Marketing Attribution Analysis Prompt
Analyze your marketing channel data to understand which touchpoints drive conversions and where to allocate budget.
Prompt Template
You are a marketing analytics expert. Analyze my marketing attribution data and provide actionable insights: Attribution model used: [first-touch / last-touch / linear / time-decay / data-driven] Analysis period: [date range] Total conversions: [number] Revenue tracked: $[amount] Channel data: [Paste your channel breakdown here — e.g.: - Organic Search: 450 conversions, $45,000 revenue, $12,000 cost - Paid Search: 280 conversions, $56,000 revenue, $28,000 cost - Email: 190 conversions, $38,000 revenue, $2,000 cost - Social Media: 85 conversions, $8,500 revenue, $15,000 cost - Direct: 120 conversions, $24,000 revenue, $0 cost] Provide: 1. **Channel performance ranking** — by ROI, CPA, and revenue 2. **Budget reallocation recommendation** — where to shift spend 3. **Underperforming channels** — cut, test, or fix? 4. **Attribution model limitations** — what this model misses 5. **Quick wins** — immediate changes to improve performance 6. **3-month experiment plan** — what to test next
Example Output
Channel Performance Analysis
ROI Ranking:
1. Email: 1,900% ROI ($38K revenue / $2K cost) ⭐ Underinvested
2. Organic Search: 275% ROI ($45K / $12K) — strong, needs content investment
3. Direct: ∞ ROI — no paid cost (but includes brand investment)
4. Paid Search: 100% ROI ($56K / $28K) — profitable but expensive
5. Social Media: -43% ROI ($8.5K / $15K) 🚨 Losing money
Budget Reallocation Recommendation:
- Cut social budget by 50% → Save $7,500/month
- Reinvest $5K into email (automation, list growth)
- Reinvest $2.5K into content/SEO
**Email is massively underinvested:** $2K producing $38K — scaling to $5K could yield $75-95K at similar conversion rates.
3-Month Experiment Plan:
- Month 1: A/B test social creative (video vs. static) before cutting
- Month 2: Launch email welcome sequence to new subscribers
- Month 3: Test branded paid search vs. pure organic
Tips for Best Results
- 💡Include actual numbers — even rough estimates produce much more useful recommendations than percentages alone
- 💡Ask it to explain the limitations of your attribution model so you understand what data you might be missing
- 💡Run this quarterly so you can spot trends, not just snapshots
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