Count conversions
Count each session with at least one completed purchase once. Track sign-ups and other goals separately.
[ glossary — commerce ]
A plain-English guide to ecommerce conversion rate for store owners who want more of their traffic to become buyers.
( the formula )
Count each session with at least one completed purchase once. Track sign-ups and other goals separately.
Use all eligible store sessions in the same reporting period. Apply the same bot and internal-traffic filters each time.
Divide purchasing sessions by total sessions and multiply by 100. Keep session-based and user-based reports separate.
Track trends against changes to marketing, product, and store experience.
( the levers )
Check whether slow product or checkout pages coincide with customers leaving.
Show authentic reviews, clear policies and recognizable payment options.
Clear product pages and a simple path to buy reduce confusion.
Explain total costs early, remove unnecessary fields and investigate payment errors.
( faq )
Divide sessions with at least one completed purchase by total eligible sessions, then multiply by 100. For example, 50 purchasing sessions out of 1,000 sessions gives 5%. A session with multiple purchases still counts once. Check whether your analytics report uses sessions, users or orders before comparing it.
There is no universal good rate. Compare your own baseline and segment results by device, traffic source, market and new or returning customers. Product price, purchase frequency and seasonality also affect the result.
Slow load times, confusing navigation, high prices with low trust, intrusive design, weak product pages, and a long or complicated checkout reduce conversions.
Use funnel data and customer feedback to identify where people stop. Test clearer product information, delivery costs, navigation or checkout changes, and measure whether they help.
Yes. We optimize store performance, UX, and checkout, and we run audits that identify the highest-impact conversion fixes.
It depends on traffic volume, the size of the effect and normal variation. Set a measurement plan before making changes and allow enough data to separate a useful result from noise. An improvement is not guaranteed.