs Effort Matrix
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```
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Low Effort High Effort
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+--------------+------------------+
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High Value | QUICK WINS | BIG BETS |
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| [Do First] | [Strategic] |
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+--------------+------------------+
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Low Value | FILL-INS | TIME SINKS |
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| [Maybe] | [Avoid] |
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+--------------+------------------+
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```
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**Quadrant Definitions:**
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| Quadrant | Characteristics | Action |
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|----------|-----------------|--------|
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| **Quick Wins** | High impact, low effort | Prioritize immediately |
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| **Big Bets** | High impact, high effort | Plan strategically, validate ROI |
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| **Fill-Ins** | Low impact, low effort | Use to fill sprint gaps |
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| **Time Sinks** | Low impact, high effort | Avoid unless required |
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**Portfolio Balance:**
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- Ideal mix: 40% Quick Wins, 30% Big Bets, 20% Fill-Ins, 10% Buffer
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- Review balance quarterly
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- Adjust based on team morale and strategic goals
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---
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### MoSCoW Method
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| Category | Definition | Sprint Allocation |
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|----------|------------|-------------------|
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| **Must Have** | Critical for launch; product fails without it | 60% of capacity |
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| **Should Have** | Important but workarounds exist | 20% of capacity |
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| **Could Have** | Desirable enhancements | 10% of capacity |
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| **Won't Have** | Explicitly out of scope (this release) | 0% - documented |
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**Decision Criteria for "Must Have":**
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- Regulatory/legal requirement
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- Core user job cannot be completed without it
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- Explicitly promised to customers
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- Security or data integrity requirement
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**Common Mistakes:**
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- Everything becomes "Must Have" (scope creep)
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- Not documenting "Won't Have" items
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- Treating "Should Have" as optional (they're important)
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- Forgetting to revisit for next release
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---
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### ICE Scoring
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**Formula:**
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```
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ICE Score = (Impact + Confidence + Ease) / 3
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```
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| Component | Scale | Description |
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|-----------|-------|-------------|
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| **Impact** | 1-10 | Expected effect on key metric |
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| **Confidence** | 1-10 | How sure are you about impact? |
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| **Ease** | 1-10 | How easy to implement? |
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**When to Use ICE vs RICE:**
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- ICE: Early-stage exploration, quick estimates
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- RICE: Quarterly planning, cross-team prioritization
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---
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### Kano Model
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Categories of feature satisfaction:
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| Type | Absent | Present | Priority |
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|------|--------|---------|----------|
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| **Basic (Must-Be)** | Dissatisfied | Neutral | High - table stakes |
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| **Performance (Linear)** | Neutral | Satisfied proportionally | Medium - differentiation |
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| **Excitement (Delighter)** | Neutral | Very satisfied | Strategic - competitive edge |
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| **Indifferent** | Neutral | Neutral | Low - skip unless cheap |
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| **Reverse** | Satisfied | Dissatisfied | Avoid - remove if exists |
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**Feature Classification Questions:**
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1. How would you feel if the product HAS this feature?
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2. How would you feel if the product DOES NOT have this feature?
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---
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## Discovery Frameworks
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### Customer Interview Guide
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**Structure (35 minutes total):**
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```
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1. CONTEXT QUESTIONS (5 min)
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└── Build rapport, understand role
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2. PROBLEM EXPLORATION (15 min)
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└── Dig into pain points
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3. SOLUTION VALIDATION (10 min)
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└── Test concepts if applicable
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4. WRAP-UP (5 min)
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└── Referrals, follow-up
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```
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**Detailed Script:**
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#### Phase 1: Context (5 min)
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```
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"Thanks for taking the time. Before we dive in..."
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- What's your role and how long have you been in it?
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- Walk me through a typical day/week.
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- What tools do you use for [relevant task]?
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```
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#### Phase 2: Problem Exploration (15 min)
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```
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"I'd love to understand the challenges you face with [area]..."
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- What's the hardest part about [task]?
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- Can you tell me about the last time you struggled with this?
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- What did you do? What happened?
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- How often does this happen?
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- What does it cost you (time, money, frustration)?
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- What have you tried to solve it?
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- Why didn't those solutions work?
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```
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#### Phase 3: Solution Validation (10 min)
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```
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"Based on what you've shared, I'd like to get your reaction to an idea..."
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[Show prototype/concept - keep it rough to invite honest feedback]
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- What's your initial reaction?
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- How does this compare to what you do today?
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- What would prevent you from using this?
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- How much would this be worth to you?
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- Who else would need to approve this purchase?
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```
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#### Phase 4: Wrap-up (5 min)
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```
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"This has been incredibly helpful..."
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- Anything else I should have asked?
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- Who else should I talk to about this?
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- Can I follow up if I have more questions?
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```
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**Interview Best Practices:**
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- Never ask "would you use this?" (people lie about future behavior)
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- Ask about past behavior: "Tell me about the last time..."
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- Embrace silence - count to 7 before filling gaps
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- Watch for emotional reactions (pain = opportunity)
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- Record with permission; take minimal notes during
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---
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### Hypothesis Template
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**Format:**
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```
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We believe that [building this feature/making this change]
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For [target user segment]
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Will [achieve this measurable outcome]
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We'll know we're right when [specific metric moves by X%]
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We'll know we're wrong when [falsification criteria]
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```
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**Example:**
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```
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We believe that adding saved payment methods
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For returning customers
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Will increase checkout completion rate
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We'll know we're right when checkout completion increases by 15%
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We'll know we're wrong when completion rate stays flat after 2 weeks
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or saved payment adoption is < 20%
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```
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**Hypothesis Quality Checklist:**
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- [ ] Specific user segment defined
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- [ ] Measurable outcome (number, not "better")
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- [ ] Timeframe for measurement
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- [ ] Clear falsification criteria
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- [ ] Based on evidence (interviews, data)
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---
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### Opportunity Solution Tree
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**Structure:**
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```
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[DESIRED OUTCOME]
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│
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├── Opportunity 1: [User problem/need]
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│ ├── Solution A
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│ ├── Solution B
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│ └── Experiment: [Test to validate]
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│
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├── Opportunity 2: [User problem/need]
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│ ├── Solution C
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│ └── Solution D
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│
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└── Opportunity 3: [User problem/need]
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└── Solution E
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```
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**Example:**
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```
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[Increase monthly active users by 20%]
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│
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├── Users forget to return
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│ ├── Weekly email digest
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│ ├── Mobile push notifications
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│ └── Test: A/B email frequency
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│
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├── New users don't find value quickly
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│ ├── Improved onboarding wizard
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│ └── Personalized first experience
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│
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└── Users churn after free trial
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├── Extended trial for engaged users
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└── Friction audit of upgrade flow
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```
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**Process:**
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1. Start with measurable outcome (not solution)
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2. Map opportunities from user research
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3. Generate multiple solutions per opportunity
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4. Design small experiments to validate
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5. Prioritize based on learning potential
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---
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### Jobs to Be Done
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**JTBD Statement Format:**
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```
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When [situation/trigger]
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I want to [motivation/job]
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So I can [expected outcome]
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```
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**Example:**
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```
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When I'm running late for a meeting
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I want to notify attendees quickly
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So I can set appropriate expectations and reduce anxiety
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```
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**Force Diagram:**
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```
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┌─────────────────┐
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Push from │ │ Pull toward
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current ──────>│ SWITCH │<────── new
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solution │ DECISION │ solution
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│ │
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└─────────────────┘
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^ ^
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Anxiety of | | Habit of
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change ──────┘ └────── status quo
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```
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**Interview Questions for JTBD:**
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- When did you first realize you needed something like this?
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- What were you using before? Why did you switch?
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- What almost prevented you from switching?
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- What would make you go back to the old way?
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---
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## Metrics Frameworks
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### North Star Metric Framework
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**Criteria for a Good NSM:**
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1. **Measures value delivery**: Captures what users get from product
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2. **Leading indicator**: Predicts business success
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3. **Actionable**: Teams can influence it
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4. **Measurable**: Trackable on regular cadence
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**Examples by Business Type:**
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| Business | North Star Metric | Why |
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|----------|-------------------|-----|
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| Spotify | Time spent listening | Measures engagement value |
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| Airbnb | Nights booked | Core transaction metric |
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| Slack | Messages sent in channels | Team collaboration value |
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| Dropbox | Files stored/synced | Storage utility delivered |
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| Netflix | Hours watched | Entertainment value |
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**Supporting Metrics Structure:**
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```
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[NORTH STAR METRIC]
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│
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├── Breadth: How many users?
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├── Depth: How engaged are they?
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└── Frequency: How often do they engage?
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```
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---
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### HEART Framework
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| Metric | Definition | Example Signals |
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|--------|------------|-----------------|
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| **Happiness** | Subjective satisfaction | NPS, CSAT, survey scores |
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| **Engagement** | Depth of involvement | Session length, actions/session |
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| **Adoption** | New user behavior | Signups, feature activation |
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| **Retention** | Continued usage | D7/D30 retention, churn rate |
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| **Task Success** | Efficiency & effectiveness | Completion rate, time-on-task, errors |
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**Goals-Signals-Metrics Process:**
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1. **Goal**: What user behavior indicates success?
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2. **Signal**: How would success manifest in data?
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3. **Metric**: How do we measure the signal?
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**Example:**
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```
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Feature: New checkout flow
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Goal: Users complete purchases faster
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Signal: Reduced time in checkout, fewer drop-offs
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Metrics:
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- Median checkout time (target: <2 min)
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- Checkout completion rate (target: 85%)
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- Error rate (target: <2%)
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```
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---
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### Funnel Analysis Template
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**Standard Funnel:**
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```
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Acquisition → Activation → Retention → Revenue → Referral
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│ │ │ │ │
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│ │ │ │ │
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How do First Come back Pay for Tell
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they find "aha" regularly value others
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you? moment
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```
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**Metrics per Stage:**
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| Stage | Key Metrics | Typical Benchmark |
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|-------|-------------|-------------------|
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| **Acquisition** | Visitors, CAC, channel mix | Varies by channel |
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| **Activation** | Signup rate, onboarding completion | 20-30% visitor→signup |
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| **Retention** | D1/D7/D30 retention, churn | D1: 40%, D7: 20%, D30: 10% |
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| **Revenue** | Conversion rate, ARPU, LTV | 2-5% free→paid |
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| **Referral** | NPS, viral coefficient, referrals/user | NPS > 50 is excellent |
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**Analysis Framework:**
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1. Map current conversion rates at each stage
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2. Identify biggest drop-off point
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3. Qualitative research: Why are users leaving?
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4. Hypothesis: What would improve conversion?
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5. Test and measure
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---
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### Feature Success Metrics
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| Metric | Definition | Target Range |
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|--------|------------|--------------|
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| **Adoption** | % users who try feature | 30-50% within 30 days |
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| **Activation** | % who complete core action | 60-80% of adopters |
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| **Frequency** | Uses per user per time | Weekly for engagement features |
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| **Depth** | % of feature capability used | 50%+ of core functionality |
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| **Retention** | Continued usage over time | 70%+ at 30 days |
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| **Satisfaction** | Feature-specific NPS/rating | NPS > 30, Rating > 4.0 |
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**Measurement Cadence:**
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- **Week 1**: Adoption and initial activation
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- **Week 4**: Retention and depth
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- **Week 8**: Long-term satisfaction and business impact
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---
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## Strategic Frameworks
|
||||
|
||||
### Product Vision Template
|
||||
|
||||
**Format:**
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||||
```
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FOR [target customer]
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WHO [statement of need or opportunity]
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THE [product name] IS A [product category]
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||||
THAT [key benefit, compelling reason to use]
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UNLIKE [primary competitive alternative]
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OUR PRODUCT [statement of primary differentiation]
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||||
```
|
||||
|
||||
**Example:**
|
||||
```
|
||||
FOR busy professionals
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||||
WHO need to stay informed without information overload
|
||||
Briefme IS A personalized news digest
|
||||
THAT delivers only relevant stories in 5 minutes
|
||||
UNLIKE traditional news apps that require active browsing
|
||||
OUR PRODUCT learns your interests and filters automatically
|
||||
```
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||||
|
||||
---
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||||
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||||
### Competitive Analysis Framework
|
||||
|
||||
| Dimension | Us | Competitor A | Competitor B |
|
||||
|-----------|----|--------------|--------------|
|
||||
| **Target User** | | | |
|
||||
| **Core Value Prop** | | | |
|
||||
| **Pricing** | | | |
|
||||
| **Key Features** | | | |
|
||||
| **Strengths** | | | |
|
||||
| **Weaknesses** | | | |
|
||||
| **Market Position** | | | |
|
||||
|
||||
**Strategic Questions:**
|
||||
1. Where do we have parity? (table stakes)
|
||||
2. Where do we differentiate? (competitive advantage)
|
||||
3. Where are we behind? (gaps to close or ignore)
|
||||
4. What can only we do? (unique capabilities)
|
||||
|
||||
---
|
||||
|
||||
### Go-to-Market Checklist
|
||||
|
||||
**Pre-Launch (4 weeks before):**
|
||||
- [ ] Success metrics defined and instrumented
|
||||
- [ ] Launch/rollback criteria established
|
||||
- [ ] Support documentation ready
|
||||
- [ ] Sales enablement materials complete
|
||||
- [ ] Marketing assets prepared
|
||||
- [ ] Beta feedback incorporated
|
||||
|
||||
**Launch Week:**
|
||||
- [ ] Staged rollout plan (1% → 10% → 50% → 100%)
|
||||
- [ ] Monitoring dashboards live
|
||||
- [ ] On-call rotation scheduled
|
||||
- [ ] Communications ready (in-app, email, blog)
|
||||
- [ ] Support team briefed
|
||||
|
||||
**Post-Launch (2 weeks after):**
|
||||
- [ ] Metrics review vs. targets
|
||||
- [ ] User feedback synthesized
|
||||
- [ ] Bug/issue triage complete
|
||||
- [ ] Iteration plan defined
|
||||
- [ ] Stakeholder update sent
|
||||
|
||||
---
|
||||
|
||||
## Framework Selection Guide
|
||||
|
||||
| Situation | Recommended Framework |
|
||||
|-----------|----------------------|
|
||||
| Quarterly roadmap planning | RICE + Portfolio Matrix |
|
||||
| Sprint-level prioritization | MoSCoW |
|
||||
| Quick feature comparison | ICE |
|
||||
| Understanding user satisfaction | Kano |
|
||||
| User research synthesis | JTBD + Opportunity Tree |
|
||||
| Feature experiment design | Hypothesis Template |
|
||||
| Success measurement | HEART + Feature Metrics |
|
||||
| Strategy communication | North Star + Vision |
|
||||
|
||||
---
|
||||
|
||||
*Last Updated: January 2025*
|
||||
Reference in New Issue
Block a user