product-manager-toolkit

$27

Quick Start

For Feature Prioritization

# Create sample data file

python scripts/rice_prioritizer.py sample

# Run prioritization with team capacity

python scripts/rice_prioritizer.py sample_features.csv --capacity 15

For Interview Analysis

python scripts/customer_interview_analyzer.py interview_transcript.txt

For PRD Creation

• Choose template from references/prd_templates.md

• Fill sections based on discovery work

• Review with engineering for feasibility

• Version control in project management tool

Core Workflows

Feature Prioritization Process

Gather → Score → Analyze → Plan → Validate → Execute

#### Step 1: Gather Feature Requests

• Customer feedback (support tickets, interviews)

• Sales requests (CRM pipeline blockers)

• Technical debt (engineering input)

• Strategic initiatives (leadership goals)

#### Step 2: Score with RICE

# Input: CSV with features

python scripts/rice_prioritizer.py features.csv --capacity 20

See references/frameworks.md for RICE formula and scoring guidelines.

#### Step 3: Analyze Portfolio

Review the tool output for:

• Quick wins vs big bets distribution

• Effort concentration (avoid all XL projects)

• Strategic alignment gaps

#### Step 4: Generate Roadmap

• Quarterly capacity allocation

• Dependency identification

• Stakeholder communication plan

#### Step 5: Validate Results

Before finalizing the roadmap:

• Compare top priorities against strategic goals

• Run sensitivity analysis (what if estimates are wrong by 2x?)

• Review with key stakeholders for blind spots

• Check for missing dependencies between features

• Validate effort estimates with engineering

#### Step 6: Execute and Iterate

• Share roadmap with team

• Track actual vs estimated effort

• Revisit priorities quarterly

• Update RICE inputs based on learnings

Customer Discovery Process

Plan → Recruit → Interview → Analyze → Synthesize → Validate

#### Step 1: Plan Research

• Define research questions

• Identify target segments

• Create interview script (see references/frameworks.md)

#### Step 2: Recruit Participants

• 5-8 interviews per segment

• Mix of power users and churned users

• Incentivize appropriately

#### Step 3: Conduct Interviews

• Use semi-structured format

• Focus on problems, not solutions

• Record with permission

• Take minimal notes during interview

#### Step 4: Analyze Insights

python scripts/customer_interview_analyzer.py transcript.txt

Extracts:

• Pain points with severity

• Feature requests with priority

• Jobs to be done patterns

• Sentiment and key themes

• Notable quotes

#### Step 5: Synthesize Findings

• Group similar pain points across interviews

• Identify patterns (3+ mentions = pattern)

• Map to opportunity areas using Opportunity Solution Tree

• Prioritize opportunities by frequency and severity

#### Step 6: Validate Solutions

Before building:

• Create solution hypotheses (see references/frameworks.md)

• Test with low-fidelity prototypes

• Measure actual behavior vs stated preference

• Iterate based on feedback

• Document learnings for future research

PRD Development Process

Scope → Draft → Review → Refine → Approve → Track

#### Step 1: Choose Template

Select from references/prd_templates.md:

Template

Use Case

Timeline

Standard PRD

Complex features, cross-team

6-8 weeks

One-Page PRD

Simple features, single team

2-4 weeks

Feature Brief

Exploration phase

1 week

Agile Epic

Sprint-based delivery

Ongoing

#### Step 2: Draft Content

• Lead with problem statement

• Define success metrics upfront

• Explicitly state out-of-scope items

• Include wireframes or mockups

#### Step 3: Review Cycle

• Engineering: feasibility and effort

• Design: user experience gaps

• Sales: market validation

• Support: operational impact

#### Step 4: Refine Based on Feedback

• Address technical constraints

• Adjust scope to fit timeline

• Document trade-off decisions

#### Step 5: Approval and Kickoff

• Stakeholder sign-off

• Sprint planning integration

• Communication to broader team

#### Step 6: Track Execution

After launch:

• Compare actual metrics vs targets

• Conduct user feedback sessions

• Document what worked and what didn't

• Update estimation accuracy data

• Share learnings with team

Tools Reference

RICE Prioritizer

Advanced RICE framework implementation with portfolio analysis.

Features:

• RICE score calculation with configurable weights

• Portfolio balance analysis (quick wins vs big bets)

• Quarterly roadmap generation based on capacity

• Multiple output formats (text, JSON, CSV)

CSV Input Format:

name,reach,impact,confidence,effort,description

User Dashboard Redesign,5000,high,high,l,Complete redesign

Mobile Push Notifications,10000,massive,medium,m,Add push support

Dark Mode,8000,medium,high,s,Dark theme option

Commands:

# Create sample data

python scripts/rice_prioritizer.py sample

# Run with default capacity (10 person-months)

python scripts/rice_prioritizer.py features.csv

# Custom capacity

python scripts/rice_prioritizer.py features.csv --capacity 20

# JSON output for integration

python scripts/rice_prioritizer.py features.csv --output json

# CSV output for spreadsheets

python scripts/rice_prioritizer.py features.csv --output csv

Customer Interview Analyzer

NLP-based interview analysis for extracting actionable insights.

Capabilities:

• Pain point extraction with severity assessment

• Feature request identification and classification

• Jobs-to-be-done pattern recognition

• Sentiment analysis per section

• Theme and quote extraction

• Competitor mention detection

Commands:

# Analyze interview transcript

python scripts/customer_interview_analyzer.py interview.txt

# JSON output for aggregation

python scripts/customer_interview_analyzer.py interview.txt json

Input/Output Examples

→ See references/input-output-examples.md for details

Integration Points

Compatible tools and platforms:

Category

Platforms

Analytics

Amplitude, Mixpanel, Google Analytics

Roadmapping

ProductBoard, Aha!, Roadmunk, Productplan

Design

Figma, Sketch, Miro

Development

Jira, Linear, GitHub, Asana

Research

Dovetail, UserVoice, Pendo, Maze

Communication

Slack, Notion, Confluence

JSON export enables integration with most tools:

# Export for Jira import

python scripts/rice_prioritizer.py features.csv --output json > priorities.json

# Export for dashboard

python scripts/customer_interview_analyzer.py interview.txt json > insights.json

Common Pitfalls to Avoid

Pitfall

Description

Prevention

Solution-First

Jumping to features before understanding problems

Start every PRD with problem statement

Analysis Paralysis

Over-researching without shipping

Set time-boxes for research phases

Feature Factory

Shipping features without measuring impact

Define success metrics before building

Ignoring Tech Debt

Not allocating time for platform health

Reserve 20% capacity for maintenance

Stakeholder Surprise

Not communicating early and often

Weekly async updates, monthly demos

Metric Theater

Optimizing vanity metrics over real value

Tie metrics to user value delivered

Best Practices

Writing Great PRDs:

• Start with the problem, not the solution

• Include clear success metrics upfront

• Explicitly state what's out of scope

• Use visuals (wireframes, flows, diagrams)

• Keep technical details in appendix

• Version control all changes

Effective Prioritization:

• Mix quick wins with strategic bets

• Consider opportunity cost of delays

• Account for dependencies between features

• Buffer 20% for unexpected work

• Revisit priorities quarterly

• Communicate decisions with context

Customer Discovery:

• Ask "why" five times to find root cause

• Focus on past behavior, not future intentions

• Avoid leading questions ("Wouldn't you love...")

• Interview in the user's natural environment

• Watch for emotional reactions (pain = opportunity)

• Validate qualitative with quantitative data

Quick Reference

# Prioritization

python scripts/rice_prioritizer.py features.csv --capacity 15

# Interview Analysis

python scripts/customer_interview_analyzer.py interview.txt

# Generate sample data

python scripts/rice_prioritizer.py sample

# JSON outputs

python scripts/rice_prioritizer.py features.csv --output json

python scripts/customer_interview_analyzer.py interview.txt json

Reference Documents

• references/prd_templates.md - PRD templates for different contexts

• references/frameworks.md - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)