Map an opportunity solution tree for continuous discovery

Stop Building Features. Start Solving Opportunities.

Product teams ship an average of 30-50 features per year, yet according to Pendo's 2023 State of Product Leadership report, 80% of features in the average SaaS product are rarely or never used. The problem isn't a lack of execution — it's a lack of structured connection between what customers need and what teams build. The opportunity solution tree is a framework that fixes this by creating an explicit, visual link from business outcomes to customer opportunities to solutions to experiments.

The Feature Factory Trap

When teams operate as "feature factories," they take customer requests at face value, prioritize by loudest voice or largest deal, and ship solutions without validating the underlying problem. The result is a bloated product where each feature was individually justified but collectively incoherent.

Teresa Torres, who popularized continuous discovery habits across hundreds of product teams, observed that the most effective teams don't just talk to customers — they systematically structure what they learn. An opportunity solution tree forces this structure by making four things explicit: what outcome are we driving, what customer opportunities could drive that outcome, what solutions could address those opportunities, and what experiments will tell us if we're right.

How the Opportunity Solution Tree Prompt Works

This prompt guides you through five phases. You start by defining a measurable outcome (not a feature, but a metric like "increase 30-day retention to 60%"). Then you map opportunities from real customer data, grouping raw observations into themed opportunity statements. Next, you brainstorm diverse solutions for each top opportunity — crucially, at least three per opportunity to avoid anchoring on the obvious choice. You then design lightweight experiments to test the riskiest assumption behind each solution. Finally, you visualize the entire tree to align your team.

When to Use It

• You're starting a new discovery cycle and need to organize disparate customer insights
• Your team is debating three different features and you need a shared framework for deciding
• A stakeholder wants to know why you're building X instead of Y — the tree is your answer
• You just completed a batch of customer interviews and need to synthesize findings into action
• Your roadmap feels disconnected from customer reality

Common Pitfalls

Starting with solutions instead of opportunities. If your tree starts with "build a dashboard" rather than "users struggle to understand their usage patterns," you've skipped the most important step. Opportunities must be framed as customer needs, not product features.

Not generating enough solution diversity. Teams that brainstorm only one solution per opportunity miss creative alternatives. Force yourself to generate at least three — the best solution is often the third or fourth idea, not the first.

Running experiments that take too long. The experiment step should take days, not months. If your experiment requires building a full feature, it's not an experiment — it's a bet. Look for faster signals: prototypes, fake doors, wizard-of-oz tests.

Sources

• Continuous Discovery Habits — Teresa Torres on building a weekly discovery practice
• 80% of SaaS Features Go Unused — Pendo's research on feature adoption rates
• Opportunity Solution Trees: A Visual Framework — The original framework explained