E-commerce Statistics at a Glance
The figures below come from original, publicly available sources published in 2025–2026. Each is based on a distinct measurement with a defined scope.
Ecommerce does not have one universal market definition. B2C retail sales, B2B business ecommerce, marketplace gross merchandise value (GMV), and platform revenue are different things. The $28 trillion UNCTAD business ecommerce figure, for example, covers broad business transactions — not just consumer online retail. Always read the source before citing a headline number.
E-commerce Market Size Statistics
The first question most people ask — "how big is ecommerce?" — does not have a single answer. The total depends entirely on which transactions you count and which countries you include. The table below shows the main measurement categories so you can match a number to its actual scope.
| Market measure | What it includes | Example sources |
|---|---|---|
| B2C online retail sales | Consumer purchases ordered through a website or app | US Census Bureau, Eurostat |
| Total business ecommerce | Digitally ordered sales across eligible business sectors, including B2B | UNCTAD |
| Gross merchandise value (GMV) | Gross transaction value flowing through a marketplace platform | Platform financial filings |
| Net revenue | Recognized revenue after returns, discounts, and accounting adjustments | Company earnings reports |
| Ecommerce share of retail | Online retail sales divided by comparable total retail sales | US Census Bureau |
These categories should never be combined into one headline figure without disclosing what each covers.
Global Business Ecommerce — UNCTAD
This figure includes business-to-business transactions alongside consumer sales. It represents measured economies, not the entire world, and is substantially broader than standard B2C retail market estimates. Do not describe it as "global online retail sales reached $28 trillion."
US Ecommerce Market Size
This is a quarterly figure, not an annual total. The Census release notes that these estimates are subject to superseding revisions. Seasonally adjusted figures account for typical seasonal variation; they should not be compared directly to unadjusted quarterly figures.
The Census Bureau releases quarterly ecommerce estimates as part of its Quarterly Retail E-Commerce Sales series. The US share of retail sales has climbed from under 1% in 2000 to 17.1% in Q2 2026, but that growth includes periods of unusual acceleration — notably the pandemic surge of 2020 — followed by partial normalization as physical retail reopened.
The Census Bureau publishes both seasonally adjusted and not seasonally adjusted (NSA) ecommerce figures. Q4 results are always higher due to holiday spending, which distorts year-over-year comparisons if you mix the two series. The 17.1% Q2 2026 share comes from the adjusted series. Always check which version a source uses before making growth comparisons.
Ecommerce Share of Retail Over Time
The table below shows US ecommerce as a share of total retail, using Census Bureau data. The pandemic years (2020–2021) accelerated adoption, and the share has since stabilized at a structurally higher level than pre-2020.
| Year / Period | Ecommerce share of US retail (approx.) | Basis |
|---|---|---|
| 2019 (full year) | ~11.0% | Census, annual estimate, not seasonally adjusted |
| 2020 (full year) | ~14.0% | Census, annual — pandemic-driven surge |
| 2021 (full year) | ~13.2% | Census, annual — partial reversion as stores reopened |
| 2022 (full year) | ~14.6% | Census, annual estimate |
| 2023 (full year) | ~15.4% | Census, annual estimate |
| Q2 2026 | 17.1% | Census, seasonally adjusted quarterly estimate |
Note: Pre-2026 annual figures use not-seasonally-adjusted annual estimates for comparability with full-year totals. The Q2 2026 figure is seasonally adjusted. Census data is subject to revision. Verify current figures directly at census.gov/retail/ecommerce.html.
A 17.1% share of retail means ecommerce accounts for 17.1 cents of every retail dollar. It does not mean ecommerce sales grew 17.1%. If ecommerce share rises from 15% to 17%, that is a gain of 2 percentage points — roughly 13% relative growth. These are entirely different numbers describing different things.
E-commerce Conversion Rate Statistics
Conversion rate is the most cited ecommerce performance metric and the most frequently misquoted. The number means nothing without knowing what counts as a conversion, what the denominator is, and whose stores were measured.
A purchase session is one in which at least one transaction was completed. Other definitions — orders divided by sessions, or purchasers divided by users — yield different numbers. Always confirm which formula a source uses before comparing figures across platforms.
Median Store Conversion Rate
This is a median — the midpoint store in the sample distribution — not an average weighted by transaction volume. The top 20% of stores in the sample converted at 2.7% or above; the top 10% at 3.6% or above. These figures apply to this specific Shopify sample and should not be generalized to all ecommerce formats.
| Performance threshold | Conversion rate | Source |
|---|---|---|
| Bottom 20% of stores | Below ~0.6% | Littledata, Oct 2026 |
| Median store | 1.4% | Littledata, Oct 2026 |
| Top 20% of stores | 2.7% or above | Littledata, Oct 2026 |
| Top 10% of stores | 3.6% or above | Littledata, Oct 2026 |
What counts as a good conversion rate depends heavily on product category, price point, purchase frequency, traffic source, and the experience a store provides. A fashion accessory store with impulse-purchase pricing may convert at 3–4%; a high-consideration electronics retailer may perform well at 0.5–1% because shoppers spend longer researching before committing.
Conversion Rate by Device
The narrow gap between devices in this sample does not mean mobile universally outperforms desktop. Store mix, product category, audience intent, and whether traffic is app-based or mobile web all affect the comparison. Historically, desktop has converted at higher rates in many segments because of larger screen size and checkout familiarity; the gap has narrowed as mobile checkouts improved.
| Metric | Mobile | Desktop | Source / Note |
|---|---|---|---|
| Median conversion rate | 1.6% | 1.5% | Littledata, Oct 2026; Shopify stores, GA4 |
| Share of holiday transactions (US) | 56.4% | ~43.6% | Adobe Analytics, Nov–Dec 2025 US holiday period |
| Traffic share | Majority of visits in most markets | Minority of visits | Varies widely by market and category |
Revenue share and transaction share can differ from visit share because average order values tend to be higher on desktop in many categories, partially offsetting desktop's lower share of overall traffic.
Mobile vs Desktop E-commerce Statistics
Mobile commerce has passed desktop in share of transactions in major markets, but the two channels still differ in conversion behavior, average order value, and session intent.
Mobile Traffic
Mobile accounts for the majority of website visits across most ecommerce categories, driven by social and search traffic on smartphones.
Mobile Transactions
Adobe reported 56.4% of US holiday season transactions (Nov–Dec 2025) completed via smartphone — a share that has grown each year.
Desktop Revenue
Desktop's lower visit share is partially offset by higher average order values in categories like electronics, furniture, and travel.
Apps vs Mobile Web
App users tend to convert at higher rates than mobile web visitors, but this reflects self-selection — frequent buyers are more likely to install an app.
This figure measures transaction share (orders), not visit share or revenue share, during the US holiday period only. It should not be generalized to all ecommerce transactions year-round or to other countries.
Defining Mobile Metrics Precisely
Three measures that are often confused in ecommerce reporting:
These three numbers can differ substantially. A store can have 70% mobile traffic but only 45% mobile revenue if desktop sessions produce higher average order values.
Online Shopping Consumer Behavior Statistics
The DHL Ecommerce Trends Report 2026 surveyed 29,000 online shoppers across 29 countries and 5,800 ecommerce businesses. It provides the broadest available cross-market view of consumer behavior for 2026. Survey responses reflect what people say they do and expect — they are not the same as observed transaction logs, which is an important distinction when reading the figures below.
Delivery Expectations
Delivery speed and cost are among the most powerful factors in purchase decisions. DHL's 2026 research found that unexpected shipping costs at checkout remain the most common reason shoppers abandon a purchase — a finding consistent across its 2025 survey (24,000 shoppers, 24 markets) and 2026 wave.
- Shipping cost transparency: Unexpected fees at checkout are the top stated reason for abandoning a purchase across most surveyed markets.
- Free delivery preference: The majority of survey respondents across markets say free delivery influences their choice of retailer.
- Delivery speed: Same-day or next-day delivery is expected by a growing share of shoppers, particularly in urban areas of high-income markets.
- Flexible delivery: Shoppers increasingly want options — specific time slots, pickup points, and rescheduling — rather than a fixed delivery window.
- Tracking: Real-time parcel tracking is now a baseline expectation in most surveyed countries, not a premium feature.
Trust and Security in Online Shopping
Consumer trust affects both conversion rates and average order value. Shoppers who trust a retailer spend more per visit and are more likely to complete checkout. DHL's research identifies several factors that build and erode trust across markets.
| Trust factor | Consumer behavior impact | Note |
|---|---|---|
| Clear returns policy | Reduces purchase hesitation; raises conversion likelihood | Effect varies by product category and price |
| Recognizable payment options | Missing preferred payment method triggers abandonment | Top reason cited in Baymard checkout studies |
| Security signals (SSL, badges) | Particularly significant for new or unfamiliar retailers | Self-reported; causal impact harder to isolate |
| Customer reviews | Shoppers use social proof to reduce perceived risk | Effect stronger for higher-priced items |
| Forced account creation | A friction point that increases checkout abandonment | Baymard identifies this as a top abandonment driver |
Social Commerce
Social commerce — purchasing directly through social media platforms — has grown consistently in DHL's annual research. The 2026 survey found that a growing share of shoppers report discovering and buying products through social platforms, with the trend most pronounced among consumers under 35. However, reported future intent to use social commerce consistently exceeds actual measured social commerce transaction shares, so survey-based projections should be read as directional rather than precise forecasts.
Shopping Cart Abandonment Statistics
Cart abandonment is one of the most discussed metrics in ecommerce, and one of the most easily misread. A high abandonment rate does not necessarily mean the same as a high volume of recoverable lost sales — many visitors add items to a cart as part of browsing, price research, or wishlist behavior, with no immediate intention to purchase.
The component studies span different years, markets, and methodologies. Some measure cart abandonment; others measure checkout session abandonment — which uses a different denominator. The 70.22% figure is best understood as an aggregate of published research rather than a direct census of global checkouts in 2026. Treat it as an industry reference point, not a precise measurement of your store's potential.
Cart Abandonment Formula
Abandoned carts = initiated carts with no completed purchase
Initiated carts = sessions with at least one item added
Checkout abandonment uses a different denominator: checkout sessions started but not completed. Cart abandonment rate is always higher than checkout abandonment rate because it captures a broader funnel stage.
Why Shoppers Abandon Carts
Baymard's research distinguishes between passive abandonment (browsing without purchase intent) and active abandonment caused by checkout friction. In their large-scale UX studies, extra costs — shipping fees, taxes, and other charges disclosed only at checkout — appear as the leading driver of active abandonment.
| Reason for abandonment | Evidence type | Source |
|---|---|---|
| Extra costs (shipping, taxes) too high, disclosed late | Consumer survey, UX research | Baymard Institute |
| No guest checkout — forced account creation | Consumer survey | Baymard Institute |
| Long or complicated checkout process | UX usability study | Baymard Institute |
| Couldn't see or calculate total cost upfront | Consumer survey | Baymard Institute |
| Website errors or crashes | Consumer survey | Baymard Institute |
| Didn't trust the site with payment details | Consumer survey | Baymard Institute |
| Delivery too slow | Consumer survey | Baymard Institute / DHL |
| Preferred payment method unavailable | Consumer survey | Baymard Institute |
| Browsing or researching, no immediate intent | Behavioral estimate | Baymard Institute |
Note: Survey respondents often select multiple reasons, so percentages in multi-select surveys should not be added to 100%. The reasons above are ranked by frequency reported across Baymard's research, not as precise single-select percentages.
Adding an item to a cart and beginning checkout are different stages. Cart abandonment is measured from the first add-to-cart event. Checkout abandonment is measured only from when a shopper begins the payment process. Checkout abandonment rates are typically in the 35–55% range — far lower than the ~70% cart figure — because checkout sessions already reflect higher purchase intent.
Average Order Value and Checkout Metrics
Average Order Value (AOV)
AOV varies enormously by category. A health supplement store, a luxury watch retailer, and a grocery delivery service will have very different AOVs even with similar conversion rates. Littledata publishes AOV benchmarks alongside its conversion data for Shopify stores; check its current reports for category-level figures.
Ecommerce Conversion Funnel
The full purchase funnel moves through several stages, each with its own drop-off rate. These are distinct metrics that require different denominators.
| Funnel stage | Typical metric | Denominator |
|---|---|---|
| Visit → Product view | Product view rate | Sessions |
| Product view → Add to cart | Add-to-cart rate | Product-view sessions |
| Add to cart → Checkout start | Cart-to-checkout rate | Sessions with a cart item |
| Checkout start → Purchase | Checkout completion rate | Sessions with a checkout started |
| Session → Purchase | Purchase conversion rate | All sessions |
The session-level conversion rate (the 1.4% median) measures the last row. You cannot derive accurate funnel-stage rates simply from the overall session conversion figure.
E-commerce Payment Statistics
Payment method availability directly affects checkout abandonment. A shopper whose preferred payment option is absent at the final step will frequently leave. DHL's 2026 survey and the Worldpay Global Payments Report both track payment preferences across markets, though they use different samples and geographies.
- Digital wallets (Apple Pay, Google Pay, PayPal) have grown into the most-used payment method by transaction count in several major markets, overtaking credit cards for online purchases.
- Credit and debit cards remain dominant by payment value in most Western markets, particularly for higher-ticket purchases.
- Buy Now Pay Later (BNPL) has grown significantly in the under-35 demographic. Adobe reported BNPL driving record use during the 2025 US holiday season.
- Local payment preferences vary widely. Countries like Germany favor bank transfers; parts of Southeast Asia have high cash-on-delivery usage; China's market is dominated by domestic digital wallet systems.
- Transaction count vs transaction value can diverge: wallets may account for the majority of orders but a smaller share of total payment value if used more frequently for lower-cost purchases.
E-commerce Delivery and Shipping Statistics
Delivery logistics sit at the intersection of consumer expectations and operational cost. The gap between what shoppers want and what retailers can profitably provide has driven widespread adoption of free shipping thresholds, loyalty-based perks, and alternative delivery models.
| Shipping factor | Consumer expectation (DHL 2026) | Business reality |
|---|---|---|
| Shipping cost | Free delivery strongly preferred; willingness to pay extra for speed varies by country | Free shipping has a cost; retailers recover it through minimum order thresholds or membership models |
| Delivery speed | Same-day or next-day expected by a growing share in high-income markets | Fulfillment infrastructure limits rapid delivery outside major urban centers |
| Tracking | Real-time updates are now a baseline expectation, not a premium | Carrier integrations required; gaps in visibility erode trust |
| Delivery flexibility | Preferred time slots, pickup lockers, and rescheduling increasingly expected | Last-mile logistics cost and infrastructure vary significantly by market |
Ecommerce Returns Statistics
Online return rates run higher than in-store because buyers cannot see, touch, or try products before purchasing. Fashion and apparel categories have the highest return rates; digital goods and perishables have the lowest (or no returns).
Online returns run higher than the overall retail average because customers cannot inspect products before purchase. The 19.3% rate applies to online sales only; the 15.8% figure covers all US retail. These two percentages use different base calculations and should not be directly compared as equivalent ratios.
Free returns have become an expectation in fashion and electronics categories. DHL's 2026 research found that a clear, no-cost returns policy increases purchase confidence — particularly for higher-priced items — and that complexity in the return process (printing labels, finding a drop-off point) is the main barrier to satisfaction with returns.
Seasonal Ecommerce Statistics
US Holiday Season 2025 (Observed)
E-commerce Growth Forecasts (Not Actuals)
The figures below are published projections. As of October 25, 2026, the 2026 US holiday season has not yet occurred. Do not cite these as confirmed or actual spending totals.
This is a forecast published before the holiday period. It should be labeled as projected spending, not actual 2026 holiday sales. Check Adobe's post-season release for the observed figure once available.
Why Different Sources Report Different Ecommerce Market Sizes
Searching for "global ecommerce market size" returns figures ranging from roughly $6 trillion to over $28 trillion. These are not contradictory estimates of the same thing — they measure fundamentally different markets. Here is why they differ.
| Source type | What it typically measures | Why the number is large or small |
|---|---|---|
| Government statistical agencies (Census, Eurostat) | Retail ecommerce sales within their jurisdiction | Limited to retail; excludes most B2B; most accurate for their defined scope |
| UNCTAD | Total business ecommerce across 46 economies, including B2B | Very large because it includes all digitally ordered business-to-business sales |
| Market research firms | Varies — often B2C retail, sometimes including travel and services | Definitions differ by report; forecasts may use different growth assumptions |
| Marketplace GMV filings | Gross merchandise value transacted on a specific platform | Platform-specific; not directly comparable across platforms or with retail ecommerce |
| Platform revenue reports | Revenue recognized by the platform operator | Much smaller than GMV because it reflects only fees and services, not transaction value |
The principle that matters for any citation: identify the source, the market definition, the observation year, and the geography before drawing comparisons. Two figures that differ by a factor of four might both be accurate — they are simply measuring different things.
Ecommerce Metrics Definitions and Formulas
| Metric | Formula | Watch for |
|---|---|---|
| Purchase conversion rate | Purchase sessions ÷ Total sessions × 100 | Check whether denominator is sessions or users |
| Average order value (AOV) | Revenue ÷ Number of orders | Confirm whether discounts, tax, shipping included; whether returns excluded |
| Cart abandonment rate | Abandoned carts ÷ Initiated carts × 100 | Different from checkout abandonment rate; definition varies by platform |
| Ecommerce retail share | Online retail sales ÷ Total retail sales × 100 | Do not confuse with year-over-year growth rate |
| Year-over-year growth | (Current period − Prior period) ÷ Prior period × 100 | Use equivalent periods; note seasonal adjustment status |
| Return rate (by value) | Returned sales value ÷ Total sales value × 100 | Different from order-count-based return rate |
Nominal ecommerce growth reflects higher prices, more transactions, or both. A 10% nominal increase in sales does not mean 10% more units were sold — it could reflect the same volume at higher prices. When inflation is elevated, real (inflation-adjusted) growth is a more accurate indicator of volume change. Most ecommerce sales figures are nominal unless specified otherwise.
Frequently Asked Questions
What percentage of US retail sales are online?
The US Census Bureau reported ecommerce accounted for 17.1% of seasonally adjusted total US retail sales in Q2 2026. This figure is for retail ecommerce only and uses the Census Bureau's seasonally adjusted quarterly series. It is subject to revision — verify the current release at census.gov/retail/ecommerce.html.
What is the average ecommerce conversion rate?
Littledata reported a median conversion rate of 1.4% across 433 Shopify stores in October 2026. This is a median, not a mean, and it applies to a specific platform sample. Conversion rates vary widely by product category, traffic channel, audience, and price point — a single "average" figure should be used as a starting benchmark, not a target.
What is a good ecommerce conversion rate?
There is no single "good" conversion rate. A store in the top 20% of Littledata's Shopify sample converts at 2.7% or above. But a high-consideration category (luxury goods, custom furniture) may perform excellently at 0.5–1%, while an impulse-buy category should aim higher. Use percentile benchmarks within your category rather than cross-industry averages.
What is the average cart abandonment rate?
Baymard Institute reports 70.22%, compiled from 50 referenced studies with varying years and methodologies. This is best used as a rough industry reference, not a precise measurement. Many abandoning visitors were browsing without immediate purchase intent — the "recoverable" portion through checkout optimization is much smaller.
Does mobile or desktop convert better?
Littledata's October 2026 data shows the gap is narrow in their Shopify sample (mobile 1.6% vs desktop 1.5% median). Historically, desktop has outperformed mobile on conversion in many categories, but that gap has narrowed significantly as mobile checkout experiences improved. Mobile generates more visits and a growing majority of transactions; desktop often produces higher AOVs in categories like electronics.
What is the ecommerce return rate?
The NRF estimated 19.3% of online sales would be returned in 2025, compared to a 15.8% overall retail return rate. Online return rates run higher because customers cannot inspect products before purchase. Fashion and apparel category return rates are higher than these cross-category averages; digital goods have no returns.
Why do different sources report different global ecommerce market sizes?
Because they measure different things. UNCTAD's ~$28 trillion includes B2B business ecommerce across 46 economies. Market research firm estimates typically cover B2C retail only, often projected rather than measured. Government statistical agency figures are limited to their jurisdiction's retail. GMV figures from marketplaces reflect gross platform transaction value, not recognized revenue. Always check what a figure actually measures before comparing or citing it.
What percentage of ecommerce transactions happen on mobile?
Adobe Analytics reported 56.4% of US online transactions during the November–December 2025 holiday season occurred via smartphone. This is for the US holiday period only. Mobile transaction share varies by country, time of year, and product category. In many markets, mobile accounts for the majority of ecommerce orders, even when desktop produces a larger share of revenue.
What is GMV vs ecommerce revenue?
GMV (gross merchandise value) is the total value of products sold through a platform, before any deductions. Revenue is what the platform or retailer actually recognizes — after returns, discounts, and in a marketplace's case, only the fees it charges. A marketplace might process $100B in GMV but recognize $8B in revenue. These figures are not interchangeable.
How will ecommerce grow in the next few years?
Growth forecasts from market research firms vary widely depending on their methodology, assumed geography, and market definition. The direction — continued growth in ecommerce's share of retail — is broadly agreed upon; the precise figures are not. Treat any 5-year ecommerce projection as directional guidance, not a reliable measurement. Adobe's September 2026 forecast projects $275.1 billion in US holiday spending for November–December 2026, up from $257.8 billion in 2025.
Sources and Research Methodology
Every statistic on this page comes from a named original source. The methodology notes below describe what each source measures, how it collects data, and where its limitations lie.
-
US Census Bureau — Quarterly Retail E-Commerce Sales
Official US retail ecommerce sales, published quarterly. Provides seasonally adjusted and not seasonally adjusted series. Subject to revision. census.gov/retail/ecommerce.html -
UNCTAD — E-commerce and Digital Economy
Measures total business ecommerce across 46 economies, including B2B. October 2026 update. Scope is broader than B2C retail. unctadstat.unctad.org -
Adobe Analytics — Holiday Shopping Season Report
Tracks US consumer online spending through Adobe's analytics platform, covering billions of visits to retail websites. Published annually after the holiday season. 2025 results published January 2026. news.adobe.com -
Adobe Analytics — 2026 Holiday Season Forecast
Projection published September 2026, covering forecast US online spending for November–December 2026. This is a forecast, not an observed figure. news.adobe.com -
Littledata — Ecommerce Conversion Rate Benchmark
Monthly-updated benchmark drawing on Google Analytics 4 data from a sample of Shopify stores. Reports median, not mean. October 2026 sample: 433 stores. littledata.io -
Baymard Institute — Cart Abandonment Rate
Compilation of 50 published shopping cart abandonment studies. The 70.22% figure aggregates across studies with different years, methodologies, and market definitions. Baymard also conducts original large-scale checkout usability research. baymard.com -
National Retail Federation — 2025 Retail Returns Landscape
Annual research on US retail returns. Covers both online and overall retail return rates. The 19.3% online figure is an estimate for 2025, not an audited actual from completed financial reports. nrf.com -
DHL — Ecommerce Trends Report 2026
Survey of 29,000 online shoppers and 5,800 ecommerce businesses across 29 countries. Findings represent self-reported consumer preferences and expectations, not observed transaction data. dhl.com -
DHL — Ecommerce Trends Report 2025
Prior-year survey covering 24,000 shoppers across 24 markets. Used for trend comparison. The 2025 and 2026 waves use different sample sizes and country sets — treat as directional comparisons, not a controlled panel. dhl.com