Attribution Overlap Analysis

Attribution overlap occurs when multiple platforms claim 100% credit for the same sale. Example: Customer clicks Meta ad → Clicks Google ad → Converts. Meta claims the sale (7-day click attribution). Google claims the sale (30-day click attribution). Both platforms report the sale in their dashboards. Result: You think you made 2 sales but only made 1. Your reported ROAS is inflated. Why it happens: Platforms use last-click attribution (each claims to be "last click"), Different attribution windows (longer windows capture more conversions), and Cross-device tracking (user clicks Meta on mobile, Google on desktop). How to detect overlap: Compare sum of platform conversions to actual Shopify orders, Analyze customer journey data (see multi-platform touchpoints), and Use UTM tracking (identify which platform was truly last click). Typical overlap rates: Meta + Google: 15-30% overlap, Meta + TikTok: 10-20% overlap, and Google + Bing: 5-10% overlap. Impact on reporting: If Meta reports 100 conversions and Google reports 80, but 20 overlap, you actually had 160 conversions, not 180. Your true ROAS is 11% lower than platform-reported ROAS. Solutions: Use deduplication logic (credit to last-click platform only), Implement multi-touch attribution (split credit), and Report blended ROAS (total revenue ÷ total spend). Tools: Causality Engine (automated overlap detection), Northbeam (journey tracking), and Manual analysis (export platform data, match order IDs).