Opportunity Solution Tree
Structure messy stakeholder asks into an outcome, evidence-backed opportunities, solution options, and testable experiments before you build retention or feature work.
Overview
Opportunity Solution Tree is an agent skill most often used in Validate (also Idea, Build) that turns stakeholder problems into outcomes, evidence-backed opportunities, solution options, and experiments.
Install
npx skills add https://github.com/deanpeters/product-manager-skills --skill opportunity-solution-treeWhat is this skill?
- Walks from stakeholder request to a measurable desired outcome with explicit success metrics
- Generates multiple opportunities with evidence hooks (usage data, exit interviews, support signals)
- Branches into solution hypotheses with paired A/B or experiment framing
- Forces explicit opportunity selection before solution ideation—reduces solution-first product thrash
- Example flow covers retention/churn: outcome → opportunities → solutions → experiment design
- Example flow generates 3 opportunities and 3 solutions per selected branch
- Retention example targets reducing monthly churn from 15% to 8% within 6 months
Adoption & trust: 1.3k installs on skills.sh; 5k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You have a vague product mandate and scattered evidence but no ordered path from outcome to the one opportunity and experiment worth building next.
Who is it for?
Solo founders and indie builders doing product discovery on retention, onboarding, or feature bets when stakeholders hand you problems instead of outcomes.
Skip if: Teams that already have a locked PRD with approved scope and no need to reframe opportunities or run discovery experiments.
When should I use this skill?
Stakeholder or user problem is stated as a feature ask, churn spike, or vague “we need X” and you need outcome-first discovery before specs.
What do I get? / Deliverables
You leave with a chosen opportunity, solution hypotheses, and experiment framing ready to refine into a spec or implementation plan.
- Desired outcome with success metric
- Ranked opportunities with evidence
- Selected solution hypotheses and experiment outlines
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Opportunity Solution Trees are the canonical shelf in Validate because they turn vague requests into scoped outcomes and prioritized bets before full build commitment. Scope subphase fits OST’s job: narrow what to solve, pick one opportunity branch, and define solution experiments instead of jumping to features.
Where it fits
Synthesize exit interviews and usage stats into three competing opportunities before you commit to a retention theme.
Translate “customers churn after 3 months” into an 15%→8% outcome and pick whether habit, features, or support is the real lever.
Re-check that the sprint’s email-digest solution still maps to the selected opportunity and planned A/B experiment.
How it compares
Use instead of jumping from churn metrics straight to a feature backlog without an outcome–opportunity tree.
Common Questions / FAQ
Who is opportunity-solution-tree for?
Solo and indie builders who wear the PM hat and need structured discovery when stakeholders ask for features without clear outcomes or evidence.
When should I use opportunity-solution-tree?
In Validate when scoping what to build next from churn or growth signals; in Idea when framing research into testable opportunities; in Build PM when reconciling a spec with the original outcome before sprinting.
Is opportunity-solution-tree safe to install?
It is procedural product methodology with no special system access; review the Security Audits panel on this Prism page before installing any skill from the repo.
SKILL.md
READMESKILL.md - Opportunity Solution Tree
# Opportunity Solution Tree Examples ### Example 1: Good OST (Retention Use Case) **Step 0 - Context:** User shares stakeholder request: "Customers churn after 3 months. We need better retention features." **Q1 Response:** "Customer retention — Reduce churn from 15% to 8% within 6 months" **Agent extracts outcome:** - **Desired Outcome:** Reduce monthly churn rate from 15% to 8% - **Why it matters:** High churn indicates value delivery problem; retention drives LTV --- **Agent generates 3 opportunities:** 1. **Opportunity 1: Users don't integrate product into daily workflow** — "Sign up, use once or twice, forget about it; not a habit" - Evidence: Usage data shows 60% of churned users had <5 logins/month 2. **Opportunity 2: Product missing critical features** — "Users switch to competitors because we lack [X feature]" - Evidence: Exit interviews mention "missing advanced reporting" 40% of the time 3. **Opportunity 3: Poor customer support** — "Users encounter issues, don't get help, give up" - Evidence: Support ticket volume from churned users 2x higher than retained users **User selects:** "Opportunity 1 — Users don't integrate into daily workflow" --- **Agent generates 3 solutions:** 1. **Solution 1: Email digest (daily summary)** — "Send daily email with key updates, prompts to return to product" - Hypothesis: Reminders drive re-engagement - Experiment: A/B test daily digest vs. no digest, measure DAU/MAU ratio 2. **Solution 2: Slack/Teams integration** — "Bring product notifications into where users already are" - Hypothesis: Meeting users in their workflow increases usage - Experiment: Offer to 100 users, measure engagement lift vs. control 3. **Solution 3: In-app triggers (progress prompts)** — "Show 'You're 80% to your goal' prompts when users log in" - Hypothesis: Progress feedback creates habit loop - Experiment: A/B test triggers vs. no triggers, measure retention at 30/60/90 days **User:** "Move to POC selection" --- **Agent evaluates:** | Solution | Feasibility | Impact | Market Fit | Total | Rationale | |----------|-------------|--------|------------|-------|-----------| | Solution 1: Email digest | 5 | 3 | 4 | 12 | Easy to build, moderate impact (email fatigue risk), good market fit | | Solution 2: Slack integration | 3 | 5 | 5 | 13 | Medium effort, high impact (meets users where they are), strong market fit | | Solution 3: In-app triggers | 4 | 4 | 4 | 12 | Moderate effort, good impact, good market fit | **Recommended POC:** Solution 2 (Slack/Teams integration) **Why this POC:** - Highest total score (13) - Strong market fit (users already live in Slack/Teams) - High impact (notifications in existing workflow drive re-engagement) - Medium feasibility (3-4 weeks to build basic integration) **Experiment:** - **Type:** A/B test - **Participants:** 200 users (100 with Slack integration, 100 control) - **Duration:** 30 days - **Success criteria:** Slack group shows 20%+ higher DAU/MAU vs. control **Why this works:** - Clear hypothesis tied to retention metric - Testable in 30 days - High confidence in market fit (users requested this) --- ### Example 2: Bad OST (Solution-First Thinking) **Q1 Response:** "We need to build a mobile app" **Why this fails:** - "Build a mobile app" is a solution, not an outcome - No measurable business metric - Jumps straight to solution without exploring problems **Fix:** - **Agent pushes back:** "A mobile app is a solution. What's the desired outcome? (e.g., Increase engagement, reach mobile-first users, drive feature adoption?)" - **User clarifies:** "Increase daily active users from mobile-first customer segment" - **Agent extracts:** Desired Outcome = Increase mobile DAU from 5% to 20% of total users **Now proceed with opportunity generation:** 1. **Opportunity 1: Mobile-first users can't access product on the go** 2. **Opportunity 2: Mobile web experience is broken/slow** 3. **Opportunity 3: Competitors offer native mobile app