Short answer: Many online stores convert somewhere around 1% to 3% of sessions, but treat that as a commonly quoted rough range, not a target. A good conversion rate is one that beats your own baseline for the same traffic mix. Judge it by channel and device, because email, branded search and cold social traffic convert at very different rates, and a blended number hides that.
Key takeaways
- The often quoted 1% to 3% range is a rough sense check. Your traffic mix, device split, price point and category decide where you should sit.
- A single benchmark misleads because the same rate can be weak for a store fed by email and strong for one fed by cold social ads.
- Judge your rate against your own last 90 days, split by channel and device. A blended rate can fall while every channel holds steady.
- Revenue per session is the fuller measure, because a lower rate with bigger orders can earn more from every visit.
A benchmark from someone else's store tells you very little about yours. A shop selling €25 phone cases to returning customers and a shop selling €900 sofas to first-time visitors from Instagram should not expect the same number.
First, the definition. Ecommerce conversion rate is completed purchases divided by sessions in the same period, multiplied by 100. Count orders only, not add-to-carts or sign-ups, exclude internal and bot traffic, and keep the same tool and definition every time you compare.
What conversion rate do most online stores get?
Most online stores are said to convert somewhere around 1% to 3% of sessions into orders. That is the range quoted most often, and it is useful only as a sense check: if you are far below 1% across all traffic, something is likely broken, and if you are well above 3%, much of your traffic probably comes from loyal or high-intent visitors.
It is not a statistic from our clients, and it is not a target. Published averages mix stores of every size, category and traffic source, and often use different definitions: some count users rather than sessions, some quietly include add-to-carts.
Imagine two stores that both convert at 2%. The first gets most of its traffic from email and returning customers, who already know and trust the brand. For that store, 2% is weak. The second gets most of its traffic from cold social ads shown to people who have never heard of it. For that store, 2% could be very good. Same number, opposite verdicts.
Why does a single benchmark mislead?
Because conversion rate depends on who arrives and how ready they are to buy, not only on how good the website is. Traffic source, device and price point each pull the number up or down, so two well run stores can sit far apart.
Traffic source
Where a visitor comes from tells you how close they are to buying. Someone clicking your email already knows you; someone scrolling past an Instagram ad was doing something else a second ago. The table shows direction, not numbers, because absolute rates depend on your store.
| Traffic source | Typical relative conversion | Why |
|---|---|---|
| Email and SMS to existing subscribers | Higher | People already know the brand, and many have bought before. |
| Branded search and direct | Higher | The visitor is looking for you specifically and is often close to buying. |
| Non-brand search and Shopping | Middle | Intent varies by query: "buy wide fit trail shoes size 44" converts better than "best running shoes". |
| Paid social prospecting (cold audiences) | Lower | People were not looking to buy and are meeting the brand for the first time. |
So your overall rate largely reflects your traffic mix. Start a prospecting campaign and it will usually drop, even if nothing on the site changed.
Device
Mobile usually converts lower than desktop, even though it often brings most sessions. People browse on phones and buy later on a laptop, and small screens make slow pages and long forms more painful. A lower mobile rate is normal; one far below desktop for the same channel usually points to a usability problem.
Price point and category
Cheap, familiar products are easy decisions. Furniture, high-end electronics or custom products need research and comparison, so people visit several times before buying and the rate per session is typically lower than for consumables. That is not a failure. The buying journey is just longer.
How do you judge whether your conversion rate is good?
Judge your conversion rate against your own baseline, not someone else's average. Pull the last 90 days of sessions and purchases, split by channel and by device, and calculate a rate for each segment. Your rate is good when each segment holds or beats its own baseline, and a segment is worth attention when it sits well below comparable ones.
Ninety days smooths out a single promotion or slow week. If your business is very seasonal, compare against the same period last year too.
A worked example
Here is an example store with simple numbers. Its blended conversion rate is 1.6%, which sounds unremarkable. Split by channel, the picture changes.
The blended number
50,000 sessions and 800 orders in 90 days, so a conversion rate of 1.6%.
Split by channel
Email: 5,000 sessions, 200 orders, 4.0%. Organic search: 12,000 sessions, 240 orders, 2.0%. Paid search: 10,000 sessions, 150 orders, 1.5%. Direct: 3,000 sessions, 70 orders, about 2.3%. Paid social: 20,000 sessions, 140 orders, 0.7%.
What it shows
Paid social brings 40% of sessions but under 18% of orders. Email brings 10% of sessions and a quarter of orders. The 1.6% average describes none of these channels.
Now imagine this store raises its paid social budget next quarter, and social sessions grow from 20,000 to 30,000 at the same 0.7% rate. That adds 70 orders. Everything else stays the same. The store now has 60,000 sessions and 870 orders, so the blended rate drops to about 1.45%.
Nothing got worse. Every channel converts as before, and the store sold more. Anyone watching only the blended number would think conversion had fallen and start changing the site. This is the most common misreading we see.
Then do the same split by device, and combine both for your biggest channels: paid social on mobile, paid search on desktop. Often one segment, such as mobile visitors from paid search, sits far below the others. That is the honest answer to "is our rate good?": most segments are fine, and one specific segment is not.
Build your conversion rate baseline in GA4 in about 20 minutes
- In GA4, open Explore, start a blank free-form exploration and set the last 90 days.
- Add the dimensions Session default channel group and Device category, and the metrics Sessions, Ecommerce purchases and Purchase revenue.
- Put channel group in rows and device category in columns, or export the table to a spreadsheet.
- Calculate purchases divided by sessions, and revenue divided by sessions, for each row.
- Highlight the segments with the most sessions and the lowest rate. Those are where to look first.
GA4 and Shopify count sessions differently, so their rates will not match. If GA4 purchases look far off your Shopify orders, check consent mode and tracking first. Our marketing analytics services often start exactly there.
Conversion rate optimisation that starts with your own data
We segment your traffic by channel and device, find the pages and steps where specific visitors drop off, and fix the obvious issues before we test anything. If the real problem is traffic quality or margin, we will say so.
See our conversion rate optimisation servicesIs conversion rate the right number to judge on its own?
Not quite. Conversion rate counts orders, not money, so revenue per session (revenue divided by sessions) is the fuller measure. Take two example stores: Store A converts at 2.5% with a €40 average order, so it earns €1.00 per session. Store B converts at 1.2% with a €120 average order, so it earns €1.44 per session. Store B has the "worse" rate and the better business.
Likewise, a low rate is not always a site problem. If a channel sends visitors who were never likely to buy, the fix sits in the channel, and if constant discounts hold the rate up, check margin per order before you celebrate. If you are weighing whether to buy more traffic or fix the site first, are Google Ads worth it covers the traffic side.
Frequently asked questions
The same rough 1% to 3% range applies, because Shopify does not change who visits your store. What matters is how your rate compares with your own baseline by channel and device. Shopify's reports measure conversion by sessions, so compare like with like.
It can be, but check what is behind it. A rate that high usually means much of your traffic comes from email, branded search or returning customers. That is healthy for a mature brand, but it can also mean you are not reaching many new customers.
Usually because the traffic mix changed. If you added more cold traffic, such as prospecting ads, sessions grow faster than orders and the blended rate falls. Check each channel against its own baseline; if those are stable, nothing on the site got worse.
Sessions, in most cases. A user-based rate is always higher because one person can visit several times before buying, and most quoted ranges are session-based. Whichever you choose, use it every time.
Usually the basics in the weakest segment: page speed on mobile, clear product pages, delivery and returns costs shown early, and a short checkout. That is a separate question from judging your rate, and we touch on it in what a digital marketing agency does for email and conversion rate.
What to do next
Stop comparing your store with an average and start comparing it with itself.
- Build your 90-day baseline by channel and device using the steps above, with revenue per session next to conversion rate.
- Find the biggest segment that sits well below comparable ones, and decide whether it is a site problem or a traffic problem.
- If you want a second pair of eyes, ask for a free written conversion audit. We send it within 48 hours, with the segments we would look at first, including "this is a traffic problem, not a site problem" if that is what the data shows.