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AI ecommerce statistics 2026: traffic, conversion, and agentic commerce

Verified AI ecommerce statistics for 2026: AI referral traffic and conversion, AI-influenced sales, retailer assistants, consumer surveys, and the status of ACP, UCP and MCP.

On this page

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.

+90%
AI-referred visits to US retail sites converted 90% better than non-AI traffic in September 2026, the highest level Adobe has recorded
Measures
AI-referred
Geography
US
Period
September 2026
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+71%
Year-over-year growth in AI-referred traffic to US retail sites, September 2026
Measures
AI-referred
Geography
US
Period
September 2026
Sample
1 trillion+ visits
Method
Analytics panel
$262B
Global 2025 holiday sales that Salesforce reports as driven by AI and agents, 20% of all retail sales
Measures
AI-influenced
Geography
Global
Period
1 Nov to 31 Dec 2025
Sample
1.5 billion+ shoppers
Method
Shopping Index, retailer-side AI
42%
of US consumers report having used AI assistants for online shopping
Measures
Self-reported behavior
Geography
US
Period
Survey, July 2026
Sample
n = 5,000+
Method
Consumer survey
00 · Definitions

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.

Measurement terms used on this page
TermMeansOn this page
AI-referredA 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-influencedAI 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-attributedRevenue 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-executedAn 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 benchmarkAI models tested on simulated shopping tasks, not live traffic.Visa's benchmark of 22 models across 15 scenarios.
AI crawler activityAutomated requests from bots, not human sessions.Never mixed with referral traffic on this page.
Retailer-owned assistant usageUse 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

Consumer survey terms used on this page
TermMeansOn this page
Stated preferenceWants, trusts or would allow something.Deloitte: 16% would let generative AI complete a purchase with permission.
IntentionPlans to use AI for shopping.Capgemini: a further 31% plan to use generative AI shopping tools.
Self-reported behaviorSays they have used AI for shopping.Adobe, July 2026: 42% have used AI assistants for online shopping.
Agentic behaviorSays they let an agent complete a purchase.Menlo Ventures and Morning Consult: 26% of US shoppers who use AI let it complete a purchase.
01 · AI-referred traffic
Data through September 2026

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.

+71%
Year-over-year growth in AI-referred traffic to US retail sites, September 2026
Measures
AI-referred
Geography
US
Period
September 2026
Sample
1 trillion+ visits
Method
Analytics panel
+127%
Year-over-year growth in AI-driven traffic to US retail sites, August 2026
Measures
AI-referred
Geography
US
Period
August 2026
Sample
1 trillion+ visits
Method
Analytics panel
+62%
Year-over-year growth in AI-driven traffic to US retail sites, July 2026. Travel +119%, financial services +31%
Measures
AI-referred
Geography
US
Period
July 2026
Sample
1 trillion+ visits
Method
Analytics panel
+138%
Year-over-year growth in AI-driven traffic to US retail sites, May 2026, its highest share of total retail visits since Adobe began tracking in October 2024
Measures
AI-referred
Geography
US
Period
May 2026
Sample
1 trillion+ visits
Method
Analytics panel
+393%
Year-over-year growth in AI traffic to US retail sites, January to March 2026
March 2026 alone: +269%.
Measures
AI-referred
Geography
US
Period
Q1 2026
Sample
1 trillion+ visits
Method
Analytics panel
+693.4%
Year-over-year growth in AI-referred traffic to US retail sites, 2025 holiday season
November 2025 +769%, December 2025 +673%.
Measures
AI-referred
Geography
US
Period
1 Nov to 31 Dec 2025
Sample
1 trillion+ visits
Method
Analytics panel
+1,200%
Year-over-year growth in generative AI traffic to US retail sites, October 2025
Measures
AI-referred
Geography
US
Period
October 2025 vs October 2024
Sample
1 trillion+ visits
Method
Analytics panel
+4,700%
Year-over-year growth in generative AI traffic to US retail sites, July 2025
Measures
AI-referred
Geography
US
Period
July 2025 vs July 2024
Sample
1 trillion+ visits
Method
Analytics panel
26%
of AI-referred traffic to US retail sites arrived on mobile in July 2025, up from 18% in January 2025
Measures
AI-referred
Geography
US
Period
July 2025
Sample
1 trillion+ visits
Method
Analytics panel
0%1,000%2,000%3,000%4,000%5,000%Hol 2024: +1,300% year over year1,300%Hol 2024Jul 25: +4,700% year over year4,700%Jul 25Oct 25: +1,200% year over year1,200%Oct 25Nov 25: +769% year over year769%Nov 25Dec 25: +673% year over year673%Dec 25Mar 26: +269% year over year269%Mar 26May 26: +138% year over year138%May 26Jul 26: +62% year over year62%Jul 26Aug 26: +127% year over year127%Aug 26Sep 26: +71% year over year71%Sep 26
Source: Adobe Analytics, 1 trillion+ visits to US retail sites. Every bar is a year-over-year comparison stated by Adobe. Adobe also publishes growth indexed to October 2024 and to July 2024; those series are not year over year and are omitted so every bar shares one baseline. Holiday 2024 (1 Nov to 31 Dec) and July 2025 from the August 2025 release; October 2025 from the November 2025 release; November and December 2025 from the January 2026 release; March 2026 from the April 2026 release; May 2026 from the June 2026 report; July 2026 from the August 2026 report; August 2026 from Adobe's holiday report page; September 2026 from the 29 October 2026 release.

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

0.2%
of total web traffic came from AI-referred sources in Q4 2025, after growth of 632% year over year. AI-referred conversion rose 55% to 1.3%
Measures
AI-referred
Geography
Global, cross-industry
Period
Q4 2025 vs Q4 2024
Sample
99 billion sessions; 6,500 sites
Method
Analytics benchmark
0.40%
of all sessions came from organic ChatGPT referrals in the four weeks to 17 August 2026, up from 0.23% across June 2025 to August 2026
Measures
AI-referred
Geography
9 countries plus EU-27
Period
27 Jul to 17 Aug 2026
Sample
1,898 sites
Method
First-party analytics
0.4%
of retail ecommerce visits come from generative AI referrals, which grew 203% year over year
Measures
AI-referred
Geography
Not stated
Period
Not stated; published Sep 2026
Sample
Not stated
Method
Modeled traffic estimates
197% vs 12%
growth in AI-referred sessions against organic search sessions on Shopify storefronts, Q2 2026. Organic search still referred more sessions than all tracked AI platforms combined
Measures
AI-referred
Geography
Not stated
Period
Q2 2026, year over year
Sample
Shopify storefronts
Method
Company disclosure
5.2%
of ChatGPT conversation sessions produced an outbound click, against 31.1% of Google queries
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.

02 · Conversion
Data through September 2026

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

+90%
AI-referred visits converted 90% better than non-AI traffic in September 2026, the highest level Adobe has observed. In August 2025 they converted 9% worse
Measures
AI-referred
Geography
US retail
Period
September 2026
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+83%
higher revenue per visit from AI traffic than non-AI traffic in September 2026, the largest gap Adobe observed in 2026
Measures
AI-referred
Geography
US retail
Period
September 2026
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+60%
higher conversion rate for AI retail visitors than non-AI traffic in July 2026, up from +54% in May 2026
Measures
AI-referred
Geography
US retail
Period
July 2026
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+42%
AI traffic converted 42% better than non-AI traffic in March 2026. In March 2025 it converted 38% worse
Measures
AI-referred
Geography
US retail
Period
March 2026
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+31%
AI referrals converted 31% more than other traffic sources in the 2025 holiday season
Measures
AI-referred
Geography
US retail
Period
1 Nov to 31 Dec 2025
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+32%
higher revenue per visit from AI-driven traffic than non-AI traffic in the 2025 holiday season. In the 2024 holiday season non-AI visits were worth 51% more
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

+86%
higher likelihood of conversion for affiliate traffic than for organic ChatGPT referrals, the widest gap in the study
Measures
AI-referred
Geography
Global
Period
2 Feb to 2 Aug 2025
Sample
973 sites
Method
First-party analytics, regression
+13%
higher likelihood of conversion for organic search than for organic ChatGPT referrals
Not statistically significant in five of the paper's robustness specifications.
Measures
AI-referred
Geography
Global
Period
2 Feb to 2 Aug 2025
Sample
973 sites
Method
First-party analytics, regression
−53%
lower likelihood of conversion for paid social than for organic ChatGPT referrals, the only channel below ChatGPT
Measures
AI-referred
Geography
Global
Period
2 Feb to 2 Aug 2025
Sample
973 sites
Method
First-party analytics, regression
<0.2%
of all traffic in the dataset came from organic LLM referrals "one year after launch", about 200 times smaller than Google organic search. ChatGPT accounted for over 90% of LLM sessions
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.

-60%-40%-20%0%+20%+40%+60%+80%+100%parity with non-AI trafficJan 25: -49% vs non-AI traffic-49%Jan 25Apr 25: -38% vs non-AI traffic-38%Apr 25Jul 25: -23% vs non-AI traffic-23%Jul 25Aug 25: -9% vs non-AI traffic-9%Aug 25Sep 25: +5% vs non-AI traffic+5%Sep 25Oct 25: +16% vs non-AI traffic+16%Oct 25Hol 25: +31% vs non-AI traffic+31%Hol 25Mar 26: +42% vs non-AI traffic+42%Mar 26May 26: +54% vs non-AI traffic+54%May 26Jul 26: +60% vs non-AI traffic+60%Jul 26Sep 26: +90% vs non-AI traffic+90%Sep 26
Source: Adobe Analytics, US retail, 1 trillion+ visits. Percentage difference in conversion rate for AI-referred visits against Adobe's blended non-AI baseline. January, April and July 2025 from the August 2025 release; August to October 2025 from the November 2025 release; holiday 2025 (1 Nov to 31 Dec) from the January 2026 release; March 2026 from the April 2026 release; May 2026 from the June 2026 report; July 2026 from the August 2026 report; September 2026 from the 29 October 2026 release. Adobe has not published text figures for January, February, April, June or August 2026, so those months are omitted, and points are not evenly spaced in time.

Conversion by channel relative to organic ChatGPT referrals, Kaiser and Schulze

  1. 01
    Affiliate
    Conversion coefficient 0.621 relative to organic ChatGPT, which the paper reports as an 86% higher likelihood of conversion. Revenue per session $3.57 higher.
  2. 02
    Paid search
    Conversion coefficient 0.370. Revenue per session $1.95 higher.
  3. 03
    Other
    Conversion coefficient 0.366. Revenue per session $2.19 higher.
  4. 04
    Direct
    Conversion coefficient 0.282. Revenue per session $3.07 higher.
  5. 05
    Email
    Conversion coefficient 0.276. Revenue per session $2.69 higher.
  6. 06
    Referral
    Conversion coefficient 0.218. Revenue per session $1.61 higher.
  7. 07
    Organic search
    Conversion coefficient 0.121, a 13% higher likelihood of conversion. Revenue per session $1.01 higher.
  8. 08
    Organic ChatGPT referral (baseline)
    The reference channel. Over the first twelve months its conversion rate and revenue per session rose while average order value fell.
  9. 09
    Paid social
    Conversion 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

1.99%
conversion rate for organic ChatGPT referrals over June 2025 to August 2026. Before ChatGPT's ad rollout in February 2026 it "approximately matched organic search's"
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
$0.89 vs $2.45
revenue per session from a paid ChatGPT ad visit against a paid Google Search visit, US. Conversion 0.37% against 1.17%
Paid ChatGPT traffic. Not comparable with the organic ChatGPT figures above.
Measures
AI-referred
Geography
US
Period
After Feb 2026 ad rollout
Sample
102 advertiser sites with full revenue tracking
Method
First-party analytics
+64%
better conversion from AI-referred sessions than organic search on Shopify storefronts, Q3 2026
Shopify words this metric differently each quarter, so quarters are not one series.
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

Engagement of AI-referred visitors compared with the comparator in each dataset
MetricAdobe, July 2025Adobe, holiday 2025Adobe, July 2026Kaiser and Schulze, Feb to Aug 2025
Time on site+32% longer+45% longer+59% longerIntermediate; above paid social and affiliate
Pages per visit+10% more+13% more+22% moreFewer page views
Bounce rate−27% lower−33% less likely to bounce−34% less likely to bounceMore 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

03 · Consumers
Data through September 2026

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).

0%25%50%75%100%Have used Gen AI shopping tools, Nov 2023Self-reported behaviorHave used Gen AI shopping tools, Nov 2023: 20% (Self-reported behavior)20%Have used Gen AI shopping tools, Nov 2024Self-reported behaviorHave used Gen AI shopping tools, Nov 2024: 24% (Self-reported behavior)24%Have used Gen AI shopping tools, Oct 2025Self-reported behaviorHave used Gen AI shopping tools, Oct 2025: 25% (Self-reported behavior)25%Plan to use them, Nov 2023IntentionPlan to use them, Nov 2023: 33% (Intention)33%Plan to use them, Nov 2024IntentionPlan to use them, Nov 2024: 35% (Intention)35%Plan to use them, Oct 2025IntentionPlan to use them, Oct 2025: 31% (Intention)31%
Source: Capgemini Research Institute, What Matters to Today's Consumer 2026, Figure 12. 12,000 consumers in 12 countries in each of the 2024 and 2025 waves, 11,681 in 2023. Have used and plan to use are separate answer options to one question and are not additive.

Adobe Consumer Survey, n = 5,000+ US respondents, fielded July 2026

42%
of US consumers have used AI assistants for online shopping, 4 points higher than in March 2026
Measures
Self-reported behavior
Geography
US
Period
July 2026
Sample
n = 5,000+
Method
Consumer survey
83%
of those who use AI for shopping agree AI assistants have improved their online shopping experience
Measures
Self-reported behavior
Geography
US
Period
July 2026
Sample
n = 5,000+
Method
Consumer survey
77% / 69%
of AI shoppers feel more confident in a purchase after using an AI assistant; 69% are less likely to return the item
Measures
Self-reported behavior
Geography
US
Period
July 2026
Sample
n = 5,000+
Method
Consumer survey
95%
of consumers who turn to AI say its responses are at least as trustworthy as a traditional search engine
Measures
Stated preference
Geography
US
Period
July 2026
Sample
n = 5,000+
Method
Consumer survey

Other surveys, late 2025 to September 2026

Consumer surveys on AI shopping, with measure, geography, sample, fielding period and source
FindingMeasureGeographySampleFieldedSource
26% of shoppers who use AI let it complete a purchase; 37% made a final purchase decision on its recommendationAgentic behaviorUSn = 5,067 adultsJuly 2026Menlo Ventures, survey by Morning Consult, 16 September 2026
38% say they have completed a purchase directly inside ChatGPTAgentic behaviorUSn = 1,072January 2026Omnisend, survey by Cint, 18 March 2026
16% would let generative AI complete a holiday purchase with their permissionStated preferenceUSn = 3,70026 Aug to 10 Sep 2026Deloitte, 15 October 2026
39% say generative AI is their primary tool for at least one holiday shopping taskIntentionUSn = 3,70026 Aug to 10 Sep 2026Deloitte, 15 October 2026
23% trust generative AI to handle payment transactions on their behalfStated preferenceUSn = 2,06526 to 28 May 2026Visa, survey by The Harris Poll, 9 September 2026
54% have used AI for at least one shopping task, up from 47% a year earlierSelf-reported behaviorUSn = 1,000+Late September 2026Visa, survey by Morning Consult, 30 October 2026
29% plan to use AI in their holiday shopping, up from 22% a year earlierIntentionUSn = 4,09315 to 26 Jun 2026PwC, 8 September 2026
25% have used Gen AI shopping tools; a further 31% plan toSelf-reported behavior12 countriesn = 12,000October 2025Capgemini 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)

38%
of US consumers report having used generative AI for online shopping
Measures
Self-reported behavior
Geography
US
Period
Survey, 2025
Sample
n = 5,000
Method
Consumer survey
52%
plan to use generative AI for online shopping this year
Measures
Intention
Geography
US
Period
Survey, 2025
Sample
n = 5,000
Method
Consumer survey
85%
of those who have used AI for shopping say it improved their shopping experience
Measures
Self-reported behavior
Geography
US
Period
Survey, 2025
Sample
n = 5,000
Method
Consumer survey
73%
of those who have used AI for shopping cite it as their primary source of product research
Measures
Self-reported behavior
Geography
US
Period
Survey, 2025
Sample
n = 5,000
Method
Consumer survey
83%
say they are more likely to use AI for larger or more complex purchases
Measures
Stated preference
Geography
US
Period
Survey, 2025
Sample
n = 5,000
Method
Consumer survey
81%
of consumers using AI assistants for online shopping report an improved shopping experience
Measures
Self-reported behavior
Geography
US
Period
Holiday 2025 survey
Sample
n = 1,000+
Method
Consumer survey
47%
report trust in AI-generated results
Measures
Stated preference
Geography
US
Period
Holiday 2025 survey
Sample
n = 1,000+
Method
Consumer survey
64% / 55%
of shoppers using AI are satisfied with the links they receive; 55% say they actively click on them
Measures
Self-reported behavior
Geography
US
Period
Holiday 2025 survey
Sample
n = 1,000+
Method
Consumer survey
65% / 68%
more confident in their purchase after AI help; 68% less likely to return the product
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.

04 · AI-influenced sales, retailer-side AI and agents
Data through December 2025

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.

Read this group on its own terms. Salesforce's Cyber Week wording is "AI and agents drove $67 billion in sales, influencing 20% of all purchases through personalized product recommendations and conversational customer service." Its holiday wording is "through personalized recommendations and deeper customer engagement." A purchase counts if a recommendation engine or a service agent touched the journey. Salesforce extrapolates its dollar totals to the whole retail industry using first-party data, third-party data and market assumptions. Only the nine-times figure below measures shoppers arriving from AI search.
$262B / 20%
AI and agents drove 20% of all 2025 holiday retail sales and $262 billion in revenue "through personalized recommendations and deeper customer engagement"
Measures
AI-influenced
Geography
Global
Period
1 Nov to 31 Dec 2025
Sample
1.5 billion+ shoppers
Method
Shopping Index, retailer-side AI
9×
Shoppers referred to retailer websites from AI-powered search channels converted nine times more often than those from social media referrals
Salesforce's own June 2026 citation of the same dataset says eight times. Social referrals are a low-converting comparator.
Measures
AI-referred
Geography
Global
Period
1 Nov to 31 Dec 2025
Sample
1.5 billion+ shoppers
Method
Shopping Index
$67B / 20%
AI and agents drove $67 billion in global Cyber Week sales, "influencing 20% of all purchases through personalized product recommendations and conversational customer service"
Measures
AI-influenced
Geography
Global
Period
25 Nov to 1 Dec 2025
Sample
1.5 billion+ shoppers
Method
Shopping Index, retailer-side AI
$336.6B
global online sales during Cyber Week 2025, up 7% year over year. US: $79.6 billion, up 5%
Measures
Company disclosure
Geography
Global and US
Period
25 Nov to 1 Dec 2025
Sample
1.5 billion+ shoppers
Method
Shopping Index
32%
faster sales growth for retailers using Agentforce 360 than peers without dedicated AI agents. Salesforce names Pandora, Shark Ninja and Funko
Compares Salesforce's own customer base with non-users. Not a random sample of retailers.
Measures
AI-influenced
Geography
Global
Period
25 Nov to 1 Dec 2025
Sample
Salesforce customers vs non-users
Method
Vendor customer comparison
+55%
week-over-week growth in agentic customer service conversations
Measures
Agent-executed
Geography
Global
Period
25 Nov to 1 Dec 2025
Sample
Agentforce customers
Method
Shopping Index
+70%
growth in agent-driven actions such as address updates and return initiations
Measures
Agent-executed
Geography
Global
Period
25 Nov to 1 Dec 2025
Sample
Agentforce customers
Method
Shopping Index
Nearly 61M
orders powered on Agentforce Commerce during Cyber Week 2025
Measures
Company disclosure
Geography
Global
Period
25 Nov to 1 Dec 2025
Sample
Agentforce Commerce customers
Method
Shopping Index
$0B$20B$40B$60B$80BCyber Week 2023: $51 billion AI-influenced global sales$51B2023Cyber Week 2024: $60 billion AI-influenced global sales$60B2024Cyber Week 2025: $67 billion AI-influenced global sales$67B2025
Source: Salesforce Shopping Index, global Cyber Week, billions of US dollars. AI-influenced spend as Salesforce defines it each year: 2023 counts online sales influenced by targeted offers, product recommendations and generative AI chat (21 to 27 November); 2024 counts online sales influenced by AI and agents including targeted offers (26 November to 2 December); 2025 counts sales influenced by personalized product recommendations and conversational customer service (25 November to 1 December). Not LLM referral traffic. Because the definition and Salesforce's own agent products changed between years, part of the change reflects coverage rather than behavior.

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

05 · Company disclosures
Data through October 2026

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.

400M+
customers used Alexa for Shopping, Amazon's agentic shopping assistant, in the last 12 months, with customer interactions up 570% year over year
Measures
Company disclosure
Geography
Not stated
Period
12 months to Q3 2026
Sample
Amazon customers
Method
Earnings release
~$12B
"incremental annualized sales" Amazon attributes to Rufus in 2025, when it was used by 300 million+ customers
Amazon does not disclose how incremental sales are measured.
Measures
Company disclosure
Geography
Not stated
Period
2025
Sample
Amazon customers
Method
Earnings release, company model
~50%
of Walmart app users have used Sparky, Walmart's AI shopping assistant. Sparky users' average order value is about 35% higher than non-users'
Measures
Company disclosure
Geography
US
Period
Q4 FY26 (to Jan 2026)
Sample
Walmart app users
Method
Earnings call remarks
+70%
year-over-year growth in customers using Sparky. Sparky users spend 40% more per order than those who don't
Users self-select, so the order value gap is not an effect of the assistant.
Measures
Company disclosure
Geography
Not stated
Period
Q2 FY27 (to Jul 2026)
Sample
Walmart customers and members
Method
Earnings call remarks
3.3×
increase in orders originating from AI searches on Shopify, year over year. AI traffic to merchant storefronts up 2.6×
Measures
AI-referred
Geography
Not stated
Period
Q3 2026
Sample
Shopify storefronts
Method
Investor deck
2×
new buyer order rate for AI-referred orders against other online channels on Shopify
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

06 · Peak events
Data through June 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

+38%
AI conversions vs non-AI traffic sources on Black Friday 2025
Measures
AI-referred
Geography
US retail
Period
Black Friday, 28 Nov 2025
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+54%
AI conversions vs non-AI traffic sources on Thanksgiving 2025
Measures
AI-referred
Geography
US retail
Period
Thanksgiving, 27 Nov 2025
Sample
1 trillion+ visits
Method
Analytics panel, blended non-AI comparator
+670%
AI traffic to US retail sites on Cyber Monday 2025, measured by shoppers clicking a link
Measures
AI-referred
Geography
US retail
Period
Cyber Monday, 1 Dec 2025
Sample
1 trillion+ visits
Method
Analytics panel
+760%
AI traffic to US retail sites, season to date at Cyber Monday
Measures
AI-referred
Geography
US retail
Period
1 Nov to 1 Dec 2025
Sample
1 trillion+ visits
Method
Analytics panel
$257.8B
total US online holiday spend, 2025
Measures
Company disclosure
Geography
US
Period
1 Nov to 31 Dec 2025
Sample
1 trillion+ visits
Method
Analytics panel
5 categories
where AI chat services were used most on Cyber Monday 2025: video games, appliances, electronics, toys, personal care
Measures
AI-referred
Geography
US retail
Period
Cyber Monday, 1 Dec 2025
Sample
1 trillion+ visits
Method
Analytics panel

Prime Day 2025 and 2026

+89%
year-over-year growth in AI traffic to US retail sites across the Prime Day 2026 event. January to May 2026: +235%
Measures
AI-referred
Geography
US retail
Period
Prime Day, 23 to 26 Jun 2026
Sample
1 trillion+ visits
Method
Analytics panel
+40%
better conversion for AI traffic than non-AI channels during Prime Day 2026. During Prime Day 2025 AI traffic converted 23% worse
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
+3,300%
year-over-year growth in generative AI traffic to US retail sites during Prime Day 2025
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.

07 · Protocols
Data through November 2026

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.

Where each protocol operates: ACP, UCP, AP2, A2A and MCP against discovery, cart, checkout, payment and post-purchase
Standard and layerSponsor or governanceDiscovery and catalogCartCheckoutPayment credentialsPost-purchaseStatus, November 2026
ACP
Commerce
OpenAI and Stripe. Specification in betaYes. Product feeds and promotionsYes, in the 2026-04-17 specificationIn the specification; not used in ChatGPT since March 2026Delegated payment specificationOrders capability in the specificationChatGPT 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 StripeYesYes, optional capabilityYesVia AP2 and regulated payment providersYesUniversal 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 2026NoNoNoYes. Signed Checkout Mandate and Payment Mandate (version 0.2)NoSpecification 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 2026n/an/an/an/an/aVersion 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 FoundationTool and data access onlyNot in scopeNot in scopeNot in scopeTool access onlySpecification 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

US
Universal Cart, with checkout powered by UCP, rolled out across Google Search and the Gemini app on 15 October 2026. Named merchants: Nike, Sephora, Target, Ulta Beauty, Walmart, Wayfair and many Shopify merchants
Measures
Protocol status
Geography
US
Period
15 October 2026
Sample
Not applicable
Method
Company announcement
Canada
Direct checkout powered by UCP began rolling out to Canadian shoppers in AI Mode and the Gemini app on 4 November 2026, with lululemon, Shoppers Drug Mart, Simons and select Shopify merchants
Measures
Protocol status
Geography
Canada
Period
4 November 2026
Sample
Not applicable
Method
Company announcement
Select merchants
Google Merchant Center: "The checkout feature enabled by UCP is available for select merchants at this time." Eligibility limited to products in the United States, Canada and Australia
Measures
Protocol status
Geography
US, Canada, Australia
Period
Retrieved 9 November 2026
Sample
Not applicable
Method
Product documentation
3× lower
conversion rate for selection sold directly inside ChatGPT than for products requiring a click out to the merchant, per Walmart EVP Daniel Danker
Grade C. Etsy told the same outlet it did not see large volume from Instant Checkout but does see valuable referral traffic.
Measures
Company disclosure
Geography
US
Period
Reported March 2026
Sample
Walmart, one retailer
Method
Executive disclosure via trade press
7
retailers OpenAI names as integrated into ACP for discovery: Target, Sephora, Nordstrom, Lowe's, Best Buy, The Home Depot, Wayfair
Measures
Protocol status
Geography
US
Period
24 March 2026
Sample
Named by OpenAI
Method
Company announcement
16 seats
on the UCP Tech Council after Amazon, Meta, Microsoft, Salesforce and Stripe joined in April 2026
Measures
Protocol status
Geography
Global
Period
24 April 2026
Sample
Not applicable
Method
Project announcement
~500M
monthly downloads across MCP's Tier 1 SDKs ("close to half-a-billion"), with the TypeScript and Python SDKs each past 1 billion total downloads
December 2025: 97 million+ monthly SDK downloads and 10,000 active servers. Scopes may differ, so no growth rate is calculated. Integration activity, not commerce transactions.
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

48 : 1
carts abandoned by retail AI agents for every completed purchase, against about three for all retail traffic. AI agent sessions grew 25× in under a year
Measures
Agent-executed
Geography
Not stated
Period
Not stated; published Nov 2026
Sample
Quantum Metric platform data
Method
Vendor behavioral data
42.8%
of simulated shopping runs failed across 22 AI models. 54% of failed runs still ended in the AI making a purchase
Best model passed 82.2% of attempts, worst 28.9%. All three attempts at a scenario passed 34.2% of the time.
Measures
Agent benchmark
Geography
Not applicable
Period
Published 5 Nov 2026
Sample
22 models; 15 scenarios; 3 attempts each
Method
Laboratory benchmark
30+
European card issuers working with Visa to let AI agents make purchases on behalf of cardholders, at merchants including lastminute.com and Frasers
No transaction count or value published.
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.

08 · Limitations
Data through November 2026

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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

09 · Implications
Data through November 2026

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.

10 · At a glance
Data through November 2026

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.

AI ecommerce statistics at a glance, with measurement, geography, period, sample, source and evidence grade
StatisticGradeWhat it measuresGeographyPeriodSample or datasetSource
+90% conversion for AI referrals vs non-AI trafficAAI-referred, against Adobe's blended non-AI baselineUSSeptember 20261 trillion+ visits, analytics panelAdobe Analytics, 29 October 2026
+83% revenue per visit for AI referrals vs non-AI trafficAAI-referred, against Adobe's blended non-AI baselineUSSeptember 20261 trillion+ visits, analytics panelAdobe Analytics, 29 October 2026
+71% AI-referred retail traffic, year over yearAAI-referred: humans clicking from an AI surface to a US retail siteUSSeptember 20261 trillion+ visits, analytics panelAdobe Analytics, 29 October 2026
+693% AI-referred retail traffic, year over yearAAI-referredUS1 Nov to 31 Dec 20251 trillion+ visits, analytics panelAdobe Analytics, 12 January 2026
AI referrals 23% less likely to convert than non-AIAAI-referred, against Adobe's blended non-AI baselineUSJuly 20251 trillion+ visits, analytics panelAdobe Analytics, 21 August 2025
0.2% of web traffic from AI-referred sources; +632% year over yearAAI-referred, cross-industryGlobalQ4 202599 billion sessions; 6,500 sitesContentsquare, 2026 Digital Experience Benchmarks, 29 January 2026
Affiliate traffic 86% and organic search 13% more likely to convert than ChatGPT referrals; paid social 53% lessAAI-referred, organic ChatGPT only, against each named channelGlobal2 Feb to 2 Aug 2025973 sites; 10.5 billion sessionsKaiser 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 2026AAI-referred, organic ChatGPT only9 countries plus EU-2730 Jun 2025 to Feb 20261,898 sites; working paperKaiser and Schulze, working paper, October 2026 (version 1)
ChatGPT sends an outbound click in 5.2% of sessions; Google in 31.1% of queriesAAI-referred click-out rateUS, desktopOct 2024 to Jul 202545,386 households; preprintShi et al., Bocconi University, arXiv 2607.07652, 8 July 2026
$262B, 20% of holiday sales, driven by AI and agentsAAI-influenced: personalized recommendations and customer engagementGlobal1 Nov to 31 Dec 20251.5 billion+ shoppers, Shopping IndexSalesforce, 8 January 2026
AI-influenced Cyber Week sales: $51B (2023), $60B (2024), $67B (2025)AAI-influenced, Salesforce definition, which changed between yearsGlobalCyber Week 2023 to 20251.5 billion+ shoppers, Shopping IndexSalesforce, 5 December 2025
42% have used AI assistants for online shoppingBSelf-reported behaviorUSJuly 2026n = 5,000+, surveyAdobe Digital Insights, 19 August 2026
25% have used Gen AI shopping tools; a further 31% plan toBSelf-reported behavior; intention12 countriesOctober 2025n = 12,000, surveyCapgemini Research Institute, 6 January 2026
26% of US shoppers who use AI let it complete a purchaseBAgentic behaviorUSJuly 2026n = 5,067, surveyMenlo Ventures, survey by Morning Consult, 16 September 2026
16% would let generative AI complete a purchase with permissionBStated preferenceUSAug to Sep 2026n = 3,700, surveyDeloitte, 15 October 2026
3.3× orders from AI searches; +64% conversion vs organic searchCAI-referred, company disclosureNot statedQ3 2026Shopify storefrontsShopify Investor Relations, 3 November 2026
400M+ customers used Alexa for Shopping; interactions +570%CRetailer-owned assistant usageNot stated12 months to Q3 2026Amazon customersAmazon Investor Relations, 29 October 2026
Retail AI agents abandon 48 carts per completed purchaseCAgent-executedNot statedPublished Nov 2026Vendor platform dataQuantum Metric, 2026 Peak Benchmark, 5 November 2026
42.8% of simulated agent shopping runs failedCAgent benchmarkNot applicablePublished 5 Nov 202622 models, 15 scenariosVisa, 5 November 2026
In-chat checkout converted 3× lower than click-out to the merchantCCompany disclosure, WalmartUSReported March 2026One retailerModern Retail, 27 March 2026
UCP checkout live for shoppers in the US and CanadaCProtocol statusUS, CA15 Oct and 4 Nov 2026Not applicableGoogle, 15 October 2026

Forecasts, grade D, not measured results

+130%
forecast year-over-year growth in AI traffic to US retail sites, 2026 holiday season: Thanksgiving +159%, Black Friday +95%, Cyber Monday +88%
Measures
Forecast
Geography
US
Period
1 Nov to 31 Dec 2026
Sample
Not applicable
Method
Forecast
$3T to $5T
global revenue that AI agents could "orchestrate" by 2030, goods only. US B2C: $900 billion to $1 trillion
Measures
Forecast
Geography
Global
Period
By 2030
Sample
Not applicable
Method
Forecast
11 · Methodology
Data through November 2026

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
  • Adobe: Cyber Monday hits recordAdobe, 2 December 2025Grade A
    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.
  • Method: 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.
  • 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 (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.
  • 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: 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.
  • AI-driven traffic surges across industriesAdobe Analytics, 12 January 2026Grade A
    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.
  • AI traffic drives 83% higher revenue per visitAdobe Analytics, 29 October 2026Grade A
    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.
  • Adobe AI Traffic Trends Report: Industry InsightsAdobe Digital Insights, January 2026Grade A
    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.
  • AI Traffic Trends Report, June 2026 (May 2026 data)Adobe Digital Insights, June 2026Grade A
    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.
  • AI Traffic Trends Report, August 2026 (July 2026 data)Adobe Digital Insights, 19 August 2026Grade A
    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 A
    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: 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%).
  • A2A joins AAIF's open agentic stackAgentic AI Foundation, 17 August 2026Grade C
    Method: Foundation announcement. Geography: Global specification. Sample: Not applicable.
    Limitations: Governance announcement. The 150+ organization figure is self-reported.
  • Amazon Q4 2025 earnings reportAmazon, 5 February 2026Grade C
    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.
  • Amazon.com announces third quarter resultsAmazon Investor Relations, 29 October 2026Grade C
    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.
  • Method: 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 C
    Method: Protocol specification. Geography: Not applicable. Sample: Not applicable.
    Limitations: A specification. Says nothing about adoption.
  • Method: 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 A
    Method: 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.
  • 2026 holiday retail surveyDeloitte, 15 October 2026Grade B
    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 C
    Method: 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 C
    Method: Product documentation. Geography: Not applicable. Sample: Not applicable.
    Limitations: Describes Google Analytics 4 only.
  • Method: Company announcement. Geography: Canada. Sample: Not applicable.
    Limitations: Names merchants but gives no merchant count or volume.
  • Method: Company announcement. Geography: Global specification. Sample: Not applicable.
    Limitations: A launch announcement with partner names and no adoption figures.
  • Under the hood: Universal Commerce Protocol (UCP)Google Developers Blog, 11 January 2026Grade C
    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 C
    Method: 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 C
    Method: 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 C
    Method: 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 A
    Method: 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 A
    Method: 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.
  • Method: Foundation press release. Geography: Global specification. Sample: Not applicable.
    Limitations: Organization counts are self-reported by the foundation.
  • Method: Foundation press release. Geography: Global. Sample: Not applicable.
    Limitations: Governance announcement only.
  • Method: 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.
  • The state of consumer AI: 2026Menlo Ventures, survey by Morning Consult, 16 September 2026Grade B
    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.
  • MCP joins the Agentic AI FoundationModel Context Protocol project, 9 December 2025Grade C
    Method: Project announcement. Geography: Global specification. Sample: Not applicable.
    Limitations: Project's own statement of its governance and usage. Download counts include dependency pulls.
  • The 2026-07-28 specificationModel Context Protocol project, 28 July 2026Grade C
    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.
  • What went wrong with ChatGPT's Instant CheckoutModern Retail, 27 March 2026Grade C
    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 B
    Method: 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.
  • Powering product discovery in ChatGPTOpenAI, 24 March 2026Grade C
    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.
  • Power product discovery in ChatGPTOpenAI, Retrieved 9 November 2026Grade C
    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.
  • OpenAI crawlers and botsOpenAI, Retrieved 8 September 2026Grade C
    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 C
    Method: Protocol specification. Geography: Not applicable. Sample: Not applicable.
    Limitations: The specification is in beta and versioned by dated folders, not tagged releases.
  • Holiday outlook 2026PwC, 8 September 2026Grade B
    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.
  • Method: 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.
  • Method: 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.
  • Salesforce reveals 2025 holiday shopping dataSalesforce, 8 January 2026Grade A
    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.
  • Method: 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.
  • Salesforce 2025 Cyber Week predictionsSalesforce, 20 November 2025Grade D
    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%).
  • Salesforce Cyber Week 2023 resultsSalesforce, via Business Wire, 28 November 2023Grade A
    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 A
    Method: 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.
  • Method: 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.
  • Shopify Q3 2026 investor deckShopify Investor Relations, 3 November 2026Grade C
    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.
  • 2026 State of Ecommerce ReportSimilarweb, 10 September 2026Grade C
    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.
  • Method: Company announcement. Geography: United States at launch. Sample: Not applicable.
    Limitations: A launch announcement. It contains no merchant fee figure and no volume figures.
  • Announcing new Tech Council membersUniversal Commerce Protocol project, 24 April 2026Grade C
    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 C
    Method: Protocol specification, draft. Geography: Not applicable. Sample: Not applicable.
    Limitations: A draft specification that can change between retrievals.
  • Method: 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.
  • Method: Company announcement. Geography: Europe. Sample: Not applicable.
    Limitations: Gives issuer and merchant names but no transaction count or value.
  • Method: 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 B
    Method: 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.
  • Walmart earnings call transcript, Q4 FY26Walmart, 19 February 2026Grade C
    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.
  • Walmart earnings call transcript, Q2 FY27Walmart, 20 August 2026Grade C
    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.