Increase ecommerce conversion rate: what the data says

In short

An online store's conversion rate is the share of visits (sessions) that end in a purchase. In Littledata's benchmark of 436 Shopify stores for July to October 2026, the median was 1.4% and the top 20% of stores converted above 2.7%; uptain's 2025 report puts small and mid-size German stores at 2.01% on average for Q1 2023 to Q1 2025. To increase the conversion rate, first find the funnel step where most buyers drop off, then work on the levers that the data supports: page speed, checkout costs and friction, delivery and return information, express payments, product page content, and search and filters.

All figures in this guide were checked on 3 November 2026 on the primary source: Shopify and Google documentation, web.dev, Baymard Institute and the benchmark publishers. Benchmarks come from software vendors that measure their own customers' stores, so they are a rough orientation, not an official statistic. Mobile-specific problems are covered in a separate article, Why an online store does not sell on mobile.

What conversion rate is and how to calculate it

The basic formula is simple: conversion rate = sessions with a purchase ÷ all sessions × 100. A store with 20,000 sessions and 300 sessions ending in an order has a conversion rate of 1.5%. The details matter, though, because Shopify and Google Analytics 4 count different things.

The numbers in Shopify and GA4 rarely match. One reason is cookie consent: according to Google's documentation on consent mode, in the basic implementation Google tags are blocked until the visitor consents, and GA4 has no modelled data for visitors who decline. In the advanced implementation, tags send cookieless pings and GA4 fills the gaps with modelling. For stores in the EU with a cookie banner, it is better to compare a store with its own history in one tool than to mix numbers from Shopify and GA4.

Conversion rate is one of three factors of revenue: sessions × conversion rate × average order value. In a model store with 20,000 sessions a month, a conversion rate of 1.5% and an average order of €60, revenue is €18,000. At 1.8%, with the same traffic and order value, it is €21,600. That is why improving conversion is often cheaper than buying more traffic.

Average conversion rate for online stores: benchmarks

No official, freely available statistic for the average conversion rate of online stores in Germany, Austria, Switzerland or Central Europe could be found on 3 November 2026. The Statista figure often quoted in German articles (from Handelsverband Österreich, 2022) sits behind a login. The following three benchmarks are open and explain how they measure:

The averages differ by industry. In Littledata's data for July to October 2026, the median was 2.5% for beauty and skincare, 2.4% for health and supplements, 2.3% for food and beverage, and 1.0% for both fashion and home and furniture. In uptain's German data, tobacco and e-cigarettes had the highest rate at 7.30%, and products bought out of habit converted best. uptain also reports that conversion regularly rises in the fourth quarter because of Black Friday and Christmas.

Device results differ too, and the sources disagree. In Littledata's sample for July to October 2026, the median was 1.5% on mobile and 1.4% on desktop. In uptain's German data for Q1 2023 to Q1 2025, desktop converted 0.61 percentage points better than mobile. A store's own split by device in Shopify or GA4 says more than any average.

What this means in practice: a store at 0.5% is in the bottom fifth of Littledata's sample and probably has a fixable problem. A store at 3% is in the top fifth, and further gains will come from smaller steps. The vendors behind these benchmarks sell tracking or cart-recovery software and measure their own customers; the samples are not representative of all stores.

Where buyers drop off: the conversion funnel in Shopify Analytics

A single conversion rate does not say where the problem is. Shopify's Conversion rate breakdown report shows the funnel in four steps, and Littledata publishes medians for the same steps from GA4 data for July to October 2026:

The report can be set as an open funnel (steps in any order) or a closed funnel (only sessions that complete the steps in order). In Google Analytics 4, the Purchase journey report under Reports > Life cycle > Monetization shows the steps session_start, view_item, add_to_cart, begin_checkout and purchase. It counts users, not sessions, and only works when the ecommerce events are set up.

The step with the largest gap compared with the store's own history or with the medians above is where to start. Looking at the funnel by device and by traffic source often shows that the problem sits in one segment only.

Page speed and Core Web Vitals

Google measures loading, responsiveness and visual stability with three Core Web Vitals. A page passes when the 75th percentile of page loads, measured separately for mobile and desktop, meets the "good" threshold. The thresholds as published on web.dev in November 2026:

Values between the two columns are rated "needs improvement". Shopify Analytics has its own Web performance reports for LCP, INP and CLS, so a Shopify store can see these values without extra tools.

The clearest evidence that speed affects sales comes from a controlled test. In a case study published on web.dev in March 2021, Vodafone ran an A/B test on a landing page: the version with a 31% better LCP brought 8% more sales. That is one company and one page, not a guarantee, but it was a real experiment rather than a correlation. The most common causes of a slow store and the mobile specifics are covered in Why an online store does not sell on mobile.

Checkout friction: what Baymard's data shows

According to Baymard Institute, the average documented cart abandonment rate is 70.22%, calculated from 50 studies (list last updated on 22 September 2025). Not all of it can be fixed: in Baymard's survey of US online shoppers, 42% had abandoned a cart because they were only browsing. Among the remaining reasons, the most common ones point to specific levers:

Baymard's testing also shows that an ideal checkout can be as short as 12 to 14 form elements, or 7 to 8 if only the form fields are counted, while the average US checkout shows 23.48 form elements by default. According to Baymard, the average large online store can gain a 35.26% increase in conversion rate through better checkout design. That figure comes from tests of large stores in the US and the EU, so a small store should read it as a sign of potential, not a forecast.

Shipping, returns and trust information

Extra costs, slow delivery and returns are among the most common reasons for leaving, and the information that answers them often appears too late. In Baymard's 2026 product page benchmark (updated on 18 March 2026), 67% of sites did not provide a total order cost estimate near the buy section, and 44% did not display or link to the returns policy from the main product page content.

What the customer should see before the checkout, ideally next to the Add to cart button:

• Shipping cost for the customer's country, and the free-shipping threshold if there is one, also in the cart with the amount still missing.
• Delivery date as an estimate ("delivered by Thursday") rather than only "2 to 4 working days".
• Returns in one sentence, with a link to the full policy.
• Reviews on the product page, and a reply to negative ones: according to Baymard, 89% of sites do not respond to negative user reviews.
• Contact details: phone number or email and the company details, easy to find from every page.

Payment methods: express checkout, Shop Pay and PayPal

In Baymard's survey, 9% of US shoppers had abandoned a purchase because there were not enough payment methods, and 19% because they did not trust the site with their card details. Express payments address both: the customer confirms a payment with details already saved, without typing a card number.

According to Shopify's help centre, Shopify shows accelerated checkout buttons for Shop Pay and for other providers that offer them, including Apple Pay, Google Pay, Amazon Pay and PayPal. They appear in an Express Checkout section at the start of the checkout, ordered dynamically to show the fastest option for each customer, and some can also appear on the product page. Shopify warns that hiding them might have a negative impact on conversion rates.

Shopify's own marketing page says Shop Pay brings "as much as 50% better conversion compared to guest checkout" and outpaces other accelerated checkouts by at least 10%. According to Shopify, these figures come from an external study completed with an unnamed global consulting firm in April 2023. They are the vendor's claims, not independent research, and the result in a specific store depends on how many of its customers already use Shop Pay.

Which methods customers in DACH and Central Europe prefer differs by country; payment fees and gateways for each market are covered in What an online store costs in 2026 and How much a Shopify store costs in 2026.

Product page content

Almost every purchase goes through a product page. In Baymard's 2026 product page benchmark, based on more than 30,000 ratings, 52% of desktop sites, 62% of mobile sites and 64% of apps had an overall product page experience rated "mediocre" or worse. The benchmark lists specific gaps:

According to the same research, 42% of users try to judge a product's size from the product images. For a small store, the practical order is: photos that show size and use, a description that answers the questions customer service gets most often, visible price and shipping, reviews, and a clear returns sentence.

Search and filters

In Baymard's large-scale testing, roughly half of participants used search as their preferred way to find products. Baymard's 2026 search benchmark (updated on 29 April 2026) found that 56% of sites fail to adequately support users' search needs. The share of sites with problems differs by query type:

• exact product name: 12% of sites have issues,
• product type ("winter jacket"): 20%,
• feature ("waterproof"): 39%,
• use case ("for hiking"): 43%,
• compatibility ("for iPhone 15"): 44%,
• abbreviations and symbols: 54%,
• non-product queries such as shipping or returns: 66%.

For filters, Baymard's 2025 product list benchmark (updated on 9 September 2025) rated 58% of desktop sites and 78% of mobile sites "mediocre" or worse. 51% of sites did not offer the five essential filter types: price, average user rating, colour, size and brand.

On Shopify, search and filters are set up in the free Shopify Search & Discovery app, which covers search, filters and product recommendations. According to Shopify's help centre, collections with more than 5,000 products do not display filters, and a filter shows at most 100 values in the store, so very large collections should be split. Shopify Analytics has reports for searches with no results and searches with no clicks: they show what customers look for and do not find.

How to prioritise and test changes

A useful order of work:

1. Fix errors first. Broken checkout steps, apps that slow down the page, missing payment methods: according to Baymard, 17% of shoppers who left did so because of errors. Errors do not need an A/B test.
2. Start at the weakest funnel step. Compare the store's add-to-cart and checkout completion rates with its own history and with the medians above.
3. Score each idea by expected impact, the share of visitors it affects and the effort. A change on the product page template reaches every product; a change on one landing page reaches only its visitors.
4. Test what is uncertain, measure what is certain. A shipping cost shown upfront can be launched and monitored; a new product page layout is worth a test.

A/B tests in Shopify: since an update announced on 5 June 2026, Shopify Rollouts can schedule, gradually publish and A/B test themes, checkout and customer account configurations, under Markets > Rollouts in the admin. According to Shopify's help centre, rollouts are available from the Basic plan, experiments only from the Grow plan. They do not work on vintage themes, Liquid templates cannot be changed within a rollout, and the results cannot be filtered by device or country. Tests that change Liquid templates therefore need a different tool.

Sample size: an online store converts only a small share of visits, so tests need a lot of traffic. In this guide's calculation (two-sided test, 5% significance level, 80% power), a store at 1.4% needs about 30,400 sessions per variant, about 60,700 in total, to reliably detect a relative improvement of 20% (from 1.4% to 1.68%). For an improvement of 10%, it needs about 116,000 sessions per variant. A store with 20,000 sessions a month would therefore run the first test for about three months. The numbers can be checked with a sample size calculator such as Evan Miller's.

Two common mistakes: stopping a test as soon as the dashboard shows a "significant" result, which Evan Miller describes as repeated significance testing errors that produce false winners, and comparing periods with different seasons, for example October with the Black Friday weeks. Stores with too little traffic for a test should make changes based on evidence such as the data in this guide, and compare the same funnel steps before and after.

Checklist: increasing the conversion rate step by step

1. Note the current conversion rate in Shopify Analytics and the definition behind it.
2. In GA4, check that purchase is the only key event used for the conversion rate.
3. Open the Conversion rate breakdown report and find the step with the largest drop, by device and traffic source.
4. Compare with benchmarks: Littledata median 1.4%, top 20% above 2.7% (July to October 2026).
5. Check Core Web Vitals: LCP up to 2.5 s, INP up to 200 ms, CLS up to 0.1.
6. Show shipping costs, the free-shipping threshold and the delivery date before checkout.
7. Link the returns policy from every product page.
8. Allow guest checkout and keep only necessary fields.
9. Switch on express checkout: Shop Pay where Shopify Payments is available, Apple Pay, Google Pay and PayPal.
10. Add size, use and model photos, reviews and a visible price to product pages.
11. Set up the five basic filters (price, rating, colour, size, brand) and check searches with no results each month.
12. Make a test order on mobile and desktop every month.
13. Calculate the sample size before an A/B test and do not stop it early.

To go through all of these points in a specific store, an e-shop audit checks the funnel, speed, checkout, payments and tracking, and sorts the findings by what to fix first. At Alpinefy it costs €690 for a smaller store and €1,090 for a larger one; Alpinefy is not a VAT payer, so the price is final. The free Webcheck tests the homepage in about 30 seconds.

Sources, checked on 3 November 2026: ShopifyQL session metrics, Shopify behaviour reports, Shopify sessions, GA4 dimensions and metrics, GA4 Purchase journey, GA4 consent mode, Littledata conversion rate, Littledata add-to-cart rate, Littledata checkout completion, uptain Conversion Rate Report 2025, IRP Commerce market data, Core Web Vitals thresholds, Web Vitals, Vodafone case study, Baymard cart abandonment, Baymard product page UX, Baymard search UX, Baymard product lists and filtering, Shopify accelerated checkouts, activating Shop Pay, Shopify Payments countries, Shop Pay, third-party payment providers, Shopify pricing (AT), Shopify Search & Discovery, Shopify filters, Shopify Rollouts changelog, Rollouts requirements, Rollouts analytics, Evan Miller sample size calculator, How Not To Run an A/B Test.