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The clearest 2026 ecommerce picture comes from three different kinds of evidence: a preliminary U.S. government sales estimate, an industry forecast for all retail, and a global consumer survey. They measure different things, so the useful answer depends on keeping their definitions, dates, and limitations separate.
The latest official U.S. ecommerce sales figure
The U.S. Census Bureau’s preliminary estimate for the second quarter of 2026 is the most current official retail-ecommerce sales benchmark in the material available for this article. Census publishes both seasonally adjusted and unadjusted series; they should not be combined.
| Q2 2026 Census series | Sales | Year-over-year change | Share of total U.S. retail sales | How to read it |
|---|---|---|---|---|
| Seasonally adjusted | $340.2 billion | 12.2% (margin of error ±0.9 percentage points) | 17.1% | Best for comparing quarters after removing recurring seasonal patterns; preliminary and subject to revision. |
| Not seasonally adjusted | $329.5 billion | Not stated in the cited release summary | 16.4% | Reflects the actual calendar-quarter pattern, including normal seasonal swings. |
The adjusted estimate is the headline figure for a quarter-to-quarter discussion: $340.2 billion in retail ecommerce sales, up 12.2% from the same quarter a year earlier and equal to 17.1% of all U.S. retail sales. “Seasonally adjusted” means Census statistically removes predictable timing effects, such as holiday shopping patterns. It does not remove inflation or otherwise convert nominal dollars into constant-price dollars.
Census labels the latest-quarter estimate preliminary because it is calculated from a sample and can be revised as additional information arrives. The reported year-over-year change carries a stated margin of error of plus or minus 0.9 percentage points. A small movement inside that uncertainty range should not automatically be described as a definitive acceleration or slowdown.
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What the Census ecommerce measure includes
Census classifies a transaction according to how the order is placed or how price and terms are negotiated. An order can qualify when it is made through the internet, a mobile device, an extranet, electronic data interchange (EDI), email, or a comparable online system. The customer may pay online or offline; the payment channel is not the deciding test.
The quarterly estimate covers retail businesses with paid employees. It is therefore an employer-firm measure, not a census of every individual seller, informal marketplace participant, or consumer-to-consumer transaction. Census excludes several activities from its retail-ecommerce estimates, including online travel services, financial brokers and dealers, and ticket sales agencies.
Why the definition matters
- A phone order placed through a retailer’s online checkout can count even if the customer pays when the goods are delivered.
- An in-store purchase is not automatically ecommerce merely because the shopper used a retailer’s app while standing in the store; the order method and negotiated terms determine classification.
- Travel bookings, securities transactions, and ticket-agency sales should not be added to the Census retail-ecommerce total.
- Because the series is not inflation-adjusted, a rise in dollar sales can reflect a combination of more transactions, higher prices, or both.
How to interpret the 2026 growth rate
The 12.2% year-over-year change compares the adjusted second quarter of 2026 with the corresponding adjusted quarter one year earlier. It is not an annual forecast and does not mean every retailer, category, or month grew at that rate.
Three qualifications belong with any use of the number:
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- Sampling uncertainty: Census reports a margin of error of ±0.9 percentage points for the headline change. Avoid claiming that a very small difference between periods is statistically meaningful without consulting the report’s confidence-interval notes.
- Revision risk: The Q2 estimate is preliminary. Later releases can revise both dollar totals and growth rates.
- Nominal dollars: The series is seasonally adjusted but not price adjusted. It measures sales value, not inflation-free volume.
For a presentation or business plan, label the figure as “preliminary, seasonally adjusted U.S. retail ecommerce sales, Q2 2026.” That wording identifies the geography, period, adjustment, and status in one line.
NRF’s $5.6 trillion number is total retail, not ecommerce
The National Retail Federation forecasts that total U.S. retail sales will grow 4.4% to $5.6 trillion in 2026. This is an annual industry forecast for retail as a whole, not a projection of online sales alone. It includes online and store purchases within NRF’s core retail scope while excluding auto dealers, gasoline stations, and restaurants.
| Measure | Figure | Period and status | Scope |
|---|---|---|---|
| Census ecommerce estimate | $340.2 billion; 12.2% year-over-year growth; 17.1% share | Q2 2026, preliminary, seasonally adjusted | U.S. retail ecommerce as defined by the ordering method |
| NRF retail forecast | $5.6 trillion; 4.4% growth | Full-year 2026 forecast, nominal dollars | Total U.S. retail in NRF’s core categories, online and stores combined |
These figures answer different questions. Census reports what a defined group of retail businesses sold during one quarter. NRF estimates what the entire core retail sector may sell over a year. Dividing the NRF forecast by the Census quarterly figure, or treating the forecast’s 4.4% as an ecommerce growth rate, would produce a misleading comparison.
NRF says its forecast assumes tariffs remain close to levels in place when the forecast was prepared. The organization warns that substantially higher tariffs or greater trade-policy uncertainty could weaken hiring, equity markets, and consumer spending. It also says geopolitical uncertainty was too high to incorporate into the forecast at that time. Those are stated assumptions and risks, not guarantees about the outcome.
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What consumers reported in the NRF–IBM 2026 survey
A separate NRF and IBM study, published January 7, 2026, surveyed 18,000 consumers globally. Its percentages are self-reported behaviors or attitudes among respondents; they are not transaction totals and should not be presented as the share of all purchases.
| Survey finding | Reported result | What it indicates |
|---|---|---|
| Use AI assistants to research products | 41% | AI tools are part of product-discovery journeys for a substantial respondent group. |
| Use AI assistants to look for reviews | 33% | Some shoppers use conversational tools to gather evaluation information. |
| Use AI assistants to search for deals | 31% | Price discovery is one of the reported AI use cases. |
| Still shop in physical stores | 72% | Store shopping remains common among surveyed global consumers. |
| Comfortable sharing data | 52% | A slim majority of respondents expressed comfort in the study’s context. |
| Share concerns about privacy, misuse, and unwanted marketing | 83% | Overlapping concerns were reported; the categories are not mutually exclusive. |
| Trading down to budget alternatives | About one-third | The study reports price sensitivity alongside selective indulgence and willingness to pay more for trusted brands. |
The survey’s percentages do not add to 100% because respondents can use AI for several purposes, shop both online and in stores, and hold more than one privacy concern. “Comfortable sharing data” also does not cancel out concern about misuse or unwanted marketing; people may accept some data sharing while objecting to particular uses.
What the AI findings do—and do not—say
The AI results describe research behavior, not completed purchases. A respondent who asks an assistant for reviews may still buy in a store, visit a brand website, or abandon the purchase. The study therefore supports the statement that AI is entering discovery, comparison, and deal-seeking workflows; it does not establish that AI generated a particular share of retail revenue.
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The same study describes consumers trading down to budget alternatives while also reporting selective indulgence and a willingness to pay more for trusted brands. That combination is more informative than a blanket claim that shoppers either always choose the cheapest option or have stopped spending. Treat “about one-third” as a survey pattern among the respondents, not a universal percentage for every market.
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Four axes to check before comparing ecommerce statistics
Statistics that appear side by side can represent incompatible units. Check these axes before drawing a trend line or calculating a share.
- Geography: Census figures describe U.S. retail. The NRF–IBM findings come from a global consumer survey.
- Measure: Census reports dollar sales and a share of retail sales. NRF reports forecast growth and a total-retail value. The survey reports self-described behavior and attitudes.
- Period: The Census result is a quarterly estimate; NRF’s number is a full-year 2026 forecast; the survey findings were published January 7, 2026.
- Adjustment: Census offers a seasonally adjusted series and an unadjusted series, but neither is adjusted for inflation. NRF’s forecast is nominal.
- Scope: Census uses an employer-firm retail series with explicit exclusions. NRF uses its own core-retail categories. The survey describes respondents, not a sales universe.
Practical implications for ecommerce teams
Make product information usable by both people and assistants
Because respondents report using AI for research, reviews, and deals, retailers should keep product facts clear and machine-readable: consistent specifications, current availability, transparent pricing, shipping terms, and easily verifiable review information. This is an operational implication of the survey, not evidence that any particular optimization will increase sales.
Design for online and store journeys
The survey’s store-shopping result argues against treating ecommerce as a replacement for physical retail. Inventory visibility, pickup and returns options, and consistent product information can reduce friction when a shopper moves between channels. The Census definition also reminds analysts that the order method, rather than the payment location, determines whether a sale enters the ecommerce series.
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Explain data practices at the moment of choice
With privacy, misuse, and unwanted-marketing concerns reported by a large majority of respondents, consent notices should identify what data is collected, why it is needed, how long it is retained, and which communications a customer can decline. Clear controls address the gap between being willing to share data in some circumstances and objecting to specific uses.
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Offer value without assuming every shopper trades down
A budget tier, durable alternatives, and clear total-cost information can serve price-sensitive customers. At the same time, the survey’s finding about trusted brands and selective indulgence suggests that reliability, safety, service, or provenance may justify a higher price for some purchases. Segmenting these needs is more defensible than applying a single “lowest price wins” strategy.
What these figures cannot establish
The available material does not provide a comparable official global retail-ecommerce sales total or global online share for 2026. The global survey supplies consumer behavior findings, not a worldwide dollar market size. Do not combine it with the U.S. Census estimate to create a global total.
The next U.S. Census quarterly release after Q2 2026 was scheduled for November 19, 2026. Until that release is available, Q2 remains the latest quarter covered here, and its preliminary status should remain attached to any citation.
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- State “U.S.” and “Q2 2026” when citing the Census estimate.
- Specify “seasonally adjusted” or “not seasonally adjusted”; never switch between the two in one trend.
- Say that the Census estimate is preliminary and not adjusted for inflation.
- Keep NRF’s $5.6 trillion forecast labeled as total retail, not ecommerce.
- Identify the NRF–IBM figures as survey responses from 18,000 global consumers published January 7, 2026.
- Describe survey percentages as reported behaviors or attitudes, not purchase shares.
Bottom line
Q2 2026 Census data show strong U.S. retail-ecommerce sales growth, but the number is a preliminary, seasonally adjusted nominal estimate with a defined retail scope. NRF’s larger $5.6 trillion figure is a forecast for all core U.S. retail, while the NRF–IBM study shows how surveyed consumers are using AI, balancing store and online shopping, weighing privacy, and responding selectively to prices. Keeping those evidence types separate produces a clearer and more honest view of ecommerce in 2026.
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