Data Discrepancy

A data discrepancy is the gap between what GA4 reports and what another system — Shopify, Stripe, your email platform, Search Console — shows for what looks like the same thing. It's almost never a bug. The tools count differently, define terms differently, and handle consent and bots differently, so their numbers were never going to match exactly.

Why it matters

Discrepancies erode trust in the data, which is the opposite of what analytics are for. A small business owner sees GA4 reporting 40 sales and Stripe reporting 47, and concludes the analytics are broken — then stops looking at them. The real lesson is that each tool measures from a different vantage point, and the gap is usually explainable rather than alarming.

A concrete example

Say GA4 shows 12% fewer purchases than your store's own dashboard. The likely culprits: visitors who declined cookies and were never tracked (see consent mode), checkout happening on a separate domain without cross-domain tracking, ad blockers, and GA4 sampling on large date ranges. None of these is an error — they're four different reasons the same purchase might not reach GA4.

The common misreading

The mistake is expecting two tools to agree to the unit and treating any gap as failure. They won't, and it isn't. What matters is whether the discrepancy is stable. A steady 10% gap is just a known offset you can mentally adjust for. A gap that suddenly widens is the real signal — that's when something in your tracking actually changed.