Product Management Toolkit

When to Use

• Prioritizing feature backlog
• Writing product requirements
• Analyzing customer interviews
• Planning sprints and roadmaps
• Making data-driven product decisions

RICE Prioritization

Formula

Score = (Reach × Impact × Confidence) / Effort

Example

Value vs Effort Matrix

           Low Effort    High Effort

High       QUICK WINS    BIG BETS
Value      [Prioritize]  [Strategic]

Low        FILL-INS      TIME SINKS
Value      [Maybe]       [Avoid]

PRD Template

# Feature: [Name]

## Problem Statement
What problem are we solving? For whom?

## Success Metrics
- Primary: [Metric and target]
- Secondary: [Supporting metrics]

## User Stories
As a [user], I want [capability] so that [benefit].

## Requirements
### Must Have (P0)
- [Requirement 1]

### Should Have (P1)
- [Requirement 2]

### Out of Scope
- [Explicit exclusion]

## Design
[Link to designs or wireframes]

## Technical Approach
[High-level technical approach]

## Timeline
- Phase 1: [Scope] - [Date]
- Phase 2: [Scope] - [Date]

## Open Questions
- [Question 1]

Customer Interview Framework

Structure (35 min)

1. Context (5 min)
   • Role and responsibilities
   • Current workflow
   • Tools used
2. Problem Exploration (15 min)
   • Pain points
   • Frequency and impact
   • Current workarounds
3. Solution Validation (10 min)
   • Reaction to concepts
   • Value perception
   • Willingness to pay
4. Wrap-up (5 min)
   • Other thoughts
   • Referrals

Analysis Framework

• Pain points with severity (high/medium/low)
• Feature requests with priority
• Jobs to be done patterns
• Key quotes for stakeholder communication

Sprint Planning

Capacity Planning

Sprint Capacity = Team Size × Days × Velocity Factor

Example:
5 engineers × 10 days × 0.7 = 35 story points

Story Point Guidelines

MoSCoW Method

• Must Have: Critical for launch
• Should Have: Important but not critical
• Could Have: Nice to have
• Won't Have: Out of scope (this release)

Metrics Framework

North Star Metric

• What's the #1 value to users?
• Is it measurable and actionable?
• Does it predict business success?

Feature Success Metrics

• Adoption: % users using feature
• Frequency: Usage per user per week
• Retention: Continued usage over time
• Satisfaction: NPS/CSAT for feature

Best Practices

Writing PRDs

• Start with problem, not solution
• Include clear success metrics
• Explicitly state what's out of scope
• Use visuals (wireframes, flows)

Prioritization

• Mix quick wins with strategic bets
• Account for dependencies
• Buffer for unexpected work (20%)
• Revisit quarterly

Discovery

• Ask "why" 5 times
• Focus on past behavior, not intentions
• Look for emotional reactions
• Validate with data