Ecommerce Conversion Rate (ECR) is the share of visits that end with a purchase — a specific case of overall conversion rate. It compresses product–market fit, UX, pricing, trust, and traffic quality into one number. Define your denominator and keep it consistent: most teams use sessions; some use unique visitors for cohort analysis—just don’t mix them in the same report.
How to calculate Ecommerce Conversion Rate
Formula (sessions-based):
ECR (%) = Orders ÷ Sessions × 100
Mini-example: 1,200 orders and 60,000 sessions → 1,200 ÷ 60,000 × 100 = 2.0%
| Channel | Sessions | Orders | ECR |
|---|---|---|---|
| 10,000 | 400 | 4.0% | |
| Paid Search | 30,000 | 450 | 1.5% |
| Social | 20,000 | 350 | 1.75% |
Interpretation: email converts best; paid search brings volume but needs funnel work across the conversion funnel.
Why it matters
- Revenue engine: Pair ECR with Average Order Value to get Revenue per Session. Lift either lever depending on constraints.
- Prioritization signal: A sagging ECR points to checkout friction or misaligned traffic; validate against step-rates like checkout conversion rate.
- Channel quality: Read ECR by channel alongside your attribution model to avoid false positives.
Practical nuances & pitfalls
- Definition drift: Decide whether “orders” = completed payment or shipped, document it, and stick to it.
- Data hygiene: Exclude internal traffic, bots, test orders, and cancelled CODs to avoid inflated rates (see bounce rate patterns on key landings).
- Micro vs. macro: Track add-to-cart, checkout start, and payment success before they tank headline ECR (tie-in to conversion funnel).
Optimization checklist (short)
Tighten value proposition above the fold, speed up PDP → cart, simplify forms, fix failed payments first, surface trust (reviews, guarantees), then run clean A/B tests. Measure ECR deltas, not vibes.