Systematically analyzes a product funnel to identify where users drop off and why, with prioritized fix recommendations.
Analyze the following product funnel data and identify the biggest opportunities. **Funnel data:** [paste your funnel steps with user counts, e.g.: Step 1: Landing page — 10,000 users Step 2: Signup started — 3,200 users Step 3: Signup completed — 1,800 users Step 4: Onboarding — 1,200 users Step 5: First value action — 450 users Step 6: Day 7 retention — 280 users] **Analysis:** 1. **Conversion rates** per step (calculate and display as table) 2. **Biggest drop-off**: Which step loses the most users? Quantify the opportunity. 3. **Root cause hypotheses** (3 per major drop-off): - UX friction (too many steps, confusing UI) - Value proposition gap (user doesn't see benefit yet) - Technical issues (slow load, errors, compatibility) 4. **Benchmarks**: How do these rates compare to industry standards for [product type]? 5. **Prioritized fixes** (Impact × Effort matrix): - Quick wins (high impact, low effort) - Strategic investments (high impact, high effort) - Deprioritize (low impact) 6. **Experiments to run** (3 A/B test hypotheses with expected lift) **Context**: [B2B SaaS / B2C app / E-commerce / Marketplace] **Current activation metric**: [define what "activated" means for your product]
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