Affiliate and Influencer Analytics AI Prompt

Analyze affiliate and influencer channel performance for this e-commerce business.

Affiliate data: {{affiliate_data}} (affiliate_id, clicks, orders, revenue, commission)
Influencer data: {{influencer_data}} (creator_id, platform, post_date, promo_code, orders, revenue)
Commission rates: {{commission_rates}}

1. Affiliate performance metrics:
   For each affiliate:
   - Clicks, orders, conversion rate, revenue
   - Commission paid and commission rate
   - Net revenue = Revenue - Commission
   - ROAS (net): Net Revenue / Commission
   - Average order value from this affiliate's referrals
   - New vs returning customers referred

2. Affiliate quality analysis:
   - Affiliates with high click volume but low conversion: traffic quality issue (incentivized or misaligned audience)
   - Affiliates with high CVR and high AOV: premium partners, worth higher commission rates
   - Coupon code affiliates vs content affiliates: which generate higher new customer rates?
   - Coupon affiliates often capture customers who would have bought anyway (low incrementality)

3. Influencer performance:
   For each influencer post:
   - Impressions, reach, clicks (if tracked), orders attributed (promo code)
   - Revenue, EMV (Earned Media Value)
   - Cost per acquisition from influencer: fee / orders
   - Compare CPA to paid social CPA as a benchmark

4. Influencer content effectiveness:
   - Which content formats drove the most orders? (Reel vs story vs feed post vs YouTube)
   - Which platforms performed best for this product category?
   - Timing: how quickly do influencer-driven orders arrive? (Typically 48-72 hours peak, then decay)

5. Commission structure optimization:
   - Are commission rates optimized per affiliate tier?
   - Which affiliates would respond to a higher commission and generate enough incremental revenue?
   - Are any affiliates receiving high commissions without driving incremental customers?

6. Recommendations:
   - Top 5 affiliates to invest more in (performance-based tiering)
   - Affiliates to pause or restructure (low quality, possible fraud signals)
   - Influencer categories to scale based on performance analysis

Return: affiliate performance table, quality analysis, influencer performance metrics, commission optimization, and investment recommendations.