Conversion Rate Optimization Data Audit
Conduct a systematic data audit of your conversion funnel to identify drop-off points, statistical significance of tests, and data-driven recommendations for improving conversion rates.
Prompt Template
You are a CRO data analyst. Conduct a thorough conversion rate optimization data audit for my product. **Product Details:** - Product type: [e.g., B2B SaaS with free trial] - Current conversion rate: [e.g., 2.3% visitor-to-trial, 18% trial-to-paid] - Monthly traffic: [e.g., 45,000 unique visitors] - Analytics tools: [e.g., Google Analytics 4, Mixpanel, Hotjar] **Funnel Steps:** [List your funnel stages with approximate conversion rates, e.g.: 1. Landing page → Sign-up page: 12% 2. Sign-up page → Account created: 45% 3. Account created → Onboarding complete: 60% 4. Onboarding complete → First value moment: 35% 5. First value moment → Paid conversion: 52%] **Available Data:** [e.g., 6 months of GA4 data, heatmaps for top 5 pages, 3 completed A/B tests] Please provide: 1. **Funnel health scorecard** — Rate each step against industry benchmarks (green/yellow/red) 2. **Biggest leak identification** — Calculate where the most absolute conversions are lost 3. **Statistical analysis framework** — Sample size calculator for your traffic, minimum detectable effect, and test duration estimates 4. **Data quality checklist** — 15-point audit to verify tracking accuracy 5. **Segmentation analysis plan** — Key segments to break down (device, source, cohort, geography) 6. **Quick wins list** — 5 high-impact, low-effort fixes based on funnel shape 7. **Test prioritization matrix** — ICE-scored backlog of 10 A/B test ideas 8. **Reporting dashboard spec** — What metrics to track weekly, monthly, and quarterly
Example Output
# CRO Data Audit Report
1. Funnel Health Scorecard
| Step | Your Rate | Benchmark | Status | Gap |
|------|-----------|-----------|--------|-----|
| Landing → Sign-up | 12% | 8-15% | 🟢 Healthy | At median |
| Sign-up → Account | 45% | 50-65% | 🔴 Critical | -5 to -20pp |
| Account → Onboarding | 60% | 55-70% | 🟢 Healthy | At median |
| Onboarding → Value | 35% | 40-55% | 🟡 Needs work | -5 to -20pp |
| Value → Paid | 52% | 35-50% | 🟢 Strong | Above median |
2. Biggest Leak: Sign-up → Account Created
Impact calculation:
- 45,000 visitors × 12% = 5,400 reach sign-up page
- 5,400 × 45% = 2,430 create accounts
- If improved to benchmark 55%: 5,400 × 55% = 2,970 accounts
- **540 additional accounts/month** → cascading to ~100 additional paid conversions
- At $100/mo ARPU = **$10,000/mo revenue impact**
4. Data Quality Checklist
- [ ] GA4 events firing on all funnel pages (check with Tag Assistant)
- [ ] No duplicate event triggers (check event count vs. page views)
- [ ] Cross-domain tracking configured if funnel spans domains
- [ ] Bot traffic filtered (check for >5% sessions with 0s duration)
- [ ] UTM parameters preserved through redirect chains
...
7. Test Prioritization Matrix
| # | Test Idea | Impact | Confidence | Ease | ICE Score |
|---|-----------|--------|------------|------|----------|
| 1 | Simplify sign-up to email-only (remove name field) | 9 | 8 | 9 | 26 |
| 2 | Add social proof to sign-up page | 8 | 7 | 8 | 23 |
| 3 | Reduce onboarding from 5 to 3 steps | 8 | 6 | 5 | 19 |
Tips for Best Results
- 💡Always calculate absolute numbers, not just percentages — a 10% improvement on a 2% step matters less than 5% on a 50% step
- 💡Verify your tracking before analyzing — bad data leads to confident wrong decisions. Run a data quality audit first
- 💡Segment by device type first — mobile vs desktop conversion gaps are often the single biggest CRO opportunity
- 💡Don't run A/B tests with less than 1,000 conversions per variant — underpowered tests produce false positives
- 💡Focus on the step with the biggest absolute drop-off, not the lowest percentage — that's where revenue impact lives
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