Shopify Conversion Rate Benchmarks by Industry (2026)

WRITTEN BY

Gary Culaev, Founder and CEO, Weblics Consulting

Shopify Conversion Rate Benchmarks by Industry (2026)

Every published Shopify conversion rate benchmark answers a slightly different question, and almost none of them say which. The result is that the same industry shows up at 6.22% in one table and 2.2% in another, from the same data provider, in the same quarter. Below are the benchmarks worth using, what each one actually measures, and how to work out which applies to you.

Short answer

• The most cited Shopify-specific benchmark is Littledata's: 1.4% average across 2,800 stores, 3.2% for the top 20%, 4.7% for the top 10% (2023 data).
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• Industry, average order value, traffic source, device and store size each move the number more than most people expect. Email traffic converts at 5-8%, TikTok ads at 1.2-2.2%.
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• Average order value is the strongest single predictor: stores under $60 AOV convert at a 2.42% median, stores above $200 at 0.79% (DTC Pages, 21 Shopify stores, Q2 2026).
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• Most published tables do not state whether they divide by sessions or by visitors. Shopify Analytics divides by sessions.
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• Retail conversion fell 5.5% year over year in Contentsquare's 2026 benchmark, so a table from 2023 makes a healthy store look like it is failing.
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• The useful comparison is your own four funnel steps against their typical ranges, not your site-wide rate against a stranger's.

In this guide

What is a good Shopify conversion rate?
Ecommerce conversion rate benchmarks by industry
Conversion rate benchmarks by average order value
Why conversion benchmarks contradict each other
Check what your Shopify dashboard is actually measuring
Conversion rate benchmarks by traffic source
Conversion rate benchmarks by device
Why bigger stores convert lower
When a low conversion rate is the correct number
Two stores at 2.1%, and how to tell them apart
Glossary
FAQ

What Is a Good Shopify Conversion Rate?

The most widely quoted Shopify benchmark comes from Littledata, whose study of 2,800 Shopify stores found an average conversion rate of 1.4%, with 3.2% or above placing a store in the top 20% and 4.7% or above in the top 10%.

Littledata Shopify conversion rate benchmark: average across 2,800 stores, top 20% and top 10% thresholds

Two things about that table matter more than the numbers in it.
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It is an average, not a median, so a handful of very high performers pull it upward while the typical store sits below it. And the study is from 2023. It remains the most cited Shopify-specific figure available, which is why it is here, but treat it as a reference point rather than a 2026 target.
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What a good conversion rate is for you depends on five things this page works through in order: your industry, your average order value, your traffic mix, your device split, and your store's size. Each one moves the number more than most people expect.

Ecommerce Conversion Rate Benchmarks by Industry

Industry is the largest single input into what your number should be. In the most widely republished industry breakdown, food and beverage converts around 6x higher than luxury and jewelry.

Shopify conversion rate by industry, from food and beverage to luxury and jewelry

The pattern behind the spread is purchase consideration. Food and beauty are cheap and repeated, and getting one wrong costs almost nothing. Furniture and jewelry get researched over weeks and often bought on a second or third visit that your analytics may count as a separate session entirely.

Quick Note:

Category labels aren't standardized between datasets. "Beauty & personal care" in one table is "Health & Beauty" in another and includes supplements. Before accepting a benchmark, check what sits inside the category, not just what it is called.

Those figures are widely reprinted, including by Shopify. They are also contradicted by the same data provider on the same page, which is covered two sections down, right after the one variable that predicts conversion better than industry does.

Conversion Rate Benchmarks by Average Order Value

Average order value predicts conversion rate better than industry does, and the relationship runs one way: the higher the basket, the lower the conversion rate. In DTC Pages' study of 21 Shopify stores, stores under $60 AOV converted at a 2.42% median and stores above $200 at 0.79%, a gap of roughly 3x that held across verticals.

Shopify conversion rate and add-to-cart rate by AOV bracket, from under $60 to $200+

The mechanism is purchase consideration, the same force behind the industry spread above. A $40 consumable is decided in one session and often by a returning customer. A $250 item is researched across several sessions, each of which lands in the denominator, and the add-to-cart rate drops with it: 6.43% under $60, 3.46% above $200.
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Two things follow for how you read your own number. A store at 0.9% with a $230 basket is performing normally, and a redesign chasing 2% will spend a quarter fighting the price point. And a conversion win bought with a smaller basket is not a win: if a test lifts conversion by 10% and cuts AOV by 12%, revenue per session went down. Read the two together, which is why every table on this page should be paired with the AOV your store actually carries.

Quick Note:

Industry tables hide this. Food and beverage converts at 6.22% partly because its baskets are small; luxury converts at 0.94% partly because its baskets are large. Before comparing yourself to a category figure, check whether your AOV sits where that category's typically does.

Why Conversion Rate Benchmarks Contradict Each Other

You do not need to compare rival sources to find the problem. Shopify's own guide to retail conversion cites Statista's Q3 2025 data twice, and the two citations disagree.

Two Statista breakdowns from the same quarter giving different conversion rate benchmarks

Food and beverage appears at 6.22% in one cut and 2.2% in another. That is a factor of 2.8 on one category, one provider, one quarter, one page. The same article notes that Dynamic Yield's benchmark index puts the global average "closer to 2.9%" against Statista's 1.6%.
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Three things produce gaps like these, and published tables rarely disclose any of them.
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The denominator. A visitor who returns three times before buying is one visitor and three sessions. Orders divided by sessions therefore reports a materially lower rate than orders divided by visitors on the identical store. Most benchmark tables, including both cited above, never say which one they used.
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Who is in the sample. A global merchant base, a panel of UK small retailers, and a set of enterprise brands running a personalization platform are three different populations. Each is real. None is interchangeable with the others.
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When it was measured. Retail conversion is seasonal and currently moving. Contentsquare's 2026 retail benchmark reports overall conversion down 5.5% year over year, and that decline is not evenly spread: desktop fell 8% while mobile fell 3.5%.
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It is like comparing your mile time to somebody else's kilometer time. Both are real numbers. Neither tells you who is faster.

Important Update:

Check the date and the denominator before acting on any benchmark. With retail conversion down 5.5% year over year, a table published two or three years ago will make a healthy store today look like it is failing. If a source states neither its date nor how it calculated the rate, it can tell you the rough shape of a category and nothing more precise than that.

Check What Your Shopify Dashboard Is Actually Measuring

Before comparing yourself to anything above, find out which metric you are holding. It takes about a minute.
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1. Open Shopify Analytics, Reports, Conversion rate, or the conversion figure on your Overview dashboard.
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2. Set the range to the last 90 days. Anything shorter is noise for most stores.
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3. Note the number, and note that Shopify calculates it as orders divided by sessions.
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4. Write it down. You will narrow it three more times before the end of this page.
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Step three is the one that catches people. Your dashboard has a defined denominator. Most published tables do not disclose theirs. A store comparing its sessions-based dashboard figure against a table that quietly counted visitors is understating its own performance, and has no way to tell by how much.
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That does not make benchmarks useless. It means you should treat a single published percentage as a range, and put your weight on comparisons where the denominator is fixed: your store against itself over time, and your channels against each other.

Pro Tip:

Cross-check Shopify against GA4 before trusting either. The two routinely disagree on session counts because of different attribution windows and bot filtering. If they are more than 10% apart, fix that before spending a quarter optimizing against a number that is wrong at the source. Which tool answers which question is covered in our guide to the best Shopify analytics apps.

Now narrow it by traffic.

Shopify Conversion Rate Benchmarks by Traffic Source

Traffic source explains more variance in your conversion rate than your industry does. Two stores running near-identical websites can sit at 4% and 1.5% purely on where their visitors come from.

Shopify conversion rate by traffic source: email and SMS, direct, organic search, Google, Meta and TikTok ads

Email and direct convert three to four times better than paid social, and it has nothing to do with the channels being smarter. Those visitors already know you and arrived with intent. Paid social interrupts someone who was not shopping and asks them to buy inside one session.
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This is why a blended site-wide conversion rate is a weak diagnostic. A store shifting from 30% paid to 70% paid will watch its overall conversion rate fall while every individual channel holds steady or improves. Nothing got worse. The mix changed.
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Compare paid traffic to the paid benchmark and email to the email benchmark. A store converting Meta traffic at 1.6% is not failing against 3.2%. It is failing against 1.8-3%, which is a much smaller and much more fixable gap. What that gap costs at scale is the subject of our piece on CRO vs ad spend.

Shopify Conversion Rate Benchmarks by Device

Desktop converts roughly 1.85x better than mobile, while mobile delivers around three quarters of the traffic.

Desktop vs mobile conversion rate for all retail and for luxury stores

Cart abandonment tells the same story from the other end: Dynamic Yield's benchmark index, drawn from 400+ brands, reports 79.0% abandonment on mobile against 68.1% on desktop.
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The gap itself is normal. The size of your gap is the diagnostic, and it is one of the few comparisons on this page where the denominator problem disappears, because both of your device figures come from the same dashboard measured the same way.
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Retail averages a 1.85x desktop-to-mobile ratio. A store where desktop converts 4x better has a mobile problem worth more than most of the tests on its roadmap. A store at 1.3x is already ahead of its category.
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Split your own number by device now. The ratio matters more than either figure.

Why Bigger Shopify Stores Convert Lower

Conversion rate falls as stores grow, which catches out almost everyone benchmarking themselves against a top-decile figure.

Shopify conversion rate by store size in monthly sessions: under 5,000, 5,000-50,000 and 50,000+

Small stores run on warm traffic: friends, existing customers, a niche audience that already knows the brand. Growth means buying colder traffic, which converts worse by definition. The percentage falls while the revenue climbs.
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Think of a shop on a busy high street versus one down a side alley. The alley shop converts a higher share of the people who walk in, because only people looking for it walk in. The high street shop converts a lower share and takes far more money.
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So a store doing 80,000 sessions a month at 1.7% is not underperforming a 1.4% platform average. It is sitting mid-range for its size, and the 4.7% top-decile threshold is populated largely by stores an order of magnitude smaller.

When a Low Conversion Rate Is the Correct Number

Four situations where a number that looks bad is fine, and where chasing it costs you money.
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High-consideration, high-price catalogs. Furniture, fine jewelry, high-end equipment. At 0.94% for luxury and jewelry, that is the category working as intended. Judge revenue per session instead.
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Wholesale or B2B on Shopify. Buyers research on the storefront and order through a rep, a portal or a purchase order. Your storefront conversion rate is measuring the wrong event.
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Subscription-first businesses. One conversion produces twelve orders. A low first-purchase rate alongside a high retention rate is a strong business, and the headline conversion figure will never show it.
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Deliberately broad top-of-funnel traffic. Awareness campaigns and informational search rankings buy visitors who were never going to purchase today. That is a strategy, not a leak, provided you are measuring what those visitors do on their second and third visit.

Reminder:

Revenue per session is the harder number to fool. It moves with conversion rate and average order value together, so it catches the case where a conversion win came out of discounting. If you track one site-wide figure, track that one.

Two Stores at 2.1%, and How to Tell Them Apart

A conversion rate tells you whether something is wrong. It never tells you what. Two stores can post the same 2.1% and need completely different work.
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Store A converts 8% of product page views into carts, which is inside the normal range, then completes 38% of started checkouts. Store B converts 4% of product page views into carts, then completes 58% of checkouts.
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Same headline number. Store A has a checkout problem: shipping costs appearing late, forced account creation, too few payment methods. Baymard Institute's 2025 survey puts unexpected extra costs at the top of the reasons non-browsers abandon, at 39%. Store B's checkout is fine and its product pages are not doing their job.
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Fixing A's problem would do nothing for B. This is why benchmarking a single site-wide number, however carefully segmented, is only the first step.
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Here is where the number breaks apart:

Typical funnel step conversion ranges, from product page view to completed order

Run your last 90 days through those four rows. One will sit visibly outside its range, and that step is where your money is going. It is also the first thing we build a testing roadmap around at Weblics, because a store that knows which step is leaking gets to skip a quarter of guessing.
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If your outlier is the second row, product page to add to cart, the fix is rarely a redesign. Start with the list we test from: 9 PDP Patterns We Test Before Spending Another Dollar on a Redesign. If it is the fourth row, start with our guide to Shopify checkout optimization.
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Every figure on this page comes with a caveat about denominators, samples and dates. Your own funnel comes with none of them, because every step is measured the same way, by the same tool, on the same store.
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So stop asking whether your number is normal. Ask which of those four rows is outside its range, and start there.

Glossary

Conversion rate (Shopify definition). Orders divided by sessions over the selected date range, as calculated in Shopify Analytics. A returning visitor with three sessions and one order counts as one order over three sessions.
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Denominator. The base a conversion rate is divided by: sessions or unique visitors. Orders per visitor is always higher than orders per session on the same store, which is why undisclosed denominators make benchmarks incomparable.
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Average order value (AOV). Net revenue divided by orders. Rises with price point and moves inversely with conversion rate, which is why the two are read together as revenue per session.
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Revenue per session. Net revenue divided by sessions. Moves with conversion rate and average order value together, so it catches a conversion win that came out of discounting.
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Desktop-to-mobile ratio. Desktop conversion rate divided by mobile conversion rate. Retail averages about 1.85x; a ratio far above that points to a mobile experience problem.
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Funnel step rate. The share of visitors who progress from one stage to the next (visit to product page, product page to cart, cart to checkout, checkout to order). Measured consistently within one store, so it needs no external caveat.