pmprompt/claude-plugin-product-management

opportunity-solution-trees

Use when asked to "opportunity solution tree", "OST", "Teresa Torres", "map customer opportunities to outcomes", "structure discovery around opportunities", or "compare solutions for a customer need".

First seen Feb 15, 2026

Installation

$ npx skills add pmprompt/claude-plugin-product-management --skill opportunity-solution-trees

Summary

  • Use when asked to "opportunity solution tree", "OST", "Teresa Torres", "map customer opportunities to outcomes", "structure discovery around opportunities", or "compare solutions for a customer need".
  • Helps product teams connect outcomes to customer opportunities and test solutions with Opportunity Solution Trees (created by Teresa Torres).

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from pmprompt/claude-plugin-product-management · top by installs.

npx skills add pmprompt/claude-plugin-product-management

Browse all from pmprompt/claude-plugin-product-management

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 49
License LICENSE
Default branch main
Open issues 2
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,406 B
  • docs SUMMARY.md 3,985 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 347 installs

SKILL.md

Opportunity Solution Trees

Domain Context

The Opportunity Solution Tree (Teresa Torres, Continuous Discovery Habits) is the backbone of modern product discovery. It prevents teams from jumping to solutions by forcing them to first map the opportunity space.

Structure (4 levels):

  1. Desired Outcome (top) — The measurable business or product outcome you're pursuing. Should be a single, clear metric (e.g., "increase 7-day retention to 40%"). This comes from your OKRs or product strategy.
  1. Opportunities (second level) — Customer needs, pain points, or desires discovered through research. Frame them from the customer's perspective: "I struggle to..." or "I wish I could..." Prioritize using Opportunity Score: Importance × (1 − Satisfaction) (Dan Olsen).
  1. Solutions (third level) — Possible ways to address each opportunity. Generate multiple solutions per opportunity — don't commit to the first idea. The Product Trio (PM + Designer + Engineer) should ideate together.
  1. Experiments (bottom) — Fast, cheap tests to validate whether a solution addresses the opportunity. Use assumption testing (Value, Usability, Viability, Feasibility).

Key principles:

  • One outcome at a time — don't try to solve everything
  • Opportunities, not features — never let customers design solutions
  • Compare and contrast — generate at least 3 solutions per opportunity
  • Discovery is not linear — loop back if experiments fail
  • Continuous, not periodic — update the tree weekly

Input Requirements

  • A desired outcome or business metric to improve
  • Customer research data (interviews, surveys, analytics, feedback)
  • Optionally: existing opportunities or solution ideas to organize

What It Is

Use the Opportunity Solution Tree (OST) to connect a business outcome to the customer opportunities that drive it, then compare solutions and tests. The tree forces you to separate needs from ideas and keeps discovery tied to delivery.

When to Use It

  • Structure discovery around customer opportunities
  • Tie customer needs to measurable outcomes
  • Compare multiple solutions for the same opportunity
  • Keep continuous discovery aligned with the roadmap
  • Create a shared view of priorities with stakeholders

When Not to Use It

  • You are not doing customer research
  • The solution is already decided
  • The work is a commodity requirement with no real options
  • You only need a quick one-off decision

Core Structure

  • Outcome: the business result you are responsible for achieving
  • Opportunities: unmet customer needs, pains, or desires
  • Solutions: multiple ideas that address one opportunity
  • Experiments: tests that validate the riskiest assumptions

Process

Follow this step-by-step process to build and use an Opportunity Solution Tree:

Step 1: Define the Desired Outcome

  • Confirm or help articulate a single, measurable outcome at the top of the tree
  • Make it specific (e.g., "increase 7-day retention to 40%" not "improve retention")
  • Tie it to your OKRs or product strategy

Step 2: Map Opportunities

  • From customer research, identify 3-7 customer opportunities (needs/pains/desires)
  • Frame each from the customer's perspective ("I struggle to...", "I wish I could...")
  • Group related opportunities into themes
  • Avoid solutions disguised as opportunities (e.g., "needs a dashboard" → "struggles to understand performance")

Step 3: Prioritize Opportunities

  • Use Opportunity Score (Importance × [1 − Satisfaction]) or qualitative assessment
  • Focus on the top 2-3 opportunities
  • Consider: impact on outcome, frequency, intensity of pain

Step 4: Generate Solutions

  • For each prioritized opportunity, brainstorm 3+ solutions
  • Include perspectives from PM, Designer, and Engineer (Product Trio)
  • Resist the "first idea" trap — compare and contrast before choosing

Step 5: Design Experiments

  • For the most promising solutions, suggest 1-2 fast experiments
  • Specify: hypothesis, method, metric, success threshold
  • Prefer experiments with "skin in the game" (Alberto Savoia) over opinion-based validation

Step 6: Visualize the Tree

  • Present the full OST in a clear hierarchical format
  • Use indentation, bullets, or a visual tool
  • Make it easy for stakeholders to scan and understand

Step 7: Iterate Weekly

  • Review the tree every week as you learn from interviews, analytics, experiments
  • Kill solutions that don't validate
  • Explore new branches as you discover new opportunities

Further Reading