Ecommerce Conversion Rate Benchmarks 2026: What Is a Good Rate for a D2C Store, and How to Raise Yours

The average ecommerce conversion rate in 2026 sits between roughly 1.3% and 2.7% of sessions, depending on who is counting and which stores are in the sample. The median Shopify store converts 1.3% of sessions into orders. Global retail trackers report 1.6% to 2%. Benchmarks built on larger brands land near 2.7%. A good rate for a D2C store is anything above 2.7%, which puts you in the top 20% of Shopify stores. Above 3.6% puts you in the top 10%.

Those numbers come from sources that measure different things, so here is the short version before the detail.

• Typical Shopify store: 1.3% median, 1.9% mean, across 438 Shopify stores for the 90 days to October 31, 2026 (Littledata).
• Global ecommerce visits: 1.6% in Q3 2026 (Statista, source data from Salesforce Research).
• Independent UK-centric merchants: 1.97% in September 2026, up from 1.68% a year earlier (IRP Commerce).
• Larger brands: 2.66% across more than 400 brands, per Dynamic Yield as reported by Shopify in its August 2026 update.
• Cart abandonment: 70.22%, the unweighted average of 50 studies (Baymard Institute).

The benchmark to compare yourself against is the one built from stores like yours, measured the way your dashboard measures. For most D2C founders on Shopify, that is the 1.3% median and the 2.7% top-quintile line. The rest of this guide shows where each number comes from, how to calculate your own rate correctly, which funnel stage is leaking, and which fixes have evidence behind them. If you would rather have the diagnosis and the fixes done for you, that is our Shopify growth work. Everything below, you can do yourself.

What is the average ecommerce conversion rate in 2026?

There is no single average. There are at least five credible public numbers, and they disagree because they are answering different questions. The table puts them side by side.

Source	Reported rate	Period	Sample	What it measures
Littledata	1.3% median (1.9% mean)	Aug 3 to Oct 31, 2026	438 Shopify stores, each with at least 1,000 sessions and 90 purchases	Share of GA4 sessions with at least one purchase, tracked server-side
Statista (Salesforce Research data)	1.6%	Q3 2026	Global ecommerce sites	Share of visits that convert to a purchase
IRP Commerce	1.97%	September 2026	IRP's ecommerce market data, reported in pounds, focused on independent merchants	Average conversion rate across all tracked markets
Dynamic Yield (via Shopify)	2.66%	Mid 2026	More than 400 brands	Global average conversion rate
Contentsquare	1.7% new visitors, 2.9% returning	2025 data, published March 2026	99 billion sessions across 6,000+ sites, all industries	Session conversion, not ecommerce-only
Unbounce	4.2% median	Report published 2024	Ecommerce landing pages built on Unbounce	Landing-page conversions, not storewide orders

Sources: Littledata, Statista, IRP Commerce, Shopify, Contentsquare, Unbounce. All accessed November 2026.

Read that table top to bottom and the pattern is clear. The smaller and more typical the stores in the sample, the lower the number. The more the sample leans toward large brands with strong repeat traffic, the higher it climbs. And once you leave storewide sessions for campaign landing pages, the number jumps again, because a landing page only sees visitors who already clicked an ad or an email.

Why the public benchmarks disagree

Four things move the number before a single shopper does anything different.

The denominator. Most sources divide orders by sessions (visits). Some divide by users. One person who visits three times and buys once is a 33% session conversion and a 100% user conversion. Shopify's own guidance is blunt on this point: the rate is calculated from orders and sessions, and reporting it on users inflates it (Shopify).

Mean versus median. Littledata publishes both for the same 438 stores: 1.3% median and 1.9% mean. The mean is higher because a minority of stores convert far above the rest and drag the average up. If you compare yourself to a mean, you are comparing yourself to a number most stores are below.

Who is in the sample. Dynamic Yield's benchmark draws on more than 400 brands. Littledata's comes from Shopify stores using its tracking app, with a floor of 1,000 sessions and 90 purchases in 90 days. IRP's data is reported in pounds and built around independent small and mid-market merchants. None of these is a random sample of all online stores.

Time of year. IRP reports monthly, and its all-market rate moved from 1.68% in September 2025 to 1.97% in September 2026. Statista's global figure moved from 1.4% in Q1 2026 (as cited by Shopify) to 1.6% in Q3 2026. A benchmark from peak season is not a fair target for February.

Which benchmark should you compare against?

Use this rule. Match the platform, the method, and the store size.

• You run a Shopify store with real but modest traffic. Compare against Littledata's median of 1.3% and its percentile bands. It is the only public source here that tracks every store with the same event definitions.
• You run a larger brand with heavy returning and email traffic. The 2% to 2.7% figures from IRP and Dynamic Yield are the closer comparison.
• You are judging a paid landing page. Use landing-page benchmarks such as Unbounce's, and never mix them with storewide numbers.
• You are on WooCommerce. No public source in this guide isolates WooCommerce stores. Use the session-based figures above with the same caveats, and weight your own trend more than any external number.

The benchmark that matters most is your own rate last quarter, measured the same way, on the same traffic mix.

What is a good ecommerce conversion rate for a D2C store?

A good ecommerce conversion rate is above 2.7%. That is the line for the top 20% of the 438 Shopify stores Littledata benchmarks. The top 10% reach 3.6% or more. Below 0.5% puts a store in the bottom 20%.

Position among Shopify stores	Conversion rate	Add-to-cart rate	Checkout completion	Cart abandonment
Bottom 10%	0.3%	2.1%	15%	94%
Bottom 20%	0.5%	3.4%	26%	90%
Median	1.3%	6.6%	47%	79%
Top 20%	2.7%	12%	65%	65%
Top 10%	3.6%	17%	73%	56%

Source: Littledata Shopify benchmarks, 435 to 438 Shopify stores depending on the metric, 90 days to October 31, 2026. For cart abandonment, lower is better, so the "top" rows show the best-performing stores.

Littledata describes the typical range, the middle 60% of stores, as 0.5% to 2.7%. So a store at 1% is not broken. It is ordinary. A store at 0.4% has a real problem. A store at 3% is ahead of four in five peers.

"Good" also depends on what you sell. A store with a median order near $70 and a store with a median order above $200 should not expect the same rate. The next section shows how wide that spread is.

One caution before you chase the top row. Conversion rate is a ratio, and ratios can improve while the business gets worse. A deep discount lifts conversion and can erase margin. If you have not worked out contribution margin per order yet, read our D2C unit economics guide alongside this one. This guide stays on conversion.

How do you calculate ecommerce conversion rate correctly?

Ecommerce conversion rate is orders divided by sessions, times 100.

Conversion rate = (orders / sessions) x 100

If your store had 20,000 sessions last month and 260 orders, your conversion rate is 260 / 20,000 = 1.3%.

That is the whole formula. The trouble is in the inputs.

Sessions versus users

A session is one visit. A user is one person, or more precisely one browser or device. The same person coming back on Tuesday and Friday is one user and two sessions.

Google Analytics 4 exposes both versions. Its session key event rate is "the percentage of sessions that converted," and its user key event rate is "the percentage of users who converted" (Google Analytics Help). They will never match.

Worked example. Your store gets 10,000 sessions from 7,000 users in a month and takes 150 orders, each from a different person.

• Session conversion rate: 150 / 10,000 = 1.5%
• User conversion rate: 150 / 7,000 = 2.14%

Same store, same month, and the user-based number is 43% higher. Almost every public benchmark in this guide is session-based. If you compare a user-based rate from your dashboard against them, you will think you are ahead when you are not.

GA4 versus Shopify analytics

Your GA4 number and your Shopify number will differ. That is normal. Three verified reasons:

1. GA4 counts any key event unless you filter. Session key event rate is sessions with a key event divided by total sessions. If newsletter signups and add-to-carts are marked as key events alongside purchases, the rate is not your purchase rate. Filter the metric to the purchase event.
2. Session rules differ by tool. In GA4 a session ends after 30 minutes of inactivity by default (Google Analytics Help). Other tools draw the line elsewhere, so the denominators differ.
3. Tools disagree on more than sessions. Shopify's own documentation of the metric says analytics tools "disagree on what counts as a session, where credit is assigned, which orders are included, and which channels are counted," and that this does not make one of them wrong (Shopify).

Shopify's advice is the right one: pick one tool as your source of truth and track the trend there. Use the other for context. Do not average them, and do not switch between them from one report to the next.

Shopify Analytics calls the metric "online store conversion rate." In GA4, use session key event rate filtered to the purchase event, or divide purchases by sessions yourself.

Three mistakes that corrupt the number

• Counting bots and internal traffic. Fake sessions inflate the denominator and push your rate down. Exclude your own team's traffic and check for traffic spikes with zero engagement.
• Mixing channels in one number. Wholesale orders, draft orders, and point-of-sale orders are not online store conversions. Keep them out of the numerator.
• Changing the window. Compare the same period length, and compare like seasons. A 7-day rate during a sale tells you nothing about a normal month.

Less than half of merchants track profit margin, traffic, average order value, or conversion rate, according to Shopify's Q4 2025 survey of store owners, cited in the same Shopify article. Simply measuring your rate the same way every week puts you ahead of many.

What is the average ecommerce conversion rate by industry?

Conversion rate by industry ranges from under 1% for high-ticket and considered purchases to above 5% for low-priced consumables, depending on the source. Here are four public breakdowns from 2026. They use different category names and different samples, so read down each column, not across the rows.

Category	Littledata median (Shopify, 90 days to Oct 2026)	Littledata top 20%	Statista (global, Q3 2026)	Dynamic Yield via Shopify (June 2026)
All stores / all sectors	1.3%	2.7%	1.6%	2.66%
Beauty and skincare / personal care	2.6%	3.9%	2.6% health and beauty, 1.9% skincare	5.32%
Health and supplements	2.4%	3.7%	n/a	n/a
Food and beverage	2.2%	3.6%	3.8%	4.58%
Fashion and apparel	1.0%	1.8%	n/a	2.77%
Home and furniture	1.0%	1.8%	n/a	1.29%
Pet care	n/a	n/a	n/a	5.7%
Consumer goods	n/a	n/a	n/a	1.76%
Luxury and jewelry	n/a	n/a	n/a	0.63%

Sources: Littledata (industries with at least 30 stores), Statista, and Dynamic Yield's industry figures as published by Shopify. "n/a" means the source does not publish that category.

IRP Commerce publishes a monthly figure for ten markets, with average order value alongside. This is the clearest public view of how price point and conversion move against each other.

IRP market	Conversion rate, Sept 2026	Conversion rate, Sept 2025	Average order value, Sept 2026
All ecommerce markets	1.97%	1.68%	£133.12
Arts and crafts	5.76%	4.32%	£128.40
Health and wellbeing	2.83%	1.93%	£52.90
Kitchen and home appliances	2.59%	3.55%	£57.74
Pet care	2.13%	2.45%	£88.92
Sports and recreation	1.90%	1.46%	£103.29
Cars and motorcycling	1.76%	1.15%	£243.95
Fashion clothing and accessories	1.62%	1.29%	£88.28
Food and drink	1.28%	1.30%	£122.23
Toys, games and collectables	1.07%	1.89%	£65.54
Baby and child	0.44%	0.69%	£871.49

Source: IRP Commerce ecommerce market data, September 2026 versus September 2025, one page per market.

Three things to take from these tables.

Consumables convert best. Beauty, supplements, food, and pet products sit at the top of every source. Shoppers know what they are buying, the price is low, and many of them are reordering.

High-ticket categories convert worst, and that is fine. IRP's baby and child market converts at 0.44% with an average order above £870. Dynamic Yield's luxury and jewelry figure is 0.63%. A store selling $900 strollers at 0.6% can be far healthier than a store selling $20 candles at 3%.

The same category can swing hard year over year. IRP's toys market fell from 1.89% to 1.07% in twelve months. Its health market rose from 1.93% to 2.83%. Small samples and category trends both play a part. Treat any single month's figure as a snapshot.

For fashion and home founders on Shopify specifically: the Littledata median is 1.0% and the top 20% line is 1.8%. If you are at 1.5% in apparel, you are well above the middle, even though you are below the "2% average" you may have read elsewhere.

Mobile versus desktop conversion rate

Mobile gets most of the traffic. On most large sites, desktop still converts at a higher rate. On Shopify stores, the gap has narrowed and in some data has flipped.

Measure	Mobile	Desktop	Source and period
Share of all traffic (all industries)	69.9%	Remainder	Contentsquare, 2026 report
Conversion rate gap (all industries)	Baseline	74% higher than mobile	Contentsquare, 2026 report
Retail conversion rate	2%	3.7%	Contentsquare retail data, as cited by Shopify
Median conversion rate, Shopify stores	1.5%	1.3%	Littledata, 90 days to Oct 2026
Top 10% conversion rate, Shopify stores	4.3%	4.7%	Littledata, 90 days to Oct 2026
Median add-to-cart rate, Shopify stores	5.3%	10%	Littledata, 90 days to Oct 2026
Median checkout completion, Shopify stores	63%	32%	Littledata, 90 days to Oct 2026
Share of sales (IRP all markets)	61.4%	37.1%	IRP Commerce, September 2026
Median share of sessions, Shopify stores	66%	n/a	Littledata, 90 days to Oct 2026

Sources: Contentsquare, Shopify, Littledata (conversion rate, add-to-cart rate, checkout completion), IRP Commerce.

The Littledata rows deserve a second look, because they cut against the usual advice. Across Shopify stores, the median mobile conversion rate (1.5%) is slightly above desktop (1.3%). Mobile shoppers add to cart about half as often as desktop shoppers (5.3% versus 10%), but once they start checkout they finish at roughly twice the rate (63% versus 32%). Littledata does not explain the gap. Our read is that it reflects who shows up on each device for a D2C brand: mobile sessions arrive from ads, email, and SMS with a saved wallet one tap away, while desktop sessions include more research visits. Treat that as an interpretation, not a finding.

The practical point holds either way. Globally, about three-quarters of retail site visits came from smartphones as of Q1 2026, and they generated more than two-thirds of online orders (Statista). Your mobile product page is your store. If mobile add-to-cart is your weakest number, that is where to work.

Conversion rate by traffic channel

Traffic source changes conversion more than almost anything you do on the page. Visitors who already know you (email, direct, branded search) convert at multiples of visitors meeting you for the first time (paid social, display).

Channel or segment	Benchmark	What it measures	Source
Returning visitors	2.9%	Session conversion, all industries	Contentsquare 2026
New visitors	1.7%	Session conversion, all industries	Contentsquare 2026
Paid search	2.8%	Highest-converting paid channel, all industries	Contentsquare 2026
AI-referred traffic	1.3%	Up 55% year over year, 0.2% of all traffic	Contentsquare 2026
Organic social	0.7%	Session conversion, all industries	Contentsquare 2026
Email landing pages	28.6% median	Ecommerce landing-page conversion	Unbounce
Paid search landing pages	5.1% median	Ecommerce landing-page conversion	Unbounce
Paid social landing pages	4.8% median	Ecommerce landing-page conversion	Unbounce

Sources: Contentsquare conversions chapter and traffic chapter (99 billion sessions, 6,000+ sites, comparisons from Q4 2024 to Q4 2025), Unbounce. The Contentsquare figures cover all industries, not ecommerce alone. The Unbounce figures are landing-page conversions, which run far higher than storewide order rates. Do not compare one set against the other.

A few channel facts worth holding onto:

• Returning visitors convert about 70% better than new ones in Contentsquare's data (2.9% versus 1.7%), and they are now more than half of all traffic (52.8%).
• Paid traffic is 42% of all traffic in the same report, with paid search at 25.15% and paid social at 10.5% of sessions. Paid social grew 18% year over year. More cold traffic means a lower blended rate, even when nothing on the site changed.
• Email is the highest-intent channel you own. In Klaviyo's 2026 benchmarks, built on more than 183,000 customers, automated flows produce nearly 41% of email revenue from 5.3% of sends (Klaviyo).
• Paid search does the heavy lifting on sales for independent merchants. In IRP's September 2026 data, paid search drove 63.5% of sales, direct 20.2%, email 10%, and paid social 0.5%.

If you run Google Ads or Meta campaigns, judge each channel against its own history, not against your blended store rate.

Conversion rate by region

Public regional data is thin, and we will not pad it. What is verifiable: Statista's Q3 2026 tracker puts the global average at 1.6% and Switzerland at 1.9%. IRP's 1.97% is drawn from merchants reporting in pounds, with 57.7% of sales domestic and 42.3% international in September 2026. Beyond that, we could not verify a current regional breakdown at its source, so we have left it out. If you sell in several countries, segment your own conversion rate by market. Shipping cost, delivery time, and payment methods differ by country, and those are three of the top reasons shoppers abandon.

Add-to-cart, cart abandonment, and checkout completion benchmarks

Sitewide conversion is the end of a chain. These are the links.

Add-to-cart rate. The median Shopify store sees a product added to cart in 6.6% of sessions. The top 20% are above 12%. Beauty and food stores have the highest median (12%), home and furniture the lowest (5.1%) (Littledata).

Cart abandonment rate. Baymard's long-running average is 70.22%, calculated as the unweighted mean of 50 studies published from 2006 to 2025, with individual studies ranging from 55% to 84% (Baymard). Littledata's Shopify median is higher at 79%, because it counts every session that added to cart and did not purchase in that session. The best 20% of stores keep it under 65% (Littledata).

Checkout completion rate. Of sessions that start checkout, a median 47% go on to purchase. The top 20% are above 65%. Health and supplements stores lead at 60%. Fashion is lowest at 47% (Littledata).

Do not panic at a 70% or 79% abandonment figure. Baymard is explicit that a large share is unavoidable. In its latest survey, 42% of US online shoppers said they had abandoned a cart because they were "just browsing / not ready to buy." People use carts as wishlists. Your job is to remove the avoidable reasons, which the checkout section covers.

Why does your conversion rate differ from the benchmark?

Before you decide your store is underperforming, check four things. Any one of them can explain a gap of a full percentage point.

Traffic mix

Your blended rate is a weighted average of your channels. Change the weights and the average moves, even if every channel performs exactly as before.

Worked example. Month one, your store gets 10,000 sessions:

• 6,000 from email, direct, and returning visitors, converting at 3.0%: 180 orders
• 4,000 from paid social, converting at 0.8%: 32 orders
• Total: 212 orders, a 2.12% conversion rate

Month two, you scale paid social to 14,000 sessions. Nothing else changes.

• 6,000 warm sessions at 3.0%: 180 orders
• 14,000 paid social sessions at 0.8%: 112 orders
• Total: 292 orders from 20,000 sessions, a 1.46% conversion rate

Conversion rate fell from 2.12% to 1.46%. Orders rose 38%. The site did not get worse. You bought more cold traffic. Whether that was a good trade is a question about acquisition cost and margin, not conversion rate.

Price point

Higher prices mean longer consideration and lower conversion. The IRP table shows it at the extremes: baby and child at 0.44% on an £871 order, health and wellbeing at 2.83% on a £53 order. Shopify makes the same point with Dynamic Yield's data, where food and beverage converts at 4.58% and luxury and jewelry at 0.63%.

Compare revenue per session, not just conversion rate. Revenue per session is conversion rate times average order value. A store at 1.3% with a $111 order earns $1.44 per session. A store at 1.2% with a $130 order earns $1.56. The second store "converts worse" and makes more money from the same traffic. For reference, the median Shopify store in Littledata's data earns $1.98 per session, with a median order of $111.

New versus returning visitors

Returning visitors convert at 2.9% and new visitors at 1.7% in Contentsquare's cross-industry data. A young brand with almost no repeat base will sit below a mature brand with a large email list, even with an identical site. This is the main reason first-year stores should compare against the lower half of the percentile table.

Tracking differences

If your number comes from a user-based report, a GA4 property with extra key events, or a period with bot traffic, the gap may be an artifact. Recalculate with orders and sessions from one tool before you act.

Which funnel stage is leaking?

A sitewide conversion rate tells you there is a problem. The funnel tells you where. Pull five numbers for the same period: sessions, sessions with a product view, sessions with an add to cart, sessions that reached checkout, and orders.

Funnel stage	Metric	Median	Top 20%	Bottom 20%	If you are below the median, look at
Landing	Bounce rate	41%	Under 21%	Over 56%	Ad-to-page match, load speed, first screen clarity
Session to cart	Add-to-cart rate	6.6%	Over 12%	Under 3.4%	Product page content, price, reviews, shipping clarity
Cart to order	Cart abandonment	79%	Under 65%	Over 90%	Extra costs, cart page friction, delivery time
Checkout to order	Checkout completion	47%	Over 65%	Under 26%	Guest checkout, form fields, payment methods, trust
Session to order	Conversion rate	1.3%	Over 2.7%	Under 0.5%	The weakest stage above

Source: Littledata Shopify benchmarks, 90 days to October 31, 2026. Bounce rate there means sessions under 10 seconds with one page and no conversion. Littledata does not publish a product-view rate, so benchmark that stage against your own history.

Here is how the stages connect for a store sitting exactly on the medians, with 20,000 sessions a month.

• 20,000 sessions
• 1,320 sessions add to cart (6.6%)
• About 553 sessions start checkout
• 260 orders (47% of checkout starts, 1.3% of sessions)
• Cart abandonment: 1 minus 260 / 1,320 = 80.3%

The checkout-start figure is derived from the other medians for illustration. The medians come from slightly different sets of stores, so they will not multiply together perfectly.

Now a diagnosis. Say your store has 20,000 sessions, 600 add-to-cart sessions, 300 checkout starts, and 180 orders.

• Add-to-cart rate: 600 / 20,000 = 3.0% (bottom 20%)
• Checkout completion: 180 / 300 = 60% (near the top 20%)
• Conversion rate: 180 / 20,000 = 0.9%

Your checkout is fine. Better than fine. The leak is upstream: people are not adding to cart. Spending a month redesigning checkout would be wasted effort. The work is on the product page, the offer, or the traffic quality.

The reverse pattern is just as common. An add-to-cart rate of 9% with checkout completion at 30% means shoppers want the product and something between the cart and the confirmation page is stopping them. That is nearly always cost surprise, forced account creation, or a missing payment method.

What to fix at each stage

High bounce, low product views. The page does not match the promise that brought the visitor, or it loads too slowly to find out. Check the landing pages your ads and emails point to. Check mobile load time first.

Product views but few add-to-carts. The product page is not answering the buying questions: what is it, will it fit or work for me, what does it cost delivered, when will it arrive, can I send it back, do other people like it.

Add-to-carts but few checkout starts. The cart is surfacing a surprise. Usually shipping cost. Sometimes a threshold the shopper just missed, or a discount code field that sends them off to hunt for a code.

Checkout starts but few orders. Friction or distrust inside checkout: account walls, long forms, declined cards, no wallet option, unclear total.

The evidence-backed fixes, ranked by effort

Every fix below has a published source behind it. They are ordered by how much work they take, because the cheapest verified fix is the one to do first.

Fix	Funnel stage it helps	Effort	Evidence
Show full delivered cost early	Cart, checkout	Low	40% of abandoners cite extra costs (Baymard)
Make guest checkout the default	Checkout	Low	18% abandon over forced accounts (Baymard)
Turn on an express wallet	Checkout	Low	Shop Pay study data (Shopify)
Link returns policy on the product page	Product page	Low	60% look for it there (Baymard)
Collect and show reviews	Product page	Low to medium	Spiegel, PowerReviews, Bazaarvoice
Cut checkout form fields	Checkout	Medium	23.48 elements average versus 12 to 14 ideal (Baymard)
Set up cart recovery flows	Cart	Medium	Klaviyo flow benchmarks
Fix mobile speed	Every stage	Medium to high	Deloitte and Google, web.dev case studies
Rebuild product page content and images	Product page	High	Baymard product page benchmark

1. Site speed

Speed is the one fix that touches every stage of the funnel.

The strongest public study is "Milliseconds Make Millions," commissioned by Google and conducted by 55 and Deloitte. It tracked 37 European and American brand sites and more than 30 million user sessions over 30 days in late 2019. For a 0.1 second improvement in mobile site speed, retail conversions rose 8.4% and average order value rose 9.2% (Deloitte). The stage-level data is just as useful: progression from product listing page to product page rose 3.2%, and from product page to add-to-basket rose 9.1% (web.dev).

Two caveats. The data is from 2019, and it measured natural speed variation across large brands, not a controlled change on a small store. Treat the direction as established and the exact percentage as an upper guide, not a promise.

Controlled tests point the same way. Vodafone ran an A/B test where the only difference was Web Vitals optimization. A 31% improvement in Largest Contentful Paint produced 8% more sales and an 11% better cart-to-visit rate (web.dev). Rakuten 24 ran an A/B test focused on Core Web Vitals and reported a 33.13% higher conversion rate and 53.37% more revenue per visitor on the optimized version (web.dev).

The targets to hit are Google's Core Web Vitals thresholds, measured at the 75th percentile of real page loads, separately for mobile and desktop (web.dev):

• Largest Contentful Paint: 2.5 seconds or less
• Interaction to Next Paint: 200 milliseconds or less
• Cumulative Layout Shift: 0.1 or less

On Shopify, the usual causes of a slow store are app scripts, oversized hero images, and third-party widgets loading before the product. We cover the fixes step by step in our Shopify Core Web Vitals guide.

2. Product page: reviews

Reviews have the most published evidence of any product page element, with one honest caveat we will get to.

Northwestern's Spiegel Research Center found that the purchase likelihood for a product with five reviews is 270% greater than for a product with none, and that the marginal benefit falls off quickly after the first five. Reviews matter more as price rises: displaying reviews lifted conversion 190% for a lower-priced product and 380% for a higher-priced one. And a perfect score is not the goal. Purchase likelihood peaks at ratings between 4.0 and 4.7, then drops as the rating approaches 5.0. A verified-buyer badge improved the odds of purchase by 15% (Spiegel Research Center).

PowerReviews' survey data fills in the shopper's side. In a June 2025 survey of 21,279 consumers, 95% said they regularly read product reviews, and only 43% said they would buy a product with zero ratings or reviews (PowerReviews). In its earlier review volume and recency study (more than 9,000 consumers and 1.5 million product pages, published December 2021), 45% of consumers said a product needs a minimum of 1 to 25 reviews before they feel comfortable buying, and 38% said they would not buy if the only reviews were three or more months old (PowerReviews).

Bazaarvoice reports a 144% lift in conversion rate and a 162% lift in revenue per visitor among shoppers who engage with user-generated content such as reviews, from its Shopper Experience Index (Bazaarvoice).

The caveat: figures like Bazaarvoice's compare shoppers who read reviews with shoppers who do not. People who stop to read reviews were already more likely to buy. So do not expect a 144% lift from installing a review app. What the combined evidence does support is this:

• Get every product to at least five reviews. That is where the steepest gain is.
• Keep them recent. A steady trickle beats a large, stale pile.
• Show the negative ones. Purchase likelihood peaks below a perfect score.
• Mark verified buyers.

3. Product page: photography, shipping, and returns

Baymard's 2026 product page benchmark found that 52% of leading desktop ecommerce sites and 62% of mobile sites have a "mediocre" or worse product page experience (Baymard). These are large retailers. The same gaps show up on D2C stores, and each one is fixable.

• Show scale. In Baymard's testing, 42% of users try to judge a product's size from its images, yet 37% of sites do not provide an "in scale" image. Add one photo of the product in a hand, on a body, or in a room.
• Show the delivered cost near the buy button. 67% of sites give no total order cost estimate near the buy section. State shipping cost or your free shipping threshold on the product page.
• Link the returns policy from the product page. In a Baymard study of 1,032 respondents, 60% said they look for return policy information on the product page. 44% of sites do not show or link it there.
• Use buttons for size and variant selection. 57% of sites do not, and dropdowns hide options and stock status.

None of these needs a redesign. They are content and theme-setting changes.

4. Cart and checkout

Baymard surveys US shoppers on why they abandoned a cart in the past three months. After removing the 42% who were just browsing, these are the reasons, from its latest survey of more than 1,000 shoppers.

Reason for abandoning	Share of respondents	Who controls the fix
Extra costs too high (shipping, tax, fees)	40%	You: pricing, thresholds, early disclosure
Delivery was too slow	20%	You: fulfillment, delivery date messaging
Did not trust the site with card information	19%	You: trust signals, known payment methods
The site wanted me to create an account	18%	You: guest checkout
Too long or complicated checkout	17%	You: form fields, steps
Website had errors or crashed	17%	You: QA, app conflicts
Returns policy was not satisfactory	13%	You: policy and where it is shown
Could not see or calculate total cost up front	12%	You: cart and product page
Credit card was declined	10%	Partly: payment options, retries
Not enough payment methods	9%	You: wallets, local methods

Source: Baymard Institute, cart abandonment rate statistics, page updated October 28, 2026. Respondents could choose more than one reason.

Every row but one is fully in your hands. Baymard estimates that the average large ecommerce site can gain a 35.26% increase in conversion rate through better checkout design alone. That figure comes from audits of sites like Walmart, Wayfair, and ASOS. It is a ceiling for sites with many checkout flaws, not a forecast for yours. The specific fixes are what matter.

Show costs before checkout. Extra costs are the top avoidable reason at 40%, and another 12% left because they could not see the total up front. Put shipping cost or the free shipping threshold on the product page and in the cart, with a progress indicator toward the threshold.

Make guest checkout the obvious path. 18% of abandoners left because the site wanted an account. Baymard's benchmark found that 47% of sites offering guest checkout do not make it the most prominent option (Baymard), and 56% do not save account creation for the confirmation step (Baymard). Offer account creation after the order is placed, when it costs the shopper one password field.

Cut form fields. The average US checkout shows 23.48 form elements by default, 14.88 of them form fields. Baymard's testing shows an ideal flow needs 12 to 14 elements, or 7 to 8 fields. Most checkouts can cut 20% to 60% of what they show. Start with the phone number: 68% of respondents in a Baymard survey are reluctant to give one at checkout, and 47% of sites that require it do not explain why.

Turn on an express wallet. Shopify publishes the strongest numbers here. An external study completed with a Big Three management consulting firm in April 2023 found that Shop Pay converts as much as 50% better than guest checkout, outpaces other accelerated checkouts by at least 10%, and that its presence alone lifts lower-funnel conversion by 5% (Shopify). The same study found Shopify's checkout overall converts 15% better on average than competing platforms (Shopify). This is vendor-published data about the vendor's own product, so weigh it accordingly. The mechanism is sound, though: a wallet removes address entry, card entry, and the account question in one step, which addresses three rows of the Baymard table at once.

Address card trust directly. 19% of abandoners did not trust the site with their card details, in a Baymard survey of 1,026 US adults in 2025 (Baymard). Recognizable payment options and a visually distinct, secure-looking card section do more here than a row of badges in the footer.

On Shopify, most of this is configuration, not development. Our Shopify checkout audit walkthrough lists the settings to check. On WooCommerce, checkout is yours to build and maintain, which gives you more control and more ways to break it. If your WooCommerce checkout has grown extra fields and plugin conflicts over the years, that is typical WooCommerce development work.

Recover what still leaves. Some abandonment is recoverable after the session. Klaviyo's analysis of more than 110,000 customers found abandoned cart flows earn the highest revenue per recipient of any automated flow, averaging $6.77 for email and $4.48 for SMS, with an average email click rate of 6% (Klaviyo). Our abandoned cart recovery guide covers timing and sequence.

5. Trust and returns policy

Returns policy shows up twice in the evidence. It is a reason people abandon (13% in Baymard's list), and it is something shoppers check before they buy.

The National Retail Federation and Happy Returns estimate that 19.3% of online sales will be returned in 2025, and report that 82% of consumers say free returns are an important consideration when shopping online (NRF).

You do not have to offer free returns to benefit. You have to make the policy easy to find and easy to understand before checkout. Put a one-line summary next to the add-to-cart button ("30-day returns, see policy") and link the full page. A clear, fair policy that shoppers can see converts better than a generous one buried in the footer. Whether free returns pay for themselves is a margin question, which the unit economics guide covers.

6. Shipping thresholds and order value

Shipping is the single largest avoidable cause of abandonment, so how you present it matters more than almost any design choice.

A free shipping threshold does two jobs. It removes the top objection for orders above the line, and it gives shoppers below the line a reason to add one more item. According to an AlixPartners study cited by Shopify, 56% of retailers require a minimum order value for free shipping (Shopify).

Set the threshold from your own order data, not from a competitor's banner. A threshold slightly above your current average order value pulls orders up. One set far above it reads as "shipping is not free" and does nothing. We walk through the math in our free shipping threshold guide.

Remember the revenue-per-session point from earlier. A threshold that lifts order value 10% while conversion holds steady is worth exactly as much as a 10% conversion lift, and it is usually easier to get.

Mobile-specific fixes

With around two-thirds of Shopify sessions on phones, mobile deserves its own pass.

Baymard's 2026 mobile benchmark rates 75% of mobile ecommerce sites as only "mediocre," and just one site in the benchmark as "good" (Baymard). The specific gaps it documents are a ready-made checklist:

• Address entry. 54% of mobile sites have no address validator or lookup. Typing an address on a phone is the slowest part of checkout. Turn on address autocomplete.
• Error messages. 93% do not use adaptive validation messages that tell the user what is wrong with the specific input. Test your checkout by entering a bad phone number and a mistyped email.
• Variant visibility. 73% do not show all color swatches in mobile product lists for visually driven products. Shoppers assume the color they want does not exist.
• Search. 27% do not put a submit button next to the mobile search field.

Then test the path yourself. On your own phone, on cellular data, go from an ad to a completed order. Time it. Count the taps. Note every moment you had to pinch, scroll sideways, or wait. Most founders have not done this in months, and it is the cheapest research you can run.

The Littledata device data gives you a specific number to watch: mobile add-to-cart rate. The Shopify median is 5.3%. If yours is under 3%, your mobile product page is the first thing to fix.

How to A/B test honestly with low traffic

Most D2C stores do not have enough traffic to A/B test most changes. That is not a failing. It is arithmetic, and knowing it saves you months of misleading "wins."

The sample size math

To detect a lift reliably, you need enough sessions in each variant that the difference could not plausibly be noise. The standard settings are 95% significance and 80% power. The table shows the sessions needed per variant under those settings.

Baseline conversion rate	Detect a 10% relative lift	Detect a 20% relative lift	Detect a 30% relative lift	Detect a 50% relative lift
1.0%	163,095	42,693	19,827	7,750
1.3%	125,058	32,731	15,198	5,939
2.0%	80,682	21,109	9,798	3,826
3.0%	53,211	13,914	6,455	2,518
5.0%	31,234	8,158	3,780	1,471

Sessions per variant, two-sided test, 5% significance, 80% power, calculated with the standard two-proportion sample size formula. Double each figure for a two-variant test. A "10% relative lift" on a 2.0% baseline means moving to 2.2%. Calculators such as Evan Miller's sample size tool take the same inputs (baseline rate, minimum detectable effect, power, significance) and give comparable results.

Now apply it. Your store gets 30,000 sessions a month and converts at 2.0%.

• To detect a 10% lift (2.0% to 2.2%): 80,682 x 2 = 161,364 sessions. That is 5.4 months of all your traffic.
• To detect a 20% lift (2.0% to 2.4%): 21,109 x 2 = 42,218 sessions. About six weeks.
• To detect a 50% lift (2.0% to 3.0%): 3,826 x 2 = 7,652 sessions. About eight days of traffic, though you should still run full weeks.

A store with 10,000 sessions a month at 1.3% needs 65,462 sessions to detect a 20% lift. That is six and a half months for one test.

A single copy or layout change rarely moves purchases by 20%. So for most stores under about 50,000 sessions a month, classic A/B testing of the final purchase rate can only confirm big swings.

Why peeking breaks your test

The second trap is stopping early. Evan Miller's well-known note on the subject explains that significance calculations assume the sample size was fixed in advance. If you run a test "until it is significant," the reported confidence level stops meaning what it says (Evan Miller).

CXL describes a simulation that makes this concrete. One thousand A/A tests were run, two identical pages against each other. With repeated checking, 531 of the 1,000 reached 95% significance at some point. When the sample size was fixed in advance, only 51 did (CXL). Same pages. No real difference. More than half looked like winners to anyone who stopped at the first green light.

CXL's practical rules, from the same article: ignore results with fewer than 250 to 350 conversions per variation, and run tests for at least one and preferably two full business cycles. The author runs most tests for at least four full weeks.

What to do instead when you cannot test

Ship best practice without a test. If your checkout forces account creation, hides shipping costs until the last step, or has no wallet button, you do not need an experiment. The evidence in the Baymard table is the test. Fix it and watch the trend.

Test a higher-frequency metric. Add-to-cart happens about five times as often as purchase. At a 6.6% add-to-cart baseline, detecting a 20% relative lift takes 6,065 sessions per variant, or 12,130 in total. A product page test that would take six months on purchases can read in weeks on add-to-carts. Check that purchases did not move the wrong way before you keep the change.

Test bold changes only. A new offer structure, a different hero product, or a rebuilt product page can produce a 30% to 50% swing, which is detectable. A button color cannot.

Use before-and-after with care. Compare four full weeks before a change with four full weeks after, on the same traffic mix, avoiding sales and holidays. It is weaker evidence than a controlled test. Say so when you report it.

Watch real shoppers. Five session recordings of abandoned checkouts will show you problems no statistical test will. Qualitative evidence does not need a sample size.

What should you measure every week?

One table, same day each week, same tool. Fifteen minutes.

Metric	How to calculate	Reference point (Shopify median)	Why it is on the list
Sessions	From your source-of-truth tool	Your own trend	Context for everything below
Conversion rate	Orders / sessions	1.3%	The headline
Add-to-cart rate	Sessions with add to cart / sessions	6.6%	Product page and traffic quality
Checkout completion	Orders / checkout starts	47%	Checkout health
Average order value	Revenue / orders	$111	Offer and threshold health
Revenue per session	Revenue / sessions	$1.98	The number that pays the bills
Mobile conversion rate	Mobile orders / mobile sessions	1.5%	Where most of your traffic is
Conversion rate by channel	Orders / sessions per channel	Your own trend	Separates site problems from mix shifts

Reference points: Littledata Shopify benchmarks, 90 days to October 31, 2026.

Two rules for reading it.

First, look at channels before you look at the blended number. If blended conversion fell and every channel held steady, your mix shifted. Nothing is broken.

Second, weekly numbers are noisy at low volume. A store with 60 orders a week will routinely move 10% to 15% from chance alone. Use the weekly check to catch breakage (a dead payment method, a broken discount, a tracking outage). Make decisions on four-week and twelve-week trends.

A 30-day conversion plan

This plan assumes a Shopify or WooCommerce store with at least a few hundred orders a month. It uses only the verified fixes above, in order of effort.

Week 1: Measure and diagnose

1. Pick your source-of-truth tool. Confirm conversion rate is orders divided by sessions, with purchases only.
2. Pull the five funnel numbers for the last 90 days: sessions, product views, add-to-carts, checkout starts, orders. Split by mobile and desktop.
3. Compare each stage with the percentile table. Mark the stage furthest below the median. That is your focus.
4. Split conversion rate by channel and by new versus returning. Note which channels changed in volume over the last quarter.
5. Complete one purchase on your own phone over cellular data. Write down every point of friction.

Week 2: Cart and checkout quick wins

1. Make guest checkout the default. Move account creation to after the order.
2. Turn on every express wallet your platform supports.
3. Remove optional checkout fields. Make phone number optional or explain why you need it.
4. Show shipping cost or the free shipping threshold on the product page and in the cart.
5. Confirm your abandoned cart flow is live, and send yourself a test.

Week 3: Product pages and speed

1. Take your top ten products by sessions. For each one, check for: at least five reviews, an in-scale image, delivered cost near the buy button, a returns line with a link, and variant buttons instead of dropdowns.
2. Request reviews from recent buyers of any top product with fewer than five.
3. Check Core Web Vitals for your product template on mobile. If Largest Contentful Paint is above 2.5 seconds, compress the lead image and remove or defer the heaviest third-party scripts.
4. Remove apps you no longer use. Each one can leave scripts behind.

Week 4: Verify and plan

1. Recheck the funnel numbers for the changed weeks against the prior four weeks, by channel.
2. Keep what moved the target stage without hurting revenue per session. Revert anything that clearly hurt.
3. Run the sample size math for your traffic. Decide whether your next change is testable or should simply ship.
4. Choose the next weakest stage and repeat.

If you are still pre-launch, most of this belongs in the build itself. Our D2C launch guide covers what to have in place on day one.

Common conversion rate myths

"A good conversion rate is 2% to 3%." That range describes averages weighted toward bigger brands. The median Shopify store is at 1.3%, and 2.7% is already top 20%. A new apparel store at 1.2% is above its category median.

"Higher conversion is always better." A sitewide 30% off sale will lift conversion and can destroy margin. Scaling cold traffic will cut conversion and can grow profit. Judge conversion alongside revenue per session and contribution margin.

"Our cart abandonment rate is 75%, so checkout is broken." The cross-study average is 70.22%, the Shopify median is 79%, and 42% of shoppers abandon because they were only browsing. Look at checkout completion instead. It isolates shoppers who showed real intent.

"Mobile always converts worse than desktop." In cross-industry data, yes. Across Shopify stores in Littledata's 2026 data, median mobile conversion is slightly above desktop. Check your own split before assuming.

"We ran a test and got a 30% lift in a week." With a few hundred sessions per variant, that result is far more likely noise than signal. In the CXL simulation, more than half of tests between identical pages looked significant at some point.

"Trust badges fix trust." What Baymard's research supports is clear total cost, recognizable payment methods, a visible returns policy, and a card form that looks secure. A badge in the footer alone addresses none of the cost, delivery, or account reasons at the top of the list.

"Speed only matters for SEO." The Deloitte and Google study measured conversions and order value directly, and the Vodafone and Rakuten 24 tests were controlled experiments on sales. Speed is a conversion lever first.

"You need more traffic." If your add-to-cart rate is in the bottom 20%, more traffic buys more of the same leak. Fix the weakest stage, then scale.

Where to go from here

Start with measurement. Calculate your rate from orders and sessions in one tool. Find your percentile. Find the weakest stage. Fix the cheapest evidence-backed problem at that stage. Check the trend after four weeks. That loop, repeated, is conversion rate optimization. It does not require a testing platform or a redesign.

If you want a second pair of eyes on where your store is leaking, our free website audit covers speed, product pages, and checkout. And if you would rather hand the whole loop off, that is what our Shopify growth work is for. WitsCode has shipped 300+ websites since 2019. We will not promise you a lift percentage. We will show you which stage is leaking and fix it in order of evidence.

Sources and methodology

Every figure in this guide was read at its source in November 2026. Where a source reports another organization's data, both are named. Benchmarks are session-based unless stated otherwise. Worked examples use illustrative store numbers and are labeled as such. Sample sizes were calculated with the standard two-proportion formula at 5% two-sided significance and 80% power.

1. Baymard Institute, cart abandonment rate statistics. 70.22% average of 50 studies (2006 to 2025), range 55% to 84%, reasons for abandonment, 42% just browsing, 23.48 form elements and 14.88 fields versus 12 to 14 and 7 to 8 ideal, 35.26% checkout design potential. baymard.com (page updated October 28, 2026; accessed November 2026)
2. Baymard Institute, Checkout UX 2026. 56% of sites do not save account creation for the confirmation step, 68% reluctant to give a phone number, 47% do not explain the phone field. baymard.com (accessed November 2026)
3. Baymard Institute, guest checkout prominence. 47% of sites do not make guest checkout the most prominent option. baymard.com (accessed November 2026)
4. Baymard Institute, perceived security of payment forms. 19% abandoned over card trust, 1,026 US respondents, 2025. baymard.com (accessed November 2026)
5. Baymard Institute, product page UX benchmark. 52% desktop and 62% mobile "mediocre or worse," in-scale images, total cost near buy section, return policy on product page, size buttons. baymard.com (accessed November 2026)
6. Baymard Institute, mobile UX benchmark 2026. 75% of mobile sites "mediocre," address validation, adaptive errors, swatches, search submit. baymard.com (accessed November 2026)
7. Littledata, Shopify benchmarks. All percentile data for conversion rate, add-to-cart rate, checkout completion, cart abandonment, bounce rate, average order value, revenue per session, mobile share. 438 Shopify stores, August 3 to October 31, 2026, generated November 4, 2026. littledata.io (accessed November 2026)
8. Littledata, conversion rate benchmark. Mean 1.9%, industry medians, mobile versus desktop. littledata.io (accessed November 2026)
9. Littledata, add-to-cart rate benchmark. Device and industry splits. littledata.io (accessed November 2026)
10. Littledata, checkout completion rate benchmark. Device and industry splits. littledata.io (accessed November 2026)
11. Littledata, cart abandonment rate benchmark. Median 79%, best 20% under 65%. littledata.io (accessed November 2026)
12. Statista, conversion rate of online shoppers worldwide. 1.6% global in Q3 2026, Switzerland 1.9%, smartphone share of visits and orders in Q1 2026. Source data credited to Salesforce Research. statista.com (updated November 6, 2026; accessed November 2026)
13. Statista, online shopping conversion rate by vertical. Food and beverage 3.8%, health and beauty 2.6%, skincare 1.9%, Q3 2026. statista.com (accessed November 2026)
14. IRP Commerce, ecommerce market data. Conversion rate, average order value, device, channel, and location splits for all markets and ten individual markets, September 2026 versus September 2025. irpcommerce.com (accessed November 2026)
15. Shopify, Ecommerce Conversion Rate: Benchmarks and Tips (2026). Definition and sessions-versus-users guidance, Dynamic Yield 2.66% and June 2026 industry figures, Statista Q1 2026 figure of 1.4%, Contentsquare retail device rates, Shopify Q4 2025 store owner survey. shopify.com (updated August 22, 2026; accessed November 2026)
16. Shopify, Shop Pay. Up to 50% better conversion than guest checkout, at least 10% above other accelerated checkouts, 5% lower-funnel lift from presence, April 2023 external study. shopify.com (accessed November 2026)
17. Shopify, checkout conversion study. Shopify checkout converts 15% better on average than competitors. shopify.com (accessed November 2026)
18. Shopify, free shipping strategies. AlixPartners finding that 56% of retailers require a minimum order for free shipping. shopify.com (published September 26, 2026; accessed November 2026)
19. Contentsquare, 2026 Digital Experience Benchmarks, conversions. New versus returning conversion, desktop versus mobile gap, paid search, AI-referred and organic social conversion. 99 billion sessions, 6,000+ sites. contentsquare.com (published March 9, 2026; accessed November 2026)
20. Contentsquare, 2026 Digital Experience Benchmarks, traffic. Mobile share 69.9%, paid share 42%, channel shares, return visits 52.8%. contentsquare.com (accessed November 2026)
21. Unbounce, ecommerce conversion benchmark report. Landing-page medians by channel. unbounce.com (published August 2024; accessed November 2026)
22. Klaviyo, 2026 email marketing benchmarks. Flows produce nearly 41% of email revenue from 5.3% of sends, 183,000+ customers. klaviyo.com (accessed November 2026)
23. Klaviyo, 2026 abandoned cart flow benchmarks. $6.77 email and $4.48 SMS revenue per recipient, 6% email click rate, 110,000+ customers. klaviyo.com (published October 2, 2026; accessed November 2026)
24. Deloitte, Milliseconds Make Millions. Retail conversions up 8.4% and order value up 9.2% for a 0.1 second mobile speed improvement. deloitte.com (published 2020; accessed November 2026)
25. web.dev, Milliseconds Make Millions summary. Stage progression rates, 37 brands, 30 million sessions, late 2019. web.dev (accessed November 2026)
26. web.dev, Vodafone case study. 31% better LCP, 8% more sales, A/B test. web.dev (accessed November 2026)
27. web.dev, Rakuten 24 case study. A/B test, 33.13% conversion rate and 53.37% revenue per visitor improvement. web.dev (accessed November 2026)
28. web.dev, Web Vitals. Core Web Vitals thresholds and 75th percentile rule. web.dev (accessed November 2026)
29. Spiegel Research Center, Northwestern University, How Online Reviews Influence Sales. 270% for five reviews, 190% versus 380% by price, 4.0 to 4.7 rating peak, 15% verified buyer effect. spiegel.medill.northwestern.edu (accessed November 2026)
30. PowerReviews, review volume and recency. Minimum review counts, recency thresholds, 9,000+ consumers. powerreviews.com (published December 2021; accessed November 2026)
31. PowerReviews, Complete Guide to Ratings and Reviews. June 2025 survey of 21,279 consumers: 95% regularly read reviews, 43% would buy with zero reviews. powerreviews.com (accessed November 2026)
32. Bazaarvoice, Shopper Experience Index figures. 144% conversion and 162% revenue per visitor lift among shoppers engaging with user-generated content. bazaarvoice.com (published February 2023; accessed November 2026)
33. National Retail Federation and Happy Returns, 2025 Retail Returns Landscape. 19.3% of online sales returned, 82% say free returns matter. nrf.com (published October 15, 2025; accessed November 2026)
34. CXL, Stopping A/B Tests. A/A simulation (531 versus 51 of 1,000), 250 to 350 conversions per variation, test duration guidance. cxl.com (accessed November 2026)
35. Evan Miller, How Not To Run an A/B Test. Fixed sample size requirement. evanmiller.org (accessed November 2026)
36. Evan Miller, Sample Size Calculator. Reference calculator for the sample size inputs. evanmiller.org (accessed November 2026)
37. Google Analytics Help, dimensions and metrics. Definitions of session key event rate and user key event rate. support.google.com (accessed November 2026)
38. Google Analytics Help, sessions. 30-minute default session timeout. support.google.com (accessed November 2026)