AI-referred visits to US retail sites converted 90% better than non-AI traffic in September 2026 in Adobe Analytics' panel, up from 49% worse in January 2025. Year-over-year traffic growth has fallen as the base has grown, to +71% in September 2026. AI referrals remain a small share of visits: 0.2% of Q4 2025 sessions in Contentsquare's global benchmark. Every figure below carries its source, sample and period.
- Measures
- AI-referred
- Geography
- US
- Period
- September 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US
- Period
- September 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-influenced
- Geography
- Global
- Period
- 1 Nov to 31 Dec 2025
- Sample
- 1.5 billion+ shoppers
- Method
- Shopping Index, retailer-side AI
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Survey, July 2026
- Sample
- n = 5,000+
- Method
- Consumer survey
What each statistic measures
The figures on this page come from different measurement systems that are often quoted as if they were one. Every card, chart and caption below uses these terms, and no two of them are added together.
| Term | Means | On this page |
|---|---|---|
| AI-referred | A human clicked a link from an AI surface to a retail site. | Adobe's traffic and conversion figures. Shopify's AI-referred sessions. The Kaiser and Schulze organic ChatGPT channel. |
| AI-influenced | AI touched the purchase journey at some point, as measured by the vendor's own model. | Salesforce's $262 billion and 20% of 2025 holiday sales. |
| AI-attributed | Revenue assigned to AI by a last-touch or modeled attribution rule. | Used on this page only where the source uses it. Amazon's "incremental annualized sales" from Rufus is a company-modeled figure of this kind. |
| Agent-executed | An agent completed the action or the transaction itself. | Salesforce's agent-driven address updates and returns. Quantum Metric's agent cart and purchase counts. |
| Agent benchmark | AI models tested on simulated shopping tasks, not live traffic. | Visa's benchmark of 22 models across 15 scenarios. |
| AI crawler activity | Automated requests from bots, not human sessions. | Never mixed with referral traffic on this page. |
| Retailer-owned assistant usage | Use of a retailer's own assistant, such as Amazon Rufus and Alexa for Shopping or Walmart Sparky. A separate channel. | Amazon: 400 million+ customers used Alexa for Shopping in the 12 months to Q3 2026. |
Consumer survey terms
| Term | Means | On this page |
|---|---|---|
| Stated preference | Wants, trusts or would allow something. | Deloitte: 16% would let generative AI complete a purchase with permission. |
| Intention | Plans to use AI for shopping. | Capgemini: a further 31% plan to use generative AI shopping tools. |
| Self-reported behavior | Says they have used AI for shopping. | Adobe, July 2026: 42% have used AI assistants for online shopping. |
| Agentic behavior | Says they let an agent complete a purchase. | Menlo Ventures and Morning Consult: 26% of US shoppers who use AI let it complete a purchase. |
AI-referred traffic: growth and share
AI-referred traffic to US retail sites grew 71% year over year in September 2026, according to Adobe Analytics, against 693.4% across the 2025 holiday season and 4,700% in July 2025. Adobe measures this as shoppers clicking a link from a generative AI chat service or browser, so it is human referral traffic, not crawler activity.
- Measures
- AI-referred
- Geography
- US
- Period
- September 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- August 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- July 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- May 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- Q1 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- 1 Nov to 31 Dec 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- October 2025 vs October 2024
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- July 2025 vs July 2024
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US
- Period
- July 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
Adobe's year-over-year growth rate fell from +4,700% in July 2025 to +1,200% in October 2025, +269% in March 2026 and +71% in September 2026, as the prior-year base grew. Adobe does not publish AI-referred traffic as a share of total retail visits. The figures below come from other datasets and are not combined with Adobe's.
Share of traffic and click-through, other datasets
- Measures
- AI-referred
- Geography
- Global, cross-industry
- Period
- Q4 2025 vs Q4 2024
- Sample
- 99 billion sessions; 6,500 sites
- Method
- Analytics benchmark
- Measures
- AI-referred
- Geography
- 9 countries plus EU-27
- Period
- 27 Jul to 17 Aug 2026
- Sample
- 1,898 sites
- Method
- First-party analytics
- Measures
- AI-referred
- Geography
- Not stated
- Period
- Not stated; published Sep 2026
- Sample
- Not stated
- Method
- Modeled traffic estimates
- Measures
- AI-referred
- Geography
- Not stated
- Period
- Q2 2026, year over year
- Sample
- Shopify storefronts
- Method
- Company disclosure
- Measures
- AI-referred
- Geography
- US, desktop
- Period
- Oct 2024 to Jul 2025
- Sample
- 45,386 households
- Method
- Comscore browsing panel
Each share has a different denominator: all web traffic across industries (Contentsquare), all sessions on a 1,898-site panel with organic ChatGPT only (Kaiser and Schulze), and retail ecommerce visits with no stated period (Similarweb). They are shown side by side, not as a trend.
Does AI-referred traffic convert?
In Adobe's US retail panel, AI referrals have converted better than non-AI traffic every month since September 2025, reaching +90% in September 2026. In Kaiser and Schulze's peer-reviewed study of 973 sites, February to August 2025, ChatGPT referrals converted below every traditional channel except paid social. Their follow-up on 1,898 sites finds ChatGPT conversion approximately matched organic search before February 2026. Shopify reports AI-referred sessions converting 64% better than organic search in Q3 2026.
Dataset A · Adobe Analytics, US retail
- Measures
- AI-referred
- Geography
- US retail
- Period
- September 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- September 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- July 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- March 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- 1 Nov to 31 Dec 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- Holiday 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
Comparator: a blended non-AI baseline that Adobe defines as paid search, affiliates and partners, email, organic search, and social media. Panel: 1 trillion+ visits to US retail sites.
Dataset B · Kaiser and Schulze, 973 sites, Marketing Science
- Measures
- AI-referred
- Geography
- Global
- Period
- 2 Feb to 2 Aug 2025
- Sample
- 973 sites
- Method
- First-party analytics, regression
- Measures
- AI-referred
- Geography
- Global
- Period
- 2 Feb to 2 Aug 2025
- Sample
- 973 sites
- Method
- First-party analytics, regression
- Measures
- AI-referred
- Geography
- Global
- Period
- 2 Feb to 2 Aug 2025
- Sample
- 973 sites
- Method
- First-party analytics, regression
- Measures
- AI-referred
- Geography
- Global
- Period
- 12 months to Aug 2025
- Sample
- 973 sites; 10.5 billion sessions
- Method
- First-party analytics
Comparator: each traditional channel individually, by regression with website, device and month fixed effects. Period: 2 February to 2 August 2025. Dataset: 973 websites in 24 categories, not retail only, 10.5 billion sessions, global with the Americas and Europe holding most sessions. Published in Marketing Science 45(4), online 21 April 2026.
Conversion by channel relative to organic ChatGPT referrals, Kaiser and Schulze
- 01AffiliateConversion coefficient 0.621 relative to organic ChatGPT, which the paper reports as an 86% higher likelihood of conversion. Revenue per session $3.57 higher.
- 02Paid searchConversion coefficient 0.370. Revenue per session $1.95 higher.
- 03OtherConversion coefficient 0.366. Revenue per session $2.19 higher.
- 04DirectConversion coefficient 0.282. Revenue per session $3.07 higher.
- 05EmailConversion coefficient 0.276. Revenue per session $2.69 higher.
- 06ReferralConversion coefficient 0.218. Revenue per session $1.61 higher.
- 07Organic searchConversion coefficient 0.121, a 13% higher likelihood of conversion. Revenue per session $1.01 higher.
- 08Organic ChatGPT referral (baseline)The reference channel. Over the first twelve months its conversion rate and revenue per session rose while average order value fell.
- 09Paid socialConversion coefficient −0.760, a 53% lower likelihood of conversion. Revenue per session $0.718 lower.
Ordered by the conversion coefficient in Table 3 of the Marketing Science paper (log-odds relative to organic ChatGPT referrals). The paper converts three coefficients into likelihoods: affiliate +86%, organic search +13% and paid social −53%. Other likelihoods are not stated in the paper and are not calculated here. Revenue per session is the regression difference in US dollars. The paper reports no absolute conversion rate by channel; the all-channel mean is 3.30% per website per week. 2 February to 2 August 2025, 973 websites. Kaiser and Schulze, Marketing Science 45(4):699-715, Published online 21 April 2026 (SSRN 5585812, last revised 27 July 2026)
Dataset C · Later readings, June 2025 to Q3 2026
- Measures
- AI-referred
- Geography
- 9 countries plus EU-27
- Period
- 30 Jun 2025 to 22 Aug 2026
- Sample
- 1,898 sites; 446,090 ChatGPT transactions
- Method
- First-party analytics
- Measures
- AI-referred
- Geography
- US
- Period
- After Feb 2026 ad rollout
- Sample
- 102 advertiser sites with full revenue tracking
- Method
- First-party analytics
- Measures
- AI-referred
- Geography
- Not stated
- Period
- Q3 2026
- Sample
- Shopify storefronts
- Method
- Company disclosure
The 1,898-site panel includes only sites with more than 10 ChatGPT transactions, so it is not a continuation of the 973-site study and the two are not a time series. It is a working paper, version 1, October 2026. Shopify's figure is a company disclosure with no published method.
Engagement of AI-referred visitors, both datasets
| Metric | Adobe, July 2025 | Adobe, holiday 2025 | Adobe, July 2026 | Kaiser and Schulze, Feb to Aug 2025 |
|---|---|---|---|---|
| Time on site | +32% longer | +45% longer | +59% longer | Intermediate; above paid social and affiliate |
| Pages per visit | +10% more | +13% more | +22% more | Fewer page views |
| Bounce rate | −27% lower | −33% less likely to bounce | −34% less likely to bounce | More favorable (abstract); organic search 13% lower |
Adobe columns: AI-referred visits against Adobe's blended non-AI baseline, US retail, 1 trillion+ visits; July 2025 from the August 2025 release, holiday 2025 from the January 2026 release, July 2026 from the August 2026 report. Kaiser and Schulze column: organic ChatGPT referrals against traditional channels across 973 sites. Adobe Analytics, 21 August 2025 · Adobe Analytics, 12 January 2026 · Adobe Digital Insights, 19 August 2026 · Kaiser and Schulze, Marketing Science 45(4):699-715, Published online 21 April 2026 (SSRN 5585812, last revised 27 July 2026)
Why the datasets differ
- 01 · Different comparators
Adobe measures AI referrals against a blended baseline that contains paid social. Kaiser and Schulze compare ChatGPT referrals with each channel individually. Shopify compares with organic search only. Beating a blend that includes paid social is not the same test as beating organic search.
- 02 · Different periods
The 973-site study covers February to August 2025. Adobe's own series was negative over the same months: 38% worse in April and 23% worse in July 2025. Adobe's readings turned positive from September 2025, and the 1,898-site follow-up finds ChatGPT conversion approximately matched organic search before February 2026.
- 03 · Different populations
Adobe is US retail only, weighted toward large enterprise retailers. The 973 sites are global and span 24 categories including finance, travel and jobs. Shopify covers its own merchants with no stated geography.
- 04 · Different definitions of AI traffic
Adobe counts referrals from chat services and AI browsers. Kaiser and Schulze isolate organic ChatGPT referrals. Shopify's metric wording changes each quarter.
- 05 · Selection effects
Peak-season AI referrals arrive with gift intent and a deadline. The 973-site study finds ChatGPT outcomes strongest in complex product categories. Each dataset may be sampling a different stage of the purchase journey.
No source has measured both populations on the same definition over the same window. Every 2026 reading of unpaid AI referrals on this page, from Adobe, Shopify and the 1,898-site panel, puts conversion at or above organic search or the blended baseline. Paid ChatGPT ad visits converted at 0.37% against 1.17% for paid Google Search. This page does not average the datasets.
Consumer AI shopping: behavior and intention
42% of US consumers report having used AI assistants for online shopping in Adobe's July 2026 survey of 5,000+, up from 38% in its 2025 survey. Across 12 countries, Capgemini's October 2025 wave puts use at 25% with a further 31% planning to. Surveys that ask about letting AI complete a purchase range from 16% who would allow it (Deloitte) to 26% of AI shoppers who say they have (Menlo Ventures).
Adobe Consumer Survey, n = 5,000+ US respondents, fielded July 2026
- Measures
- Self-reported behavior
- Geography
- US
- Period
- July 2026
- Sample
- n = 5,000+
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- July 2026
- Sample
- n = 5,000+
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- July 2026
- Sample
- n = 5,000+
- Method
- Consumer survey
- Measures
- Stated preference
- Geography
- US
- Period
- July 2026
- Sample
- n = 5,000+
- Method
- Consumer survey
Other surveys, late 2025 to September 2026
| Finding | Measure | Geography | Sample | Fielded | Source |
|---|---|---|---|---|---|
| 26% of shoppers who use AI let it complete a purchase; 37% made a final purchase decision on its recommendation | Agentic behavior | US | n = 5,067 adults | July 2026 | Menlo Ventures, survey by Morning Consult, 16 September 2026 |
| 38% say they have completed a purchase directly inside ChatGPT | Agentic behavior | US | n = 1,072 | January 2026 | Omnisend, survey by Cint, 18 March 2026 |
| 16% would let generative AI complete a holiday purchase with their permission | Stated preference | US | n = 3,700 | 26 Aug to 10 Sep 2026 | Deloitte, 15 October 2026 |
| 39% say generative AI is their primary tool for at least one holiday shopping task | Intention | US | n = 3,700 | 26 Aug to 10 Sep 2026 | Deloitte, 15 October 2026 |
| 23% trust generative AI to handle payment transactions on their behalf | Stated preference | US | n = 2,065 | 26 to 28 May 2026 | Visa, survey by The Harris Poll, 9 September 2026 |
| 54% have used AI for at least one shopping task, up from 47% a year earlier | Self-reported behavior | US | n = 1,000+ | Late September 2026 | Visa, survey by Morning Consult, 30 October 2026 |
| 29% plan to use AI in their holiday shopping, up from 22% a year earlier | Intention | US | n = 4,093 | 15 to 26 Jun 2026 | PwC, 8 September 2026 |
| 25% have used Gen AI shopping tools; a further 31% plan to | Self-reported behavior | 12 countries | n = 12,000 | October 2025 | Capgemini Research Institute, 6 January 2026 |
Question wording, base and recall window differ between surveys, so the rows are not a ranking or a trend. The Omnisend figure is a vendor survey with unpublished question wording. OpenAI never published how many merchants offered Instant Checkout before dropping it in March 2026, and no other survey here reports a comparable share. The Menlo Ventures base is US shoppers who use AI, a subgroup whose size is not published.
Earlier Adobe surveys: n = 5,000 (published August 2025) and n = 1,000+ (Holiday 2025, published January 2026)
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Survey, 2025
- Sample
- n = 5,000
- Method
- Consumer survey
- Measures
- Intention
- Geography
- US
- Period
- Survey, 2025
- Sample
- n = 5,000
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Survey, 2025
- Sample
- n = 5,000
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Survey, 2025
- Sample
- n = 5,000
- Method
- Consumer survey
- Measures
- Stated preference
- Geography
- US
- Period
- Survey, 2025
- Sample
- n = 5,000
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Holiday 2025 survey
- Sample
- n = 1,000+
- Method
- Consumer survey
- Measures
- Stated preference
- Geography
- US
- Period
- Holiday 2025 survey
- Sample
- n = 1,000+
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Holiday 2025 survey
- Sample
- n = 1,000+
- Method
- Consumer survey
- Measures
- Self-reported behavior
- Geography
- US
- Period
- Holiday 2025 survey
- Sample
- n = 1,000+
- Method
- Consumer survey
Adobe's three surveys have different sample sizes, fielding dates and question wording. The 85% (2025, n = 5,000), 81% (Holiday 2025, n = 1,000+) and 83% (July 2026, n = 5,000+) improved-experience figures are not a trend line.
AI-influenced sales: Salesforce Shopping Index
Salesforce reports that AI and agents drove 20% of global 2025 holiday retail sales, $262 billion, and $67 billion of Cyber Week sales. This is retailer-owned AI measured on Salesforce-powered storefronts and extrapolated to the industry. It is not LLM referral traffic and it is kept apart from the Adobe figures above for that reason.
- Measures
- AI-influenced
- Geography
- Global
- Period
- 1 Nov to 31 Dec 2025
- Sample
- 1.5 billion+ shoppers
- Method
- Shopping Index, retailer-side AI
- Measures
- AI-referred
- Geography
- Global
- Period
- 1 Nov to 31 Dec 2025
- Sample
- 1.5 billion+ shoppers
- Method
- Shopping Index
- Measures
- AI-influenced
- Geography
- Global
- Period
- 25 Nov to 1 Dec 2025
- Sample
- 1.5 billion+ shoppers
- Method
- Shopping Index, retailer-side AI
- Measures
- Company disclosure
- Geography
- Global and US
- Period
- 25 Nov to 1 Dec 2025
- Sample
- 1.5 billion+ shoppers
- Method
- Shopping Index
- Measures
- AI-influenced
- Geography
- Global
- Period
- 25 Nov to 1 Dec 2025
- Sample
- Salesforce customers vs non-users
- Method
- Vendor customer comparison
- Measures
- Agent-executed
- Geography
- Global
- Period
- 25 Nov to 1 Dec 2025
- Sample
- Agentforce customers
- Method
- Shopping Index
- Measures
- Agent-executed
- Geography
- Global
- Period
- 25 Nov to 1 Dec 2025
- Sample
- Agentforce customers
- Method
- Shopping Index
- Measures
- Company disclosure
- Geography
- Global
- Period
- 25 Nov to 1 Dec 2025
- Sample
- Agentforce Commerce customers
- Method
- Shopping Index
Series sources: Salesforce, via Business Wire, 28 November 2023 · Salesforce, 4 December 2024 · Salesforce, 5 December 2025
Salesforce forecast $73 billion and 22% for Cyber Week 2025 on 20 November 2025 and reported $67 billion and 20% after it. The forecast window was 27 November to 1 December; the result window was 25 November to 1 December. The forecast is cited here only so the two are not confused. Salesforce, 20 November 2025
Retailer assistants and Shopify AI orders
Amazon reports 400 million+ customers used Alexa for Shopping in the 12 months to Q3 2026. Walmart reports that roughly half of its app users have used Sparky. Shopify reports orders from AI searches up 3.3 times year over year in Q3 2026. All three are company disclosures with no published method.
- Measures
- Company disclosure
- Geography
- Not stated
- Period
- 12 months to Q3 2026
- Sample
- Amazon customers
- Method
- Earnings release
- Measures
- Company disclosure
- Geography
- Not stated
- Period
- 2025
- Sample
- Amazon customers
- Method
- Earnings release, company model
- Measures
- Company disclosure
- Geography
- US
- Period
- Q4 FY26 (to Jan 2026)
- Sample
- Walmart app users
- Method
- Earnings call remarks
- Measures
- Company disclosure
- Geography
- Not stated
- Period
- Q2 FY27 (to Jul 2026)
- Sample
- Walmart customers and members
- Method
- Earnings call remarks
- Measures
- AI-referred
- Geography
- Not stated
- Period
- Q3 2026
- Sample
- Shopify storefronts
- Method
- Investor deck
- Measures
- AI-referred
- Geography
- Not stated
- Period
- Q3 2026
- Sample
- Shopify storefronts
- Method
- Investor deck
Retailer-owned assistants are a separate channel from third-party AI referrals: a shopper using Rufus or Sparky is already on the retailer's own site or app, so this usage is not an AI referral as Adobe and Shopify define one. Walmart's order value comparisons set Sparky users against non-users, who self-select, so they do not measure an effect of the assistant. Amazon's Alexa for Shopping combines Rufus and Alexa+, so its customer count does not continue the 2025 Rufus series. Amazon Investor Relations, 29 October 2026 · Amazon, 5 February 2026 · Walmart, 19 February 2026 · Walmart, 20 August 2026
Shopify describes its AI metric differently in each quarter's materials and does not say whether the definition changed, so the quarterly multiples are shown one quarter at a time. Shopify is one of the platforms in the ecommerce platform comparison. Shopify Investor Relations, 3 November 2026
Peak events: holiday 2025 and Prime Day 2026
AI referrals converted 38% better than non-AI traffic sources on Black Friday 2025 and 54% better on Thanksgiving, in Adobe's US retail panel. During Prime Day 2026 they converted 40% better, against 23% worse during Prime Day 2025. These are AI-referred figures from Adobe. Salesforce's AI-influenced totals measure something different.
Thanksgiving to Cyber Monday 2025
- Measures
- AI-referred
- Geography
- US retail
- Period
- Black Friday, 28 Nov 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- Thanksgiving, 27 Nov 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- Cyber Monday, 1 Dec 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US retail
- Period
- 1 Nov to 1 Dec 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- Company disclosure
- Geography
- US
- Period
- 1 Nov to 31 Dec 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US retail
- Period
- Cyber Monday, 1 Dec 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
Prime Day 2025 and 2026
- Measures
- AI-referred
- Geography
- US retail
- Period
- Prime Day, 23 to 26 Jun 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
- Measures
- AI-referred
- Geography
- US retail
- Period
- Prime Day, 23 to 26 Jun 2026
- Sample
- 1 trillion+ visits
- Method
- Analytics panel, blended non-AI comparator
- Measures
- AI-referred
- Geography
- US retail
- Period
- Prime Day, 8 to 11 Jul 2025
- Sample
- 1 trillion+ visits
- Method
- Analytics panel
The peak-day conversion gaps for Thanksgiving and Black Friday 2025 are wider than the season average of +31%, which is consistent with the selection effect described in the conversion section: shoppers arriving from an AI service on those days carry gift intent and a deadline. Prime Day 2026 ran from 23 to 26 June and Prime Day 2025 from 8 to 11 July, so the year-over-year comparison spans different weeks. Adobe reports the 2025 season's total US online spend at $257.8 billion but does not publish AI-referred traffic as a share of it, and no share figure is estimated here. Adobe had not published measured figures for the 2026 holiday season at 9 November 2026; its forecast is in the forecasts table.
Agentic commerce protocols and agent checkout
OpenAI moved ChatGPT away from in-chat Instant Checkout on 24 March 2026; purchases from ChatGPT now complete on merchant-owned sites and apps. Google launched Universal Cart with checkout powered by its Universal Commerce Protocol in the US on 15 October 2026 and began rolling out direct checkout in Canada on 4 November 2026. MCP is a model-to-tool integration standard and defines no cart, checkout or payment primitives.
| Standard and layer | Sponsor or governance | Discovery and catalog | Cart | Checkout | Payment credentials | Post-purchase | Status, November 2026 |
|---|---|---|---|---|---|---|---|
ACP Commerce | OpenAI and Stripe. Specification in beta | Yes. Product feeds and promotions | Yes, in the 2026-04-17 specification | In the specification; not used in ChatGPT since March 2026 | Delegated payment specification | Orders capability in the specification | ChatGPT uses ACP for discovery only. OpenAI: "purchases are completed on merchant-owned websites or apps" and "There are no fees on purchases that start in ChatGPT" |
UCP Commerce | Google-led. Tech Council of 16 seats, including Google, Shopify, Etsy, Target, Wayfair, Amazon, Meta, Microsoft, Salesforce and Stripe | Yes | Yes, optional capability | Yes | Via AP2 and regulated payment providers | Yes | Universal Cart with UCP checkout live in the US since 15 October 2026. Direct checkout rolling out in Canada from 4 November 2026. Merchant Center Help still describes checkout as available to select merchants |
AP2 Payments | FIDO Alliance, donated by Google in April 2026 | No | No | No | Yes. Signed Checkout Mandate and Payment Mandate (version 0.2) | No | Specification open. Version 0.2 released 28 April 2026, adding human-not-present flows. No transaction volume disclosed |
A2A Agent-to-agent | Agentic AI Foundation since 17 August 2026 | n/a | n/a | n/a | n/a | n/a | Version 1.0 stable since March 2026; latest release 1.0.1. 150+ supporting organizations. Not a commerce protocol |
MCP Integration | Agentic AI Foundation, under the Linux Foundation | Tool and data access only | Not in scope | Not in scope | Not in scope | Tool access only | Specification version 2026-07-28. Close to half a billion monthly downloads across Tier 1 SDKs, July 2026 |
Sources: ACP from the ACP specification and OpenAI's merchant page (both retrieved 9 November 2026), OpenAI (24 March 2026) and Stripe (29 September 2025). UCP from Google (11 January, 19 March, 15 October and 4 November 2026), the UCP project (24 April 2026) and Merchant Center Help (retrieved 9 November 2026). AP2 from the AP2 specification (version 0.2) and Google (28 April 2026). A2A from the Agentic AI Foundation (17 August 2026). MCP from the MCP project (28 July 2026). MCP is included to show what it does not cover. OpenAI and Stripe, ACP repository, Retrieved 9 November 2026 (latest stable version 2026-04-17) · OpenAI, Retrieved 9 November 2026 · Universal Commerce Protocol project, 24 April 2026 · AP2 project, Retrieved 9 November 2026 (version 0.2, 28 April 2026) · Google Cloud, 16 September 2025 · Google, 28 April 2026 · Agentic AI Foundation, 17 August 2026 · Linux Foundation, 9 April 2026 · Model Context Protocol project, 28 July 2026 · Linux Foundation, 9 December 2025
- Measures
- Protocol status
- Geography
- US
- Period
- 15 October 2026
- Sample
- Not applicable
- Method
- Company announcement
- Measures
- Protocol status
- Geography
- Canada
- Period
- 4 November 2026
- Sample
- Not applicable
- Method
- Company announcement
- Measures
- Protocol status
- Geography
- US, Canada, Australia
- Period
- Retrieved 9 November 2026
- Sample
- Not applicable
- Method
- Product documentation
- Measures
- Company disclosure
- Geography
- US
- Period
- Reported March 2026
- Sample
- Walmart, one retailer
- Method
- Executive disclosure via trade press
- Measures
- Protocol status
- Geography
- US
- Period
- 24 March 2026
- Sample
- Named by OpenAI
- Method
- Company announcement
- Measures
- Protocol status
- Geography
- Global
- Period
- 24 April 2026
- Sample
- Not applicable
- Method
- Project announcement
- Measures
- Protocol status
- Geography
- Global
- Period
- 28 July 2026
- Sample
- Self-reported
- Method
- Project announcement
What happened to in-chat checkout
Stripe and OpenAI launched Instant Checkout in ChatGPT on 29 September 2025, US only, with US-based Etsy businesses at launch and Shopify merchants described as coming soon. The launch introduced the Shared Payment Token, scoped to a specific merchant and cart total. Stripe, 29 September 2025 On 24 March 2026 OpenAI wrote: "We've found that the initial version of Instant Checkout did not offer the level of flexibility that we aspire to provide, so we're allowing merchants to use their own checkout experiences while we focus our efforts on product discovery." OpenAI, 24 March 2026
The best available evidence on why comes from Walmart. Its EVP Daniel Danker told Wired, as reported by Modern Retail, that conversion rates were three times lower for selection sold directly inside the chatbot than for products requiring a click out to the merchant. Etsy told the same outlet it did not see large volume from Instant Checkout but does see valuable referral traffic. This is a named-executive disclosure from one retailer, graded C, and it is the only conversion comparison of in-chat checkout against redirect that has been made public. Modern Retail, 27 March 2026
OpenAI has not published how many merchants went live on Instant Checkout, and counts reported by other outlets could not be traced to a primary source. OpenAI's merchant page now says: "We're moving away from a standalone Instant Checkout experience in ChatGPT and prioritizing better shopping discovery and merchant-owned checkout experiences." It also says "There are no fees on purchases that start in ChatGPT." OpenAI's developer documentation still describes Instant Checkout as available to approved partners, which conflicts with the merchant page. OpenAI, Retrieved 9 November 2026
What ACP is now
OpenAI describes ACP as "the connective layer between merchants and users throughout discovery," through which merchants share product feeds and promotions so their catalogs are represented in ChatGPT, with delivery paths that include third-party providers such as Salesforce and Stripe. OpenAI names Target, Sephora, Nordstrom, Lowe's, Best Buy, The Home Depot and Wayfair as integrated for discovery. Shopify merchants' product data is integrated through Shopify Catalog with no additional merchant work, and Shopify's Mani Fazeli is quoted saying buyers "can complete purchases on the merchant's online store through an in-app browser." Walmart has an in-ChatGPT app with account linking, loyalty and Walmart payments. The rollout covers free, Go, Plus and Pro users. OpenAI, 24 March 2026 The protocol itself still specifies checkout and delegated payment. Its latest stable version, 2026-04-17, covers cart, feed, orders, authentication and MCP, and the specification remains in beta, maintained by OpenAI and Stripe. OpenAI and Stripe, ACP repository, Retrieved 9 November 2026 (latest stable version 2026-04-17) The agentic commerce explainer covers the model in more depth.
What UCP is, and what is actually available
Google announced UCP at NRF on 11 January 2026 as an open-source standard co-developed with Shopify, Etsy, Wayfair, Target and Walmart, endorsed by more than 20 partners including Adyen, American Express, Best Buy, Flipkart, Macy's Inc, Mastercard, Stripe, The Home Depot, Visa and Zalando, and compatible with the Agent Payments Protocol, Agent2Agent and the Model Context Protocol as transports. Google Developers Blog, 11 January 2026 On 19 March 2026 Google added optional Cart and Catalog capabilities, the latter giving agents real-time pricing and inventory from retailer catalogs, and highlighted Identity Linking for loyalty benefits. Google, 19 March 2026 On 24 April 2026 the UCP Tech Council grew to 16 seats, adding Amazon, Meta, Microsoft, Salesforce and Stripe to members including Google, Shopify, Etsy, Target and Wayfair. Universal Commerce Protocol project, 24 April 2026
The specification and the checkout feature are different things. The specification is published and open. Google Merchant Center Help states that "the checkout feature enabled by UCP is available for select merchants at this time," that eligibility is limited to products in the United States, Canada and Australia, and that merchants express interest through a form. Retailers remain merchant of record. That wording was unchanged between 8 September and 9 November 2026. Google Merchant Center Help, Retrieved 9 November 2026
Google's consumer launches have moved ahead of that page. Universal Cart, with checkout powered by UCP, rolled out in the US across Google Search and the Gemini app on 15 October 2026, with Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair and many Shopify merchants named. Shoppers can check out with Google Pay or send the cart to the merchant's site. Google, 15 October 2026 On 4 November 2026 direct checkout powered by UCP began rolling out to Canadian shoppers in AI Mode and the Gemini app, and Google said simplified UCP integration will be available directly in Merchant Center from 2027. Google Canada, 4 November 2026 No merchant count or transaction volume has been published for either.
Where MCP fits
On 9 December 2025 Anthropic donated the Model Context Protocol to the Agentic AI Foundation, a directed fund under the Linux Foundation co-founded by Anthropic, Block and OpenAI with support from Google, Microsoft, AWS, Cloudflare and Bloomberg. MCP joined goose and AGENTS.md as founding projects, and its maintainers retain autonomy over technical direction. At donation the project reported 97 million+ monthly SDK downloads and 10,000 active servers. Model Context Protocol project, 9 December 2025 Anthropic, 9 December 2025 On 28 July 2026 it reported close to half a billion monthly downloads across its Tier 1 SDKs, a scope that may differ from the December figure. No newer server count has been published. Model Context Protocol project, 28 July 2026 MCP is not a commerce protocol. It defines how a model reaches tools and data, which is why UCP lists it as one transport among several, and it does not define carts, checkout or payment credentials. The MCP server directory lists the ecommerce servers that exist on it.
Agent-executed shopping: what has been measured
- Measures
- Agent-executed
- Geography
- Not stated
- Period
- Not stated; published Nov 2026
- Sample
- Quantum Metric platform data
- Method
- Vendor behavioral data
- Measures
- Agent benchmark
- Geography
- Not applicable
- Period
- Published 5 Nov 2026
- Sample
- 22 models; 15 scenarios; 3 attempts each
- Method
- Laboratory benchmark
- Measures
- Agent-executed
- Geography
- Europe
- Period
- 2 July 2026
- Sample
- Not applicable
- Method
- Company announcement
These are the first published measures of agents shopping on their own. Quantum Metric's figure comes from vendor platform data with no stated site count or period. Visa's is a laboratory benchmark that has not yet tested checkout or payment. Visa's European programme names issuers and merchants but no transaction count.
The two largest sponsors have taken different paths. OpenAI moved ChatGPT purchases to merchant-owned checkout in March 2026, and Walmart has reported in-chat conversion three times lower than click-out. Google launched checkout on its own surfaces in the US and Canada in October and November 2026, with Google Pay or a hand-off to the merchant's site. No conversion comparison for Google's checkout has been published.
The measurement blind spot
Every AI traffic figure on this page comes from a tag-based analytics tool or a first-party analytics dataset, and those tools are built to exclude automated requests. That design choice, together with attribution rules and platform log access, shapes what the numbers can and cannot show.
- 01 · Tag-based analytics reports human sessions by design
Google Analytics 4 excludes traffic from known bots and spiders automatically, using Google research and the Interactive Advertising Bureau's International Spiders and Bots List, and the exclusion cannot be disabled or its volume seen. Any figure from a tag-based tool is therefore a human-session figure by construction. The requests that AI systems make to fetch product pages on a shopper's behalf, or to crawl a catalog, live only in server logs. Google Analytics Help, Retrieved 8 September 2026
- 02 · User-agent strings are claims, not identity
Google publishes a verification procedure because, in its words, site owners may be "concerned that spammers or other troublemakers are accessing your site while claiming to be from Google." The procedure is a reverse DNS lookup on the requesting IP, or a match against Google's published IP range files. Google Search Central, Retrieved 8 September 2026 OpenAI publishes separate IP address lists for OAI-SearchBot, GPTBot and ChatGPT-User for the same reason. OpenAI, Retrieved 8 September 2026 Allowlists and blocklists built on user-agent strings alone work from unverified identity data.
- 03 · Attribution rules credit the last recorded touch
Google Analytics 4 attribution models assign credit to touchpoints by rule or by a data-driven algorithm, and every model excludes direct visits from receiving credit unless the whole path is direct. Google Analytics Help, Retrieved 8 September 2026 A shopper who researches in an LLM without clicking through, then buys via a branded search or by typing the URL, leaves no AI touchpoint to credit. The purchase is attributed to search, or to whatever preceded the direct visit.
- 04 · Some platforms expose no server logs at all
The only unambiguous record of automated requests is the server or edge log, and not every hosted platform gives merchants one. Our server log monitoring guide documents what each major platform exposes; Shopify's online store, for example, offers no web server or edge log access, so merchants there cannot see crawler activity directly.
In the Comscore desktop panel, ChatGPT produced an outbound click in 5.2% of conversation sessions, against 31.1% of Google queries. Shi et al., Bocconi University, arXiv 2607.07652, 8 July 2026 Ecommerce Guide reading: taken together, these mean most referral figures on this page probably understate AI influence rather than overstate it, because the research step that happens inside an assistant and never produces a click is invisible to every referral dataset cited here. The only measurement that captures automated activity with verified identity is server-side, matched against published IP ranges and confirmed with reverse DNS, which are the two methods Google documents.
What these statistics mean for ecommerce teams
Split by how much evidence sits behind each practice. The first group is measurement and data hygiene that the sources on this page directly support. The second group is work whose effect nobody has yet measured in public.
Established practice
- Analytics and attribution setup
Know which attribution model your reporting uses and what it does with direct visits, so an AI-assisted purchase that returns as direct or branded search is at least a known gap rather than an invisible one.
- Identify AI referrals in reporting
Adobe measures AI referrals as shoppers clicking a link from a generative AI chat service or browser. The same referrer-based definition can be applied in any analytics tool, and it is the only definition under which the Adobe and Kaiser and Schulze figures are comparable with your own.
- Server-log and crawler monitoring
Automated requests from AI systems do not appear in tag-based analytics. Server-side logging with verification against published IP ranges and reverse DNS is the established way to see them.
- Product feed completeness and accuracy
OpenAI describes ACP as the layer through which merchants share product feeds and promotions so their catalogs are represented in ChatGPT, and Shopify Catalog does this for Shopify merchants with no additional work. The product feed management tools directory covers the software category.
- Product and Offer structured data, catalog APIs and Merchant Center feeds
UCP's catalog capability is designed to give agents real-time variants, inventory and pricing, and Google's UCP onboarding runs through Merchant Center product data.
- Inventory and price accuracy
Google's UCP documentation makes the merchant of record responsible for real-time inventory checks and requires an out-of-stock error during checkout when an item is unavailable, which halts that transaction. Google for Developers, Retrieved 9 November 2026 The UCP catalog specification states that catalog responses are not transactional commitments and that checkout is authoritative, so a catalog that disagrees with checkout fails at the point of sale. Universal Commerce Protocol project, Retrieved 9 November 2026
Experimental
- Content and citation visibility tactics
No source on this page demonstrates that any content change causes higher visibility inside an assistant. Tools that monitor brand mentions across assistants exist and are listed in the AI visibility tools directory; what they measure is presence, not cause.
- Whether to test ACP, UCP or MCP integrations
As of November 2026: ACP discovery integration has a low-cost path for Shopify merchants through Shopify Catalog with no per-merchant work, and named large retailers have integrated directly; OpenAI charges no fees on purchases that start in ChatGPT. UCP checkout is live for shoppers in the US through Universal Cart and rolling out in Canada, while Merchant Center Help still describes merchant access as select merchants, with simplified integration in Merchant Center promised from 2027. MCP is not a commerce decision; it is an integration standard that UCP can use as a transport. Anything stronger than that is not supported by the sources on this page.
- Consent and delegated purchasing design
AP2 version 0.2 models purchases through a signed Checkout Mandate and Payment Mandate, including human-not-present flows. Survey answers on delegation range from 16% who would let AI complete a purchase with permission (Deloitte) to 26% of AI shoppers who say they have (Menlo Ventures). Quantum Metric reports retail agents abandoning 48 carts per completed purchase. No published dataset yet shows what spending limits shoppers set.
- Fraud and identity controls for agent traffic
The verification methods above establish whether a request is from a named crawler. They do not yet establish which human, if any, an agent acts for, and no source here reports fraud rates for agent-initiated orders.
Every headline figure with its measurement, sample and grade
Only figures retrieved from a primary document appear here. The grade describes the type of evidence, not the accuracy of the number; an A-grade panel can still be unrepresentative of the market.
| Statistic | Grade | What it measures | Geography | Period | Sample or dataset | Source |
|---|---|---|---|---|---|---|
| +90% conversion for AI referrals vs non-AI traffic | A | AI-referred, against Adobe's blended non-AI baseline | US | September 2026 | 1 trillion+ visits, analytics panel | Adobe Analytics, 29 October 2026 |
| +83% revenue per visit for AI referrals vs non-AI traffic | A | AI-referred, against Adobe's blended non-AI baseline | US | September 2026 | 1 trillion+ visits, analytics panel | Adobe Analytics, 29 October 2026 |
| +71% AI-referred retail traffic, year over year | A | AI-referred: humans clicking from an AI surface to a US retail site | US | September 2026 | 1 trillion+ visits, analytics panel | Adobe Analytics, 29 October 2026 |
| +693% AI-referred retail traffic, year over year | A | AI-referred | US | 1 Nov to 31 Dec 2025 | 1 trillion+ visits, analytics panel | Adobe Analytics, 12 January 2026 |
| AI referrals 23% less likely to convert than non-AI | A | AI-referred, against Adobe's blended non-AI baseline | US | July 2025 | 1 trillion+ visits, analytics panel | Adobe Analytics, 21 August 2025 |
| 0.2% of web traffic from AI-referred sources; +632% year over year | A | AI-referred, cross-industry | Global | Q4 2025 | 99 billion sessions; 6,500 sites | Contentsquare, 2026 Digital Experience Benchmarks, 29 January 2026 |
| Affiliate traffic 86% and organic search 13% more likely to convert than ChatGPT referrals; paid social 53% less | A | AI-referred, organic ChatGPT only, against each named channel | Global | 2 Feb to 2 Aug 2025 | 973 sites; 10.5 billion sessions | Kaiser and Schulze, Marketing Science 45(4):699-715, Published online 21 April 2026 (SSRN 5585812, last revised 27 July 2026) |
| ChatGPT referral conversion approximately matched organic search before February 2026 | A | AI-referred, organic ChatGPT only | 9 countries plus EU-27 | 30 Jun 2025 to Feb 2026 | 1,898 sites; working paper | Kaiser and Schulze, working paper, October 2026 (version 1) |
| ChatGPT sends an outbound click in 5.2% of sessions; Google in 31.1% of queries | A | AI-referred click-out rate | US, desktop | Oct 2024 to Jul 2025 | 45,386 households; preprint | Shi et al., Bocconi University, arXiv 2607.07652, 8 July 2026 |
| $262B, 20% of holiday sales, driven by AI and agents | A | AI-influenced: personalized recommendations and customer engagement | Global | 1 Nov to 31 Dec 2025 | 1.5 billion+ shoppers, Shopping Index | Salesforce, 8 January 2026 |
| AI-influenced Cyber Week sales: $51B (2023), $60B (2024), $67B (2025) | A | AI-influenced, Salesforce definition, which changed between years | Global | Cyber Week 2023 to 2025 | 1.5 billion+ shoppers, Shopping Index | Salesforce, 5 December 2025 |
| 42% have used AI assistants for online shopping | B | Self-reported behavior | US | July 2026 | n = 5,000+, survey | Adobe Digital Insights, 19 August 2026 |
| 25% have used Gen AI shopping tools; a further 31% plan to | B | Self-reported behavior; intention | 12 countries | October 2025 | n = 12,000, survey | Capgemini Research Institute, 6 January 2026 |
| 26% of US shoppers who use AI let it complete a purchase | B | Agentic behavior | US | July 2026 | n = 5,067, survey | Menlo Ventures, survey by Morning Consult, 16 September 2026 |
| 16% would let generative AI complete a purchase with permission | B | Stated preference | US | Aug to Sep 2026 | n = 3,700, survey | Deloitte, 15 October 2026 |
| 3.3× orders from AI searches; +64% conversion vs organic search | C | AI-referred, company disclosure | Not stated | Q3 2026 | Shopify storefronts | Shopify Investor Relations, 3 November 2026 |
| 400M+ customers used Alexa for Shopping; interactions +570% | C | Retailer-owned assistant usage | Not stated | 12 months to Q3 2026 | Amazon customers | Amazon Investor Relations, 29 October 2026 |
| Retail AI agents abandon 48 carts per completed purchase | C | Agent-executed | Not stated | Published Nov 2026 | Vendor platform data | Quantum Metric, 2026 Peak Benchmark, 5 November 2026 |
| 42.8% of simulated agent shopping runs failed | C | Agent benchmark | Not applicable | Published 5 Nov 2026 | 22 models, 15 scenarios | Visa, 5 November 2026 |
| In-chat checkout converted 3× lower than click-out to the merchant | C | Company disclosure, Walmart | US | Reported March 2026 | One retailer | Modern Retail, 27 March 2026 |
| UCP checkout live for shoppers in the US and Canada | C | Protocol status | US, CA | 15 Oct and 4 Nov 2026 | Not applicable | Google, 15 October 2026 |
Forecasts, grade D, not measured results
- Measures
- Forecast
- Geography
- US
- Period
- 1 Nov to 31 Dec 2026
- Sample
- Not applicable
- Method
- Forecast
- Measures
- Forecast
- Geography
- Global
- Period
- By 2030
- Sample
- Not applicable
- Method
- Forecast
How this page is researched and updated
Every statistic on this page links to the organization that produced the data, not to a report about it. Where a figure originates in a vendor's own release, earnings material, or a research paper, we link to that document. Where we have been unable to retrieve the underlying document, the figure has been removed rather than retained on trust. Each statistic carries its geography, the period measured, the sample or dataset size where disclosed, and the method used. Where two credible sources disagree, both are shown with their definitions, and we explain why they can differ rather than averaging them.
Published April 19, 2026. Last reviewed November 9, 2026, when every source below was opened and each figure checked against it. Any calculation performed by us is labeled "Ecommerce Guide calculation" or "Ecommerce Guide reading" in place. Maintained by the Ecommerce Guide editorial team; contact details are in the site footer.
Figures checked and not used
- A 4% merchant fee for ACP or Instant Checkout. No OpenAI, Stripe or Shopify document states a rate; OpenAI's merchant page says there are no fees on purchases that start in ChatGPT.
- "About 7 times" AI traffic growth for Shopify. It appears in third-party call transcripts, not in Shopify's releases, decks or investor site.
- $14.2 billion global and about $3 billion US AI-influenced Black Friday 2025 sales. No Salesforce-owned page states them or defines them.
- 805% AI traffic growth on Black Friday 2025. Adobe's own chart data labels 805% as season to date for 1 to 28 November 2025, not a single day, and no Adobe release states it. The season figure on this page is 693.4%.
- A count of merchants live on Instant Checkout. OpenAI has not published one.
Evidence grades
Grades describe the type of evidence, not the accuracy of the number. An A-grade panel can still be unrepresentative, and a C-grade company disclosure can be exactly right about the one company it describes.
- A
- Large first-party behavioral or transaction dataset: the Adobe Analytics panel, the Salesforce Shopping Index, Contentsquare's benchmark, the Kaiser and Schulze site panels, the Comscore household panel.
- B
- Credible survey with disclosed methodology, sample and fielding period.
- C
- Company disclosure, earnings material, product documentation, a laboratory benchmark, or a vendor dataset whose sample or period is not disclosed.
- D
- Secondary report, unclear methodology, or a directional estimate or forecast.
▸Sources cited on this page (66), with method, sample and what each cannot tell you
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites. AI traffic is measured by shoppers clicking a link from a generative AI chat service or browser. Geography: United States. Sample: 1 trillion+ visits.Limitations: Single-day and month-to-date figures. Adobe notes the base of AI users remains modest.
- Adobe: U.S. holiday shopping season to hit record $275.1 billion online, rising 6.7% YoYAdobe, 28 September 2026Grade DMethod: Forecast based on the Adobe Analytics panel. Companion survey of 5,000 US consumers. Geography: United States. Sample: Not applicable (forecast).Limitations: A forecast, not a measured result.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. AI traffic measured by shoppers clicking on a link. Geography: United States. Sample: 1 trillion+ visits.Limitations: Covers the four-day event of 8 to 11 July 2025 against a very small 2024 base. The release gives no AI conversion figure for the event.
- Generative AI-powered shopping rises with traffic to retail sitesAdobe Analytics, 21 August 2025Grade AMethod: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Companion consumer survey. Geography: United States. Sample: 1 trillion+ visits (behavioral); n = 5,000 US consumers (survey).Limitations: Weighted toward large US retailers that run Adobe Analytics. Growth rates for January and April 2025 are indexed to July 2024, not year over year, because the base was too small before then. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel.
- Consumers spent $88.7 billion online in October 2025, with AI-powered shopping continuing to riseAdobe Analytics, 10 November 2025Grade AMethod: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Geography: United States. Sample: 1 trillion+ visits.Limitations: Same panel and same blended non-AI comparator as the August 2025 release. Monthly figures, so single-month conversion differences can move with promotional calendars.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites. Companion Holiday 2025 Consumer Survey. Geography: United States. Sample: 1 trillion+ visits (behavioral); n = 1,000+ US respondents (survey).Limitations: Covers the 2025 holiday season (1 November to 31 December), a peak period with gift intent and deadlines. The companion survey is smaller than the August 2025 survey (1,000+ against 5,000), so the two survey series are not directly comparable. The +254% revenue-per-visit figure in this release is growth in AI's own revenue per visit, not a gap against non-AI traffic.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Companion consumer survey. Geography: United States. Sample: 1 trillion+ visits.Limitations: First-quarter 2026 and March 2026 figures. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel. The companion survey's fielding period is not stated.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Geography: United States. Sample: 1 trillion+ visits.Limitations: The 2026 event ran in June and the 2025 event in July, so the year-over-year comparison spans different calendar weeks. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Geography: United States. Sample: 1 trillion+ visits.Limitations: Single-month figures for September 2026, the latest month Adobe had published at 9 November 2026. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Geography: United States. Sample: 1 trillion+ visits.Limitations: Holiday 2025 figures. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Geography: United States. Sample: 1 trillion+ visits.Limitations: Single-month figures for May 2026. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel. Some charts in the PDF extract inconsistently against Adobe's HTML data tables; only figures stated in the report text are used here.
- Method: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Adobe Consumer Survey of more than 5,000 US respondents, fielded July 2026. Geography: United States. Sample: 1 trillion+ visits (behavioral); n = 5,000+ US respondents (survey).Limitations: Single-month figures for July 2026. The non-AI comparator is a blend of paid search, affiliates and partners, email, organic search and social media, so a lift against it is not a lift against any single channel. The survey is a different instrument from Adobe's August 2025 and Holiday 2025 surveys.
- 2026 Holiday Shopping Trends, Statistics & ForecastAdobe Digital Insights, Live page, retrieved 9 November 2026Grade AMethod: Adobe Analytics panel of over 1 trillion visits to US retail sites, 100 million SKUs, 18 product categories. Geography: United States. Sample: 1 trillion+ visits.Limitations: A live page that Adobe updates through the season without a changelog. The August 2026 traffic figure is a measurement; the holiday figures on the same page are forecasts, and its Thanksgiving forecast (141%) differs from the 28 September 2026 press release (159%).
- Method: Foundation announcement. Geography: Global specification. Sample: Not applicable.Limitations: Governance announcement. The 150+ organization figure is self-reported.
- Method: Earnings release. Geography: Not stated. Sample: Amazon customers.Limitations: Amazon does not explain how it measures incremental annualized sales. Covers Amazon's own assistant on Amazon only.
- Method: Earnings release. Geography: Not stated. Sample: Amazon customers.Limitations: Alexa for Shopping combines Rufus and Alexa+, so the customer count does not compare directly with earlier Rufus figures.
- Donating the Model Context Protocol and establishing the Agentic AI FoundationAnthropic, 9 December 2025Grade CMethod: Company announcement. Geography: Global specification. Sample: Not applicable.Limitations: Server counts are self-reported at the time of donation and count integration activity, not commerce transactions.
- Agent Payments Protocol specificationAP2 project, Retrieved 9 November 2026 (version 0.2, 28 April 2026)Grade CMethod: Protocol specification. Geography: Not applicable. Sample: Not applicable.Limitations: A specification. Says nothing about adoption.
- What matters to today's consumer 2026: how AI is transforming value perceptionCapgemini Research Institute, 6 January 2026Grade BMethod: Online questionnaire. Report methodology dates fielding to October 2025; the press release says October and November 2025. Geography: Australia, Canada, France, Germany, India, Italy, Japan, the Netherlands, Spain, Sweden, the UK and the US. Sample: n = 12,000 consumers aged 18 and over (11,681 in the 2023 wave).Limitations: Multi-country, so not comparable with US-only surveys. The report describes its findings as directional guidance.
- AI is rewriting how consumers discover brands and raising the stakes for experience and loyaltyContentsquare, 2026 Digital Experience Benchmarks, 29 January 2026Grade AMethod: Analysis of 99 billion sessions, 500 billion page views and 6,500 websites, Q4 2024 against Q4 2025 (October to December). Geography: Global. Sample: 99 billion sessions; 6,500 websites.Limitations: Cross-industry, not retail only. Conversion benchmarks include only sites that collect conversion data. Contentsquare sells the analytics product the data comes from.
- Method: Online panel survey, fielded 26 August to 10 September 2026. Margin of error ±2 points. Geography: United States. Sample: n = 4,000; n = 3,700 for these items.Limitations: Asked before the season, so "primary tool" may describe plans as well as past behavior.
- Method: Company announcement. Geography: United States. Sample: Not applicable.Limitations: Names merchants but gives no usage, merchant count or transaction figures.
- Method: Company announcement. Geography: Global specification. Sample: Not applicable.Limitations: A governance announcement with no adoption figures.
- Method: Company announcement. Geography: Global specification. Sample: Not applicable.Limitations: Announces optional capabilities. Says nothing about how many merchants have adopted them.
- Google Analytics 4: known bot traffic is excluded automaticallyGoogle Analytics Help, Retrieved 8 September 2026Grade CMethod: Product documentation. Geography: Not applicable. Sample: Not applicable.Limitations: Describes Google Analytics 4 only.
- Google Analytics 4: attribution models and lookback windowsGoogle Analytics Help, Retrieved 8 September 2026Grade CMethod: Product documentation. Geography: Not applicable. Sample: Not applicable.Limitations: Describes Google Analytics 4 only.
- A new way to shop: introducing a more intuitive, agentic shopping experience for consumers and retailers in CanadaGoogle Canada, 4 November 2026Grade CMethod: Company announcement. Geography: Canada. Sample: Not applicable.Limitations: Names merchants but gives no merchant count or volume.
- Powering AI commerce with the new Agent Payments Protocol (AP2)Google Cloud, 16 September 2025Grade CMethod: Company announcement. Geography: Global specification. Sample: Not applicable.Limitations: A launch announcement with partner names and no adoption figures.
- Method: Company announcement and technical overview. Geography: Global specification. Sample: Not applicable.Limitations: Describes the specification and its partners. Says nothing about live transaction volume.
- Universal Commerce Protocol on Google: frequently asked questionsGoogle for Developers, Retrieved 9 November 2026Grade CMethod: Product documentation. Geography: Not applicable. Sample: Not applicable.Limitations: Documentation for Google's implementation of UCP checkout only.
- Universal Commerce Protocol checkout: availability and eligibilityGoogle Merchant Center Help, Retrieved 9 November 2026Grade CMethod: Product documentation. Geography: United States, Canada and Australia. Sample: Not applicable.Limitations: Documentation is updated without a changelog. The wording was identical on 8 September and 9 November 2026, after Google's blog had announced the US Universal Cart and the Canadian rollout.
- Verify requests from Google crawlers and fetchersGoogle Search Central, Retrieved 8 September 2026Grade CMethod: Product documentation. Geography: Not applicable. Sample: Not applicable.Limitations: Describes Google's crawlers only.
- Frontiers: ChatGPT Referrals to E-Commerce Websites: How Do LLMs Compare Against Traditional Channels?Kaiser and Schulze, Marketing Science 45(4):699-715, Published online 21 April 2026 (SSRN 5585812, last revised 27 July 2026)Grade AMethod: Google Analytics first-party data from 973 websites, aggregated weekly, last-click attribution. Quasibinomial and weighted linear models with website, device and month fixed effects. Channel comparisons use 2 February to 2 August 2025; transaction counts use 28 July 2024 to 2 August 2025. Geography: Global. The Americas (2.7 billion sessions) and Europe (2.1 billion sessions) hold the majority; the US contributes 1.8 billion sessions. Sample: 973 websites; 10.5 billion sessions; 50,251 ChatGPT referral transactions; 164,875,690 traditional-channel transactions.Limitations: Peer reviewed. Descriptive, not causal. Sites span 24 categories including finance, travel and jobs, so it is not retail only, and a conversion is any financial transaction. Isolates organic ChatGPT referrals only. The first author is employed by the data provider, which the paper discloses. The organic search gap is not statistically significant in five of the robustness specifications. The window ends before the late 2025 crossover in Adobe's US series.
- Can Advertising Fund Free AI? Evidence from ChatGPT's ad rolloutKaiser and Schulze, working paper, October 2026 (version 1)Grade AMethod: Google Analytics 4 last-click data from 1,898 websites, 30 June 2025 to 22 August 2026. Staggered difference-in-differences around ChatGPT's ad rollout, with EU-27 traffic as the untreated control. Geography: US, Australia, Canada, New Zealand, UK, Japan, South Korea, Brazil, Mexico and EU-27. Sample: 1,898 websites; 22,408,828 organic ChatGPT sessions; 446,090 ChatGPT transactions.Limitations: A working paper, not peer reviewed. The panel includes only sites with more than 10 ChatGPT transactions, so it is not a like-for-like continuation of the 973-site paper. "Approximately matched" is descriptive; no coefficient is given. The paid ChatGPT comparison uses 102 advertiser sites skewed to services, software and finance.
- A2A protocol surpasses 150 organizations, lands in major cloud platforms, and sees enterprise production use in first yearLinux Foundation, 9 April 2026Grade CMethod: Foundation press release. Geography: Global specification. Sample: Not applicable.Limitations: Organization counts are self-reported by the foundation.
- Linux Foundation announces the formation of the Agentic AI FoundationLinux Foundation, 9 December 2025Grade CMethod: Foundation press release. Geography: Global. Sample: Not applicable.Limitations: Governance announcement only.
- The agentic commerce opportunity: how AI agents are ushering in a new era for consumers and merchantsMcKinsey & Company, October 2025Grade DMethod: Estimate based on US Census data and forecast adoption rates. Geography: Global; US B2C for the narrower figure. Sample: Not applicable (forecast).Limitations: A 2030 forecast. "Orchestrate" is not defined. Goods only; services and B2B are excluded.
- Method: Online survey, weighted to be nationally representative, fielded July 2026. Geography: United States. Sample: n = 5,067 US adults; size of the AI-shopper subgroup not stated.Limitations: "Complete a purchase" is not defined. Menlo Ventures is a venture capital investor in consumer AI companies.
- Method: Project announcement. Geography: Global specification. Sample: Not applicable.Limitations: Project's own statement of its governance and usage. Download counts include dependency pulls.
- Method: Project announcement. Geography: Global specification. Sample: Not applicable.Limitations: Self-reported. Counts Tier 1 SDKs, which may not match the scope of the December 2025 figure, so no growth rate is calculated. Downloads include dependency pulls. No server count newer than December 2025 has been published.
- Method: Reporting of comments by Walmart EVP Daniel Danker to Wired, and an Etsy statement. Geography: United States. Sample: Two named companies.Limitations: A named-executive disclosure reported by a trade publication. Walmart did not publish the underlying data. Two retailers, not a market measurement.
- Handing shopping over to AI: how far will shoppers actually go?Omnisend, survey by Cint, 18 March 2026Grade BMethod: Online survey, fielded late January 2026. Margin of error ±3%. Geography: United States (part of a four-country survey). Sample: n = 1,072 US respondents.Limitations: A vendor survey. Question wording is not published. The 38% figure sits awkwardly with how few merchants Instant Checkout reached before it was dropped, and no other survey on this page reports a comparable share.
- Method: Company announcement. Geography: Global rollout to free, Go, Plus and Pro users. Sample: Not applicable.Limitations: Describes OpenAI's own product direction. Names retailers integrated for discovery but gives no usage or conversion figures.
- Method: Merchant documentation. Geography: Not stated. Sample: Not applicable.Limitations: Undated. OpenAI's developer documentation still describes Instant Checkout as available to approved partners, which conflicts with this page.
- Method: Product documentation. Geography: Not applicable. Sample: Not applicable.Limitations: Describes OpenAI's crawlers only.
- Agentic Commerce Protocol specificationOpenAI and Stripe, ACP repository, Retrieved 9 November 2026 (latest stable version 2026-04-17)Grade CMethod: Protocol specification. Geography: Not applicable. Sample: Not applicable.Limitations: The specification is in beta and versioned by dated folders, not tagged releases.
- Method: Online survey, fielded 15 to 26 June 2026, broadly representative of the US population. Geography: United States. Sample: n = 4,093.Limitations: Intention measured in June for a season that starts in November.
- Quantum Metric research finds shoppers are tuning out peak sales as AI decides where and when they buyQuantum Metric, 2026 Peak Benchmark, 5 November 2026Grade CMethod: Aggregated, anonymized behavioral data from the Quantum Metric platform, combined with a survey of 1,500 consumers in the US and UK. Geography: Not stated for the behavioral data; survey US and UK. Sample: Platform data, size not stated; n = 1,500 (survey).Limitations: The press release does not state the number of sites, the period, or how agent sessions are identified. A vendor dataset.
- AI and agents propel Cyber Week to record $336.6B in global online salesSalesforce, 5 December 2025Grade AMethod: Salesforce Shopping Index, aggregated commerce data from over 1.5 billion shoppers on Salesforce-powered storefronts, with AI and agent activity measured through Agentforce and Commerce Cloud. Salesforce applies factors to extrapolate to the broader retail industry. Geography: Global, with a US split. Sample: 1.5 billion+ shoppers.Limitations: AI-influenced spend is defined by Salesforce as purchases influenced by personalized product recommendations and conversational customer service. It is retailer-owned AI, not LLM referral traffic, and the two cannot be compared. Dollar totals are extrapolated to the industry using first-party data, third-party data and market assumptions. The Agentforce growth comparison is between Salesforce's own customers and non-users, not a random sample of retailers.
- Method: Salesforce Shopping Index, 1.5 billion+ shoppers on Salesforce-powered storefronts, extrapolated to the broader retail industry. Geography: Global. Sample: 1.5 billion+ shoppers.Limitations: AI-influenced is Salesforce's definition: sales driven "through personalized recommendations and deeper customer engagement." Retailer-owned AI, not LLM referral traffic. Dollar totals are extrapolated to the industry. A later Salesforce page (24 June 2026) cites the same dataset as eight times rather than nine times for the AI-search versus social conversion comparison.
- Salesforce data reveals new Cyber Week all-time high: $314.9B in global salesSalesforce, 4 December 2024Grade AMethod: Salesforce Shopping Index, Cyber Week 2024 (26 November to 2 December 2024). Geography: Global. Sample: 1.5 billion+ shoppers.Limitations: The 2024 definition covers online sales influenced by AI and agents including targeted offers, so it is not identical to the 2025 definition. Salesforce's measurement of AI influence has expanded as its own agent products launched, so year-to-year comparison partly reflects product coverage.
- Method: Forecast, not a measured result. Geography: Global. Sample: Not applicable.Limitations: A forecast for 27 November to 1 December 2025. The reported result covers 25 November to 1 December, so the windows differ. Cited on this page only to show that the forecast ($73 billion, 22%) exceeded the reported result ($67 billion, 20%).
- Method: Salesforce Shopping Index, Cyber Week 2023 (21 to 27 November 2023). Geography: Global. Sample: 1.5 billion+ shoppers.Limitations: The 2023 figure predates Salesforce's Agentforce products. It counts online sales influenced by targeted offers, product recommendations and generative AI-powered chat services.
- Answering Without Referring: How AI Search Rewrites the Web's Economic BargainShi et al., Bocconi University, arXiv 2607.07652, 8 July 2026Grade AMethod: Comscore desktop browsing panel, balanced panel of 45,386 households. Geography: United States. Sample: 45,386 households.Limitations: A preprint, not peer reviewed. Desktop browsing only, so mobile and the ChatGPT app are excluded. Covers October 2024 to July 2025.
- AI and organic search are doing different jobs: what Shopify's data showsShopify, 11 August 2026Grade CMethod: Company analysis of Q2 2026 storefront sessions and orders. Geography: Not stated. Sample: Shopify merchant storefronts.Limitations: A company blog. Method and merchant sample are not disclosed.
- Method: Company disclosure in investor materials. Geography: Not stated. Sample: Shopify merchant storefronts.Limitations: Shopify words its AI traffic metric differently each quarter (referral sessions from AI chatbots, AI-referred sessions, AI traffic to merchant storefronts) and does not say whether the definition changed, so the quarterly multiples are not one series. Method not disclosed.
- Method: Modeled web traffic estimates from Similarweb's panel and data partners. Geography: Not stated on the public page. Sample: Not stated on the public page.Limitations: The full report is gated. The public page gives neither the period nor the geography behind the 0.4% and 203% figures. Modeled estimates, not first-party analytics.
- Stripe powers Instant Checkout in ChatGPT and releases Agentic Commerce Protocol codeveloped with OpenAIStripe, 29 September 2025Grade CMethod: Company announcement. Geography: United States at launch. Sample: Not applicable.Limitations: A launch announcement. It contains no merchant fee figure and no volume figures.
- Method: Project governance announcement. Geography: Global specification. Sample: Not applicable.Limitations: Governance only. Says nothing about adoption.
- Universal Commerce Protocol specification: catalog capability (draft)Universal Commerce Protocol project, Retrieved 9 November 2026Grade CMethod: Protocol specification, draft. Geography: Not applicable. Sample: Not applicable.Limitations: A draft specification that can change between retrievals.
- Visa releases first-of-its-kind industry benchmark for AI shopping; almost half of test runs failVisa, 5 November 2026Grade CMethod: Simulated benchmark: 22 AI models from 12 labs, 15 shopping scenarios, three attempts each. Geography: Not applicable. Sample: 22 models; 15 scenarios; 3 attempts each.Limitations: A laboratory test, not live shopping. Test dates are not stated. Checkout and payment steps were not yet tested.
- Visa and banks across Europe reach the next phase of agentic commerceVisa Europe, 2 July 2026Grade CMethod: Company announcement. Geography: Europe. Sample: Not applicable.Limitations: Gives issuer and merchant names but no transaction count or value.
- Secret SantAI? Visa survey finds Americans quietly turning to AI for holiday shopping helpVisa, survey by Morning Consult, 30 October 2026Grade BMethod: Survey fielded late September 2026. Geography: United States. Sample: n = 1,000+ US adults.Limitations: Exact fielding dates and sample size are given only approximately.
- New Visa research finds consumer trust is accelerating the path to agentic commerceVisa, survey by The Harris Poll, 9 September 2026Grade BMethod: Online survey, fielded 26 to 28 May 2026. Geography: United States. Sample: n = 2,065.Limitations: Sponsored by a payment network with an interest in agentic payments.
- Method: Executive remarks on the official earnings call transcript. Geography: United States. Sample: Walmart app users.Limitations: Spoken remarks, not in the earnings release. Users and non-users of Sparky self-select, so the order value difference is not an effect of Sparky.
- Method: Executive remarks on the official earnings call transcript. Geography: Not stated. Sample: Walmart customers and members.Limitations: Spoken remarks, not in the earnings release. Users and non-users of Sparky self-select.
Frequently asked questions
- How much ecommerce traffic comes from AI?
- Still a small share. Contentsquare's benchmark of 99 billion sessions across 6,500 sites puts AI-referred sources at 0.2% of total traffic in Q4 2025, after 632% growth. A 1,898-site panel by Kaiser and Schulze puts organic ChatGPT referrals at 0.40% of sessions in the four weeks to 17 August 2026. Similarweb puts generative AI at 0.4% of retail ecommerce visits. Adobe does not publish a share; it reports AI-referred traffic to US retail sites up 71% year over year in September 2026.
- Does AI referral traffic convert better than Google search?
- Shopify reports AI-referred sessions converting 64% better than organic search on its storefronts in Q3 2026. Adobe's US retail panel reports AI referrals converting 90% better than a blended non-AI baseline, which includes organic search, in September 2026. Kaiser and Schulze's 1,898-site panel finds ChatGPT conversion approximately matched organic search before February 2026. Their peer-reviewed study of February to August 2025 found organic search 13% more likely to convert than ChatGPT referrals. Comparators, periods and populations differ across all four.
- What share of consumers use AI for shopping?
- In Adobe's July 2026 survey of more than 5,000 US consumers, 42% reported having used AI assistants for online shopping, up from 38% in its 2025 survey of 5,000. Capgemini's survey of 12,000 consumers in 12 countries, fielded October 2025, puts use of generative AI shopping tools at 25%, with a further 31% planning to use them. Visa's late-September 2026 survey of 1,000+ US adults found 54% had used AI for at least one shopping task. Question wording differs, so the figures are not comparable.
- What is agentic commerce?
- Commerce in which a software agent acts for a shopper: discovering products, assembling a cart, and in some designs completing payment. As of November 2026, ChatGPT uses the Agentic Commerce Protocol for product discovery and sends purchases to merchant-owned sites and apps, having moved away from in-chat Instant Checkout in March 2026. Google offers checkout powered by its Universal Commerce Protocol through Universal Cart in the US from 15 October 2026 and direct checkout in Canada from 4 November 2026.
- Do shoppers let AI agents complete purchases?
- Some say they do. In a Menlo Ventures and Morning Consult survey of 5,067 US adults, fielded July 2026, 26% of shoppers who use AI said they let it complete a purchase. In Deloitte's 2026 holiday survey, 16% of US respondents would let generative AI complete a purchase with their permission. Behavioral data is thinner: Quantum Metric reports retail AI agents abandoning 48 carts for every completed purchase, and Visa's benchmark found 42.8% of simulated shopping runs by 22 AI models failed.
- How much retail revenue is AI-influenced?
- Salesforce reports that AI and agents drove 20% of global 2025 holiday retail sales, $262 billion, through personalized recommendations and deeper customer engagement, and $67 billion of Cyber Week 2025 sales. The Cyber Week series runs $51 billion in 2023, $60 billion in 2024 and $67 billion in 2025, with the definition changing between years. Salesforce extrapolates these totals to the whole industry from 1.5 billion+ shoppers on its storefronts. This is retailer-owned AI, not LLM referral traffic.
- How many people use retailer AI shopping assistants?
- Amazon reports that 400 million+ customers used Alexa for Shopping, which combines Rufus and Alexa+, in the 12 months to Q3 2026, with interactions up 570% year over year. For 2025, Amazon said Rufus was used by 300 million+ customers and delivered nearly $12 billion in incremental annualized sales, without disclosing the method. Walmart said in February 2026 that roughly half of its app users had used Sparky, and in August 2026 that Sparky users were up 70% year over year.
- What is the difference between ACP, UCP and MCP?
- ACP, maintained by OpenAI and Stripe and still in beta, specifies product feeds, cart, checkout, delegated payment and orders; ChatGPT uses it for discovery only. UCP, led by Google with a 16-seat Tech Council that includes Shopify, Amazon, Microsoft and Stripe, covers discovery, an optional cart, checkout and post-purchase, with payments via AP2, and powers Google's checkout in the US and Canada. MCP, governed by the Agentic AI Foundation under the Linux Foundation, is a model-to-tool integration standard with no cart, checkout or payment primitives.
- Is ChatGPT still the largest source of LLM referral traffic?
- It was in the most recent peer-reviewed data. In Kaiser and Schulze's 973-site study, covering July 2024 to August 2025, ChatGPT accounted for over 90% of sessions from LLM platforms, with Perplexity at 4.1%, Gemini at 2.6% and Copilot at 2.1%. No retrievable primary source on this page measures the split for 2026.
- Can retailers accurately attribute AI-assisted purchases?
- Not with tag-based analytics alone. Google Analytics 4 excludes known bot traffic automatically, so automated requests from AI systems never appear, and its attribution models give no credit to direct visits, so a shopper who researches in an assistant and returns by typing the URL or searching the brand is credited elsewhere. In a US desktop panel, ChatGPT produced an outbound click in 5.2% of sessions against 31.1% of Google queries. Server-side logs with crawler identity verified against published IP ranges and reverse DNS are the only record of the automated side.
