The Feature Prioritization template helps product teams prioritize features using the Impact-Effort matrix. This format ensures teams focus on high-impact work that can be delivered efficiently, maximizing value delivery.
This template is essential for product managers, product teams, and anyone making decisions about what to build next. It provides a structured way to evaluate and compare features objectively.
The Impact-Effort Matrix
The format categorizes features into four quadrants:
- High Impact, Low Effort: Quick wins—do these first
- High Impact, High Effort: Major projects—plan carefully
- Low Impact, Low Effort: Fill-ins—do when you have time
- Low Impact, High Effort: Avoid—not worth the effort
This matrix helps teams make data-driven prioritization decisions and avoid the common trap of building low-value features.
How to facilitate
Prioritization Best Practices
- Define impact criteria: What does "high impact" mean? (Revenue, users, strategic value?)
- Estimate effort realistically: Include design, development, testing, and deployment
- Involve stakeholders: Get input from engineering, design, and business
- Revisit regularly: Priorities change as you learn more
- Consider dependencies: Some features must come before others
Facilitation Tips
- Use voting or dot voting to assess impact and effort
- Discuss edge cases—features on the border between quadrants
- Consider user needs, business value, and technical constraints
- Document reasoning for future reference
- Create a prioritized backlog from the matrix
When to use this template
When to Use Feature Prioritization
- Product planning: Deciding what to build next
- Roadmap planning: Quarterly or annual planning
- Backlog refinement: Prioritizing user stories
- Resource allocation: Deciding where to invest engineering time
Example Features
Common prioritization scenarios:
- Quick wins: Bug fixes, small UX improvements
- Major projects: New features, platform migrations
- Fill-ins: Nice-to-have features, polish
- Avoid: Features with unclear value, vanity metrics
