E-commerce Traffic Source Analysis AI Prompt

Analyze traffic sources and their contribution to e-commerce revenue.

Analytics data: {{analytics_data}} (sessions, source/medium, channel, orders, revenue)
Time period: {{period}}
Marketing spend by channel: {{spend_data}}

1. Revenue by channel:
   - Revenue attributed by channel: organic search, paid search, direct, email, paid social, organic social, referral, affiliate
   - Each channel: sessions, orders, conversion rate, AOV, revenue
   - Revenue per session by channel (best efficiency metric for cross-channel comparison)

2. Channel conversion rate comparison:
   - Email typically converts at 2-5%: highest-converting channel
   - Organic search: 1-3%
   - Paid search (branded): 3-8%
   - Paid search (non-branded): 1-2%
   - Social (paid): 0.5-1.5%
   - Direct: 2-4%
   - How does each channel compare to these benchmarks?

3. Paid channel ROI:
   - For each paid channel: spend, attributed revenue, ROAS
   - True ROI (gross profit basis): (Revenue x Gross Margin - Spend) / Spend
   - Which paid channels have ROAS above the threshold to justify continued investment?

4. Organic vs paid balance:
   - Organic revenue as % of total: is the business too dependent on paid traffic?
   - Paid traffic shut-off risk: if all paid channels stopped tomorrow, what would revenue be?
   - Cost of revenue: what % of revenue is consumed by marketing spend?

5. New customer vs returning customer by channel:
   - Which channels drive new customers vs returning customers?
   - Channels bringing primarily returning customers: potential attribution issue (assisting role) or wasted prospecting spend

6. Traffic quality signals:
   - Bounce rate by channel
   - Pages per session by channel
   - Session duration by channel
   - Low-quality channels (high bounce, low engagement): review targeting and landing page alignment

Return: revenue by channel table, conversion rate benchmark comparison, paid channel ROI, organic vs paid balance, new vs returning mix, and traffic quality signals.