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Documentation Index

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Build a visual framework connecting a desired outcome to customer opportunities, solutions, and validation experiments.

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Tools Required

This skill runs using CORE memory only. No integrations required.

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Step 1: Define the Desired Outcome

Confirm or help articulate a single, measurable outcome at the top of the tree. This should be a specific business or product metric you’re pursuing (e.g., “increase 7-day retention to 40%”). This comes from your OKRs or product strategy. Ask: “What’s the one metric or outcome we’re trying to achieve? Be specific.”

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Step 2: Map Opportunities

From customer research, identify 3-7 customer opportunities (needs, pain points, desires). Frame each from the customer’s perspective: “I struggle to…” or “I wish I could…” These are problems worth solving, not features. Don’t let customers propose solutions—extract the underlying needs.

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Step 3: Prioritize Opportunities

Use Opportunity Score to rank opportunities: 
Opportunity Score = Importance × (1 − Satisfaction)
  • Importance: How important is this to customers? (0-1 scale)
  • Satisfaction: How satisfied are they with current solutions? (0-1 scale)
Focus on the top 2-3 opportunities.

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Step 4: Generate Solutions

For each prioritized opportunity, brainstorm 3+ distinct solutions. Include perspectives from Product, Design, and Engineering. Don’t commit to the first idea—compare and contrast before selecting.

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Step 5: Design Experiments

For the most promising solutions, design 1-2 fast, cheap validation tests. Specify:
  • Hypothesis: What are we testing?
  • Method: How will we test it?
  • Metric: What will we measure?
  • Success threshold: What result validates the hypothesis?
Prefer experiments with “skin in the game” (pre-orders, willingness to pay) over opinion-based validation.

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Step 6: Visualize the Tree

Present the full OST in a hierarchical format, showing the flow from outcome → opportunities → solutions → experiments.

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Output Format

Opportunity Solution Tree — [Desired Outcome] 🎯 Desired Outcome [Single, measurable metric or goal] 🎪 Opportunities (Ranked by Opportunity Score)
OpportunityImportance (0-1)Satisfaction (0-1)Opportunity ScorePriority
[Opportunity 1][0-1][0-1][Score]High/Medium/Low
[Opportunity 2][0-1][0-1][Score]High/Medium/Low
[Opportunity 3][0-1][0-1][Score]High/Medium/Low
💡 Top Solutions by Opportunity Opportunity 1: [Description]
  • Solution A: [Description]
  • Solution B: [Description]
  • Solution C: [Description]
  • Recommended: [Solution] because [rationale]
Opportunity 2: [Description] [Same format] 🧪 Validation Experiments For Opportunity 1 / Solution [X]:
  • Hypothesis: [What we believe to be true]
  • Method: [How we’ll test it]
  • Metric: [What we’ll measure]
  • Success threshold: [Result that validates]
  • Timeline: [Days to run]
For Opportunity 2 / Solution [Y]: [Same format] Next Steps
  1. Run experiments for top 2 solutions
  2. Kill/iterate based on results
  3. Update tree weekly as you learn

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Edge Cases

  • Too many opportunities: Prioritize ruthlessly. Focus on top 2-3; defer others.
  • Unclear satisfaction data: Use qualitative assessment or conduct quick survey.
  • Multiple solutions equally strong: Run parallel experiments; let data decide.
  • No research data: Conduct 5-10 customer interviews before mapping tree.
  • Tree becomes too large: Focus on one desired outcome at a time. Create separate trees for other outcomes.