TL;DR:
- Set up your opportunity solution tree in 2 hours with clear outcome mapping
- Run weekly 90-minute sessions to iterate and validate assumptions
- Track assumption tests, not feature delivery, for real discovery progress
- Use simple tools (Miro, Figma) to avoid complexity overhead
- Focus on one opportunity branch per sprint to maintain momentum
Table of contents
- Context and why it matters in 2025
- Step-by-step playbook
- Templates and examples
- Metrics to track
- Common mistakes and how to fix them
- FAQ
- Further reading
- Why CraftUp helps
Context and why it matters in 2025
Most product teams build features in isolation, losing sight of the customer problems they're solving. The opportunity solution tree framework creates a visual map connecting your desired outcomes to specific customer opportunities and potential solutions. This matters more in 2025 because teams ship faster but often in the wrong direction.
Success means your team can trace every feature back to a validated customer opportunity and measure progress toward meaningful outcomes. When done right, you'll spend less time debating what to build and more time testing assumptions with real users.
The framework works because it forces you to separate problems (opportunities) from solutions, making it easier to pivot when initial ideas don't work. Teams using this approach report 40% fewer failed features and clearer alignment between product and business goals.
Step-by-step playbook
Step 1: Define your desired outcome
Goal: Establish the business metric your team will move in the next quarter.
Actions:
- Choose one specific, measurable outcome (not an output like "ship 5 features")
- Write it as: "Increase [metric] from [current] to [target] by [date]"
- Get stakeholder agreement on this single focus
Example: "Increase monthly active users from 2,400 to 3,600 by March 31st" instead of "Improve user engagement."
Pitfall: Choosing multiple outcomes dilutes focus and creates competing priorities.
Definition of done: Your outcome is written, measurable, and approved by your team and key stakeholders.
Step 2: Map customer opportunities
Goal: Identify specific customer problems that, if solved, would drive your desired outcome.
Actions:
- Review recent customer feedback, support tickets, and user research
- List 8-12 opportunity statements starting with "Customers struggle to..."
- Group similar opportunities and prioritize by impact and evidence strength
- Plot opportunities as branches under your outcome
Example: For increasing MAUs, opportunities might include "Customers struggle to understand the value after signup" or "Customers struggle to complete their first meaningful action."
Pitfall: Writing opportunities as solutions in disguise ("Customers need a better onboarding flow" is a solution, not an opportunity).
Definition of done: You have 6-8 distinct opportunity branches with clear customer problem statements.
Step 3: Generate solution ideas
Goal: Brainstorm multiple ways to address each high-priority opportunity.
Actions:
- For your top 3 opportunities, generate 4-6 solution ideas each
- Include a mix of quick wins and bigger bets
- Avoid evaluating ideas during generation (do that separately)
- Add solution branches under each opportunity
Example: For "Customers struggle to see value after signup," solutions might include: welcome email series, interactive product tour, simplified first-use flow, or peer success stories.
Pitfall: Falling in love with your first solution idea and not exploring alternatives.
Definition of done: Each priority opportunity has multiple solution options mapped as sub-branches.
Step 4: Add assumption statements
Goal: Make your beliefs about opportunities and solutions explicit and testable.
Actions:
- For each opportunity, write: "We believe [customer segment] experiences [problem] because [hypothesis]"
- For each solution, write: "We believe [solution] will [impact] because [assumption]"
- Mark assumptions as "high," "medium," or "low" risk based on uncertainty
- Color-code or tag assumptions by confidence level
Example: "We believe new users abandon after signup because they don't understand what to do first" (opportunity assumption) and "We believe an interactive tutorial will increase activation because users need guided practice" (solution assumption).
Pitfall: Writing assumptions that are too vague to test or validate.
Definition of done: Every opportunity and solution has explicit, testable assumptions tagged by risk level.
Step 5: Plan assumption tests
Goal: Design quick experiments to validate or invalidate your riskiest assumptions.
Actions:
- Pick 2-3 highest-risk assumptions from your tree
- Design tests that can run in 1-2 weeks maximum
- Choose methods: customer interviews, surveys, prototype tests, or data analysis
- Define what evidence would prove or disprove each assumption
Example: Test "users don't understand what to do first" with 8 customer interviews asking about their signup experience, looking for confusion patterns.
Pitfall: Designing tests that take months or require building the full solution.
Definition of done: You have 2-3 assumption tests planned with clear success criteria and timelines.
Step 6: Establish weekly review cadence
Goal: Create a sustainable rhythm for updating your tree based on new evidence.
Actions:
- Schedule 90-minute weekly sessions with your core team (PM, designer, engineer)
- First 30 minutes: review test results and update assumptions
- Next 45 minutes: plan upcoming tests and adjust priorities
- Final 15 minutes: update the visual tree and document decisions
- Rotate who facilitates to maintain engagement
Example: Every Wednesday 2-3:30pm, review last week's customer interviews, update opportunity priorities, and plan next week's prototype test.
Pitfall: Making sessions too long or including too many people, leading to meeting fatigue.
Definition of done: Weekly sessions are scheduled with clear agendas and rotating facilitation.
Templates and examples
Here's a simple opportunity solution tree template you can copy into Miro, Figma, or any visual tool:
DESIRED OUTCOME
└── Increase [specific metric] from [X] to [Y] by [date]
OPPORTUNITIES (Customer Problems)
├── Opportunity 1: Customers struggle to [specific problem]
│ ├── Assumption: We believe [segment] experiences this because [hypothesis]
│ ├── Evidence: [customer quotes, data, observations]
│ └── Test: [planned experiment to validate]
│
├── Opportunity 2: Customers struggle to [specific problem]
│ ├── Solutions:
│ │ ├── Solution A: [specific approach]
│ │ │ ├── Assumption: We believe this will work because [hypothesis]
│ │ │ └── Test: [experiment plan]
│ │ └── Solution B: [alternative approach]
│ └── [continue pattern]
│
└── Opportunity 3: [continue pattern]
WEEKLY REVIEW CHECKLIST
□ Review completed assumption tests
□ Update evidence and confidence levels
□ Adjust opportunity priorities
□ Plan next week's experiments
□ Update visual tree
□ Document key decisions
Metrics to track
Assumption test velocity
Formula: Number of assumption tests completed per week Instrumentation: Track in a simple spreadsheet or project management tool Example range: 2-4 tests per week for a team of 3-4 people
Evidence quality score
Formula: Percentage of opportunities backed by direct customer evidence (interviews, observations, data) Instrumentation: Manual review during weekly sessions Example range: 70-90% of opportunities should have supporting evidence
Opportunity validation rate
Formula: (Validated opportunities / Total opportunities tested) × 100 Instrumentation: Track validation outcomes in your tree documentation Example range: 40-60% validation rate indicates good assumption quality
Solution pivot frequency
Formula: Number of times you change solution direction per opportunity Instrumentation: Document solution changes during weekly reviews Example range: 1-3 pivots per opportunity before finding viable solutions
Time to first customer contact
Formula: Days from identifying opportunity to first customer conversation Instrumentation: Track dates in your opportunity documentation Example range: 3-7 days maximum to maintain discovery momentum
Tree update consistency
Formula: Percentage of weeks where tree is updated with new evidence Instrumentation: Simple calendar tracking of update sessions Example range: 80-100% consistency needed for effective continuous discovery
Common mistakes and how to fix them
• Building the tree once and never updating it - Schedule non-negotiable weekly review sessions and rotate facilitation to maintain engagement.
• Making opportunities too broad or vague - Write specific problem statements that start with "Customers struggle to..." and include observable behaviors.
• Jumping straight to solutions without understanding opportunities - Force yourself to identify and validate 3-5 customer problems before brainstorming any solutions.
• Creating assumption tests that take weeks to complete - Design experiments that can run in 5-7 days maximum, focusing on learning over perfection.
• Including too many people in weekly reviews - Keep core sessions to 3-4 people maximum, then share updates with broader stakeholders separately.
• Treating the tree as a roadmap or project plan - Remember this is a discovery tool for learning, not a delivery schedule for shipping features.
• Avoiding customer contact and relying only on internal assumptions - Aim for direct customer interaction within one week of identifying any new opportunity.
• Making the visual tree too complex or detailed - Keep it simple enough that anyone can understand the logic in 2-3 minutes.
FAQ
Q: How long does it take to set up an opportunity solution tree initially? A: About 2 hours for the first version. Spend 30 minutes defining your outcome, 60 minutes mapping opportunities from existing research, and 30 minutes adding initial solution ideas. Don't aim for perfection.
Q: What tools work best for maintaining an opportunity solution tree? A: Miro and Figma work well for visual collaboration. Avoid complex tools like specialized software that add overhead. A simple shared whiteboard tool that your whole team can edit works perfectly.
Q: How many opportunities should we focus on at once? A: Start with 6-8 total opportunities but only actively test 1-2 at a time. This gives you enough options without spreading your testing efforts too thin across too many areas.
Q: Can opportunity solution tree work for B2B products with long sales cycles? A: Yes, but adjust your testing methods. Use customer interviews, prototype feedback, and pilot programs instead of usage analytics. The framework structure remains the same regardless of business model.
Q: How do we handle stakeholders who want to skip discovery and jump to building? A: Show them the tree connecting their desired business outcomes to customer opportunities. Frame assumption testing as risk reduction that prevents building the wrong features, not as delays to shipping.
Further reading
- Teresa Torres' Continuous Discovery Habits - The original framework creator's detailed guide with advanced techniques and real case studies.
- Product Discovery at Scale by Gibson Biddle - Practical examples from Netflix showing how large teams use discovery frameworks effectively.
- Jobs to be Done Framework by Clayton Christensen - Complementary approach to understanding customer opportunities through the lens of functional jobs.
Why CraftUp helps
Mastering continuous discovery requires consistent practice with real frameworks, not just reading about them.
- 5-minute daily lessons for busy people who need to learn discovery methods while shipping products
- AI-powered, up-to-date workflows PMs need including Customer Interviews With AI: Scripts to Reduce Bias and How to Choose the Right North Star Metric for Your Product
- Mobile-first, practical exercises to apply immediately including opportunity mapping templates and assumption test builders
Start free on CraftUp to build a consistent product habit at https://craftuplearn.com.
