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:
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
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
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:
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
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
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:
- Opportunity 1: Mobile-first users can't access product on the go
- Opportunity 2: Mobile web experience is broken/slow
- Opportunity 3: Competitors offer native mobile apps
Solutions for Opportunity 1 might include:
- Build native mobile app (high effort)
- Optimize mobile web (medium effort)
- Build progressive web app (PWA) (medium effort)
POC evaluation reveals: Optimize mobile web scores higher on feasibility + impact than building native app. Test mobile web improvements first.