Conversion Rate Calculator
What share of visitors actually buy?
Your numbers
Result
Conversion rate
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How this is calculated
Conversion rate is the ratio that determines whether traffic is worth paying for. This calculator also works out the revenue per session and how many extra sessions you need to hit a target, which is the version of the number that actually drives decisions.
- Conversion rate = orders ÷ sessions
- Revenue per session = (orders × average order value) ÷ sessions
- Orders at target rate = sessions × target conversion rate
- Additional revenue available = (orders at target − actual orders) × average order value
- Cost per order = (sessions × cost per session) ÷ orders
What to make of the number
A typical ecommerce store converts between 1.5% and 3%. On marketplace listings conversion can run far higher because intent is stronger. The practical use of the number is the gap to your target: closing a 1.6% to 2.2% gap on existing traffic is usually far cheaper than buying the equivalent extra sessions.
Frequently asked questions
What is a good ecommerce conversion rate?
Generally between 1.5% and 3% for a general store. Higher for stores with strong brand or high-intent traffic; lower for broad interest-based traffic. Compare against your own historical rate and your traffic mix rather than a published average.
Why is revenue per session more useful than conversion rate?
Because it combines conversion and order value into one figure you can compare directly against your cost per session. If revenue per session exceeds cost per session, the traffic is profitable before you even consider margin.
How much can conversion rate realistically improve?
Meaningfully, but not infinitely. Page speed, clearer shipping and returns information, better product photography and reviews typically produce the largest gains. Expect incremental improvement rather than a doubling.
Should I measure conversion by session or by user?
Sessions are the standard for ecommerce and are what analytics platforms report by default. Users are useful for understanding behaviour across multiple visits, especially with long consideration cycles.
Why did conversion rate fall after a traffic increase?
Almost always because the additional traffic is colder. As you broaden targeting, the audience is less likely to buy, so rate falls while total orders may still rise. Track absolute orders alongside the rate.