opportunity-solution-tree

What problem does it solve? Product teams often jump straight to building features without understanding which customer problems are worth solving. This Skill structures product discovery using Teresa Torres' Opportunity Solution Tree framework, connecting a measurable outcome to customer opportunities, candidate solutions, and validation experiments. ## Core Features & Use Cases - Outcome Definition: Clarifies a single, measurable desired outcome (e.g., raising 7-day retention to 40%) as the root of the tree. - Opportunity Prioritization: Extracts 3-7 customer opportunities from research data and ranks them using opportunity scoring (importance x (1 - satisfaction)). - Solution & Experiment Design: Generates multiple solutions per opportunity from product, design, and engineering perspectives, then defines hypothesis-driven experiments with metrics and success thresholds. - Use Case: A product team with interview notes and survey data wants to decide what to build next quarter. The Skill organizes their findings into a visual tree linking the retention goal to top pain points, three solution options each, and fast validation tests. ## Quick Start Ask the AI to build an opportunity solution tree for your target metric using your customer research notes as input.