reaperinvest Conversion Funnel Analysis
When to Use This Skill
Use this skill when you need to:
- Map your customer journey from awareness to purchase
- Identify where the biggest drop-offs occur in your funnel
- Prioritize optimization efforts for maximum conversion impact
- Benchmark your funnel performance against industry standards
DO NOT use this skill for A/B test design, ad campaign optimization, or CRM pipeline management. This is for analyzing and diagnosing funnel performance.
Core Principle
FIX THE BIGGEST LEAK FIRST — A 10% IMPROVEMENT AT THE WORST DROP-OFF POINT BEATS A 50% IMPROVEMENT AT A STEP THAT ALREADY CONVERTS WELL.
Phase 1: Brief
Required Inputs
| Input | What to Ask | Default |
|---|---|---|
| Funnel type | "What funnel? (website, e-commerce checkout, SaaS signup, sales pipeline)" | Website lead funnel |
| Funnel stages | "List every step from first visit to final conversion." | Must be provided |
| Current data | "Do you have numbers for each stage? (visitors, leads, trials, purchases)" | Must be provided or estimated |
| Time period | "What time period does the data cover?" | Last 30 days |
| Goal | "What conversion rate are you targeting for the full funnel?" | Industry benchmark |
| Known issues | "Any stages you already suspect are underperforming?" | Unknown |
GATE: Confirm brief and data before proceeding.
Phase 2: Map
Funnel Visualization
Build a stage-by-stage funnel with:
- Volume at each stage (absolute numbers)
- Conversion rate between each stage
- Drop-off rate at each stage (inverse of conversion)
- Cumulative conversion from top to bottom
Benchmark Comparison
Provide relevant benchmarks per stage:
| Funnel Type | Stage | Typical Conversion |
|---|---|---|
| Website lead gen | Visit → Lead | 2-5% |
| SaaS | Signup → Trial active | 40-60% |
| SaaS | Trial → Paid | 15-25% |
| E-commerce | Visit → Add to cart | 8-12% |
| E-commerce | Cart → Purchase | 40-65% |
GATE: Present the funnel map and confirm accuracy before analyzing.
Phase 3: Analyze
Deliverables
1. Funnel Performance Report
- Stage-by-stage conversion and drop-off rates
- Comparison to benchmarks: above, at, or below industry
- The "biggest leak" — the stage with the highest absolute opportunity
2. Drop-Off Diagnosis For each underperforming stage, diagnose likely causes:
- Visit → Lead: Weak CTA, unclear value proposition, slow load time
- Lead → Qualified: Poor targeting, mismatched expectations, no nurture
- Qualified → Close: Pricing friction, lack of urgency, competitor strength
- Provide 3-5 hypotheses per underperforming stage
3. Optimization Priority Matrix
| Stage | Drop-Off Rate | Potential Uplift | Effort | Priority |
|---|---|---|---|---|
| Cart → Checkout | 65% | High | Low | 1 |
| Visit → Signup | 97% | Medium | Medium | 2 |
4. Action Plan
- Top 3 fixes ranked by impact-to-effort ratio
- Specific recommendations for each fix
- Measurement plan: how to verify the fix worked
Phase 4: Polish
Monitoring Dashboard Spec
Recommend a simple funnel dashboard with:
- Weekly stage-by-stage conversion rates
- Trend lines to spot degradation early
- Alert thresholds for each stage
Review Cadence
- Weekly: quick funnel health check
- Monthly: full analysis with segment overlays
- Quarterly: funnel redesign review — are the stages still correct?
Example 1: SaaS Free Trial Funnel
Stages: Website Visit → Signup → Trial Active → Feature Activated → Paid Key finding: 70% drop-off between Signup and Trial Active — onboarding is broken Top fix: Reduce signup-to-value time with guided onboarding flow
Example 2: E-commerce Purchase Funnel
Stages: Visit → Product View → Add to Cart → Checkout → Purchase Key finding: 55% cart abandonment — above benchmark of 35% Top fix: Add trust badges, simplify checkout, implement cart abandonment email
Anti-Patterns
- Optimizing the top when the bottom leaks — doubling traffic to a broken checkout page doubles frustration, not revenue. Fix the bottom first.
- Ignoring absolute numbers — a 50% conversion rate on 10 visitors is 5 customers. Sometimes the problem is volume, not rate.
- Single-metric obsession — overall conversion rate masks stage-specific problems. Always break down by stage.
- Benchmarking without context — a 1% website conversion rate might be excellent for luxury goods and terrible for a free tool. Use relevant benchmarks.
- Analyzing without segmenting — mobile vs. desktop, new vs. returning, and channel-specific funnels often tell very different stories.
Recovery
- No funnel data available: Help define the stages and set up basic tracking. Provide a 30-day data collection plan before analysis.
- Funnel stages unclear: Map the customer journey from their perspective, not the internal process. Ask "What does the customer DO at each step?"
- Everything looks bad: Prioritize ruthlessly. Pick the one stage with the highest absolute impact and start there.
- User wants to redesign the whole funnel: Optimize the existing funnel first. Redesign only after quick wins are exhausted.