opportunity-mapping

Map opportunities using Teresa Torres' Opportunity Solution Trees. Use when asked to identify opportunities, find product gaps, explore new areas, map the solution space, or connect business outcomes to customer needs and testable solutions.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "opportunity-mapping" with this command: npx skills add assimovt/productskills/assimovt-productskills-opportunity-mapping

Map opportunities by connecting business outcomes to customer needs to testable solutions. Teresa Torres' Opportunity Solution Trees (OSTs) prevent the two biggest PM mistakes: building solutions without clear problems, and chasing problems disconnected from business goals.

Opportunity Solution Tree Structure

Build the tree top-down, but fill it bottom-up with evidence:

Desired Outcome (business metric you're trying to move)
  |
  +-- Opportunity 1 (customer need/pain/desire)
  |     +-- Solution A
  |     |     +-- Experiment 1
  |     |     +-- Experiment 2
  |     +-- Solution B
  |           +-- Experiment 3
  |
  +-- Opportunity 2
        +-- Solution C
        +-- Solution D
              +-- Experiment 4

Level 1: Desired Outcome

One measurable business outcome. Not a feature, not a project — a metric.

  • "Increase 7-day activation rate from 23% to 40%"
  • NOT: "Improve onboarding" (not measurable)

Level 2: Opportunities

Customer needs, pain points, or desires that, if addressed, would move the outcome. These come from research — interviews, data, support tickets — not brainstorming.

Rules for good opportunities:

  • Framed as customer needs, not product features
  • "New users don't understand what to do first" (opportunity)
  • NOT "Add an onboarding wizard" (solution masquerading as opportunity)
  • Each opportunity is independent — addressing one doesn't depend on another

Level 3: Solutions

Multiple possible solutions for each opportunity. Generate at least 3 before evaluating. The goal is to explore the solution space, not commit to the first idea.

Level 4: Experiments

Small, fast tests to validate whether a solution addresses the opportunity. Experiments should answer: "Does this solution actually solve this opportunity?"

Building the Tree

  1. Start with the outcome. Align with your team or stakeholders on exactly one outcome to focus on.
  2. Map opportunities from research. Review interview notes, support tickets, analytics. Cluster evidence into distinct opportunities. Each opportunity needs evidence from 3+ sources.
  3. Generate solutions per opportunity. Brainstorm at least 3 solutions per opportunity. Include wild ideas — they often reveal assumptions.
  4. Design experiments per solution. What's the smallest test? Prototype, concierge, Wizard of Oz, fake door, A/B test.
  5. Prioritize which branch to explore. You can't test everything. Pick the opportunity with strongest evidence and the solution with lowest experiment cost.

Guidelines

  • CRITICAL: NEVER skip from outcome directly to solutions. The opportunity layer is where the insight lives.
  • ALWAYS frame opportunities as customer needs, not features. If it sounds like a feature, push back to the underlying need.
  • NEVER have only one solution per opportunity. If you can't think of 3 solutions, you haven't explored the space.
  • ALWAYS ground opportunities in evidence from research, not assumptions.
  • NEVER pursue more than 2-3 opportunities simultaneously. Focus beats breadth.
  • ALWAYS design experiments that could DISPROVE your solution, not just confirm it.

Built on Continuous Discovery Habits by Teresa Torres. Skills from productskills.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

prd-writing

No summary provided by upstream source.

Repository SourceNeeds Review
General

experiment-design

No summary provided by upstream source.

Repository SourceNeeds Review
General

bet-sizing

No summary provided by upstream source.

Repository SourceNeeds Review
General

strategy-doc

No summary provided by upstream source.

Repository SourceNeeds Review