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Define Opportunity Tree

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SKILL.md
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<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->

name: define-opportunity-tree description: Creates an opportunity solution tree mapping desired outcomes to opportunities and potential solutions. Use for outcome-driven product discovery, prioritization, or communicating product strategy. phase: define version: "2.0.0" updated: 2026-01-26 license: Apache-2.0 metadata: category: problem-framing frameworks: [triple-diamond, lean-startup, design-thinking] author: product-on-purpose

Opportunity Solution Tree

An Opportunity Solution Tree (OST) is a visual framework for product discovery that connects business outcomes to customer opportunities and potential solutions. Developed by Teresa Torres, it prevents the common trap of jumping straight to solutions by ensuring every feature idea traces back to a customer need and measurable outcome.

When to Use

  • During continuous product discovery to organize learning
  • When prioritizing what opportunities to pursue
  • To communicate product strategy to stakeholders
  • When you have too many feature ideas and need structure
  • After user research to connect insights to action
  • When aligning team on what outcomes matter most

Instructions

When asked to create an opportunity solution tree, follow these steps:

  1. Define the Desired Outcome Start at the top with a clear, measurable business or product outcome. This should be something you can influence through product changes. Express it quantitatively when possible (e.g., "Increase 30-day retention from 40% to 55%").

  2. Identify Opportunity Areas Branch out to 3-5 opportunity areas—places where customer needs or pain points could be addressed. Opportunities are not solutions; they're customer problems, needs, or desires. Phrase them from the customer's perspective.

  3. Add Supporting Evidence For each opportunity, note the evidence that supports it: user research quotes, behavioral data, support tickets, or market trends. Strong opportunities have multiple evidence sources.

  4. Brainstorm Solutions For each opportunity, generate 2-4 potential solutions. Don't self-censor at this stage. Solutions can range from quick experiments to major features. Keep them specific enough to evaluate.

  5. Define Assumption Tests For each promising solution, identify the riskiest assumption and design a lightweight experiment to test it. Good tests validate whether the solution will actually address the opportunity.

  6. Prioritize the Tree Not all branches are equal. Mark which opportunity and solution you'll pursue first based on potential impact, confidence, and effort. The tree is a living document—you'll iterate as you learn.

  7. Visualize the Structure Create a tree diagram showing the hierarchy: outcome at top, opportunities below, solutions beneath each opportunity, and experiments at the leaves.

Output Format

Use the template in references/TEMPLATE.md to structure the output.

Quality Checklist

Before finalizing, verify:

  • Outcome is measurable and within product team's influence
  • Opportunities are customer-centric (needs/problems, not features)
  • Each opportunity has supporting evidence documented
  • Multiple solutions exist per opportunity (not jumping to one)
  • Assumptions are explicit and experiments designed
  • Prioritization is clear (which branch to explore first)

Examples

See references/EXAMPLE.md for a completed example.

Source

git clone https://github.com/product-on-purpose/pm-skills/blob/main/skills/define-opportunity-tree/SKILL.mdView on GitHub

Overview

An Opportunity Solution Tree (OST) is a visual framework for product discovery that connects business outcomes to customer opportunities and potential solutions. It helps teams avoid jumping to features by ensuring every idea ties to a measurable outcome and a real user need.

How This Skill Works

Begin with a clearly measurable outcome at the top. For each opportunity, collect supporting evidence from user research, behavior data, or tickets, then generate 2-4 concrete solutions and define a lightweight experiment to test the riskiest assumption. Prioritize branches and visualize the structure from outcome to opportunities to solutions and experiments.

When to Use It

  • During continuous product discovery to organize learning
  • When prioritizing which opportunities to pursue
  • To communicate product strategy to stakeholders
  • When you have many feature ideas and need structure
  • After user research to connect insights to action

Quick Start

  1. Step 1: Define the Desired Outcome
  2. Step 2: Identify Opportunities and Evidence
  3. Step 3: Brainstorm Solutions, Tests, and Prioritize

Best Practices

  • Define a measurable outcome at the top and keep it in scope
  • Ensure opportunities are customer-centric and evidence-based
  • Document 2-4 diverse solutions per opportunity
  • Explicitly define tests for the riskiest assumptions
  • Treat the tree as a living document and iterate as you learn

Example Use Cases

  • SaaS app aims to increase activation by clarifying onboarding; opportunities include guided onboarding, contextual tips; solutions: guided tour, in-app checklist, progressive reveal; tests: onboarding length and copy experiments.
  • E-commerce site seeks higher checkout completion; opportunities to reduce cart friction and improve trust signals; solutions: guest checkout, autofill, trust badges; tests: checkout funnel tweaks and A/B tests.
  • Mobile app targets 15% lift in 30-day retention; opportunities: better onboarding, personalized tips; solutions: personalized onboarding flow, in-app nudges, rewards; tests: cohort-based retention measurement.
  • B2B product prioritizes feature adoption; opportunities: in-product guidance, integration readiness; solutions: feature tours, API sandbox, targeted emails; tests: usage metrics after tours.
  • Content platform wants longer session times; opportunities: improved content discovery, recommendations; solutions: recommendation engine, topic hubs, enhanced search tips; tests: session duration after changes.

Frequently Asked Questions

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