Amazon AI referral traffic points to higher-intent shoppers, with AI referrals generating 53% more revenue per visit, 28% more cart additions, and 33% fewer bounces.
The path from product research to purchase is getting harder for sellers to track as shoppers increasingly use AI assistants before making buying decisions. Amazon AI referral traffic adds another layer to that path, with recent data showing that shoppers coming from AI sources can be more engaged and more likely to convert.
The trend is still early, since most consumers have not made AI shopping a regular habit. But for sellers competing for attention across crowded search results, understanding how AI systems read product information and influence purchase decisions could become an important part of measuring traffic quality.
Amazon AI Referrals Continue to Outpace Traditional Retail Traffic
AI traffic to U.S. retail sites rose 62% year over year in July, according to Adobe data shared by EMARKETER, while traffic from AI sources converted 60% better than non-AI traffic. The July results marked the 11th consecutive month in which AI conversion outpaced non-AI sources, showing continued strength in traffic quality even as AI shopping remains a relatively small consumer use case.
Adobe also found that AI-referred shoppers spent 59% more time on retailers’ sites and were 33% less likely to bounce than non-AI visitors. They also added items to their carts at higher rates, giving retailers more evidence that AI referrals can bring shoppers who are further along in the purchase process.
The trend extends to retailers using their own AI tools, with Albertsons reporting a roughly 10% lift in average order value from its basic conversational search and up to a 26% increase from its more advanced assistant capabilities. Walmart’s Sparky users had a 35% higher average order value than shoppers who did not use the assistant, while 44% of Amazon app sessions that used Alexa for Shopping in July resulted in a sale.
For sellers and an Amazon agency, the data highlights why Amazon AI referral traffic is worth watching as retailers assess the commercial impact of AI shopping. Adoption remains limited, with less than 17% of U.S. internet users using generative AI weekly for shopping and 56% of U.S. digital shoppers either uninterested in AI shopping or unaware of it, according to the cited EMARKETER research.
Adobe Finds Gaps in Retailers’ AI Content Visibility
Adobe’s latest analysis also focused on whether retailers’ content can be read and understood by large language models. Its AI Content Visibility Checker analyzes web pages to identify content that LLMs can and cannot read, including information such as pricing, availability, and product details.
The findings give Amazon AI referral traffic a broader context because AI systems need clear and accessible information to surface products during AI product discovery. Adobe reported that its analysis covered more than 1 trillion visits to U.S. retail sites, with more than 200 of the Top 2,000 online retailers using Adobe for web analytics in 2025 and representing more than $836 billion in ecommerce sales.
Adobe’s expanded July analysis found that retailers had an average LLM visibility score of 61%, meaning 39% of the analyzed homepage content was not machine-readable. The category results also showed meaningful differences in how well retailers were positioned for AI shopping recommendations.
| Retail Category | LLM Visibility | Not Machine-Readable |
|---|---|---|
|
Apparel |
76%
|
24%
|
|
Electronics |
70%
|
30%
|
|
Cosmetics |
68%
|
32%
|
|
Sporting Goods
|
67%
|
33% |
|
Furniture & Home
|
64%
|
36%
|
|
General Merchandise
|
63%
|
37%
|
|
Grocery |
59%
|
41%
|
For apparel, electronics, and cosmetics, Adobe identified consistent and structured product content as a factor supporting AI visibility, while other categories showed a greater need for content updates. Digital Commerce 360 also introduced AI Rankings tied to its Top 1000 Database to measure retailer readiness for AI-driven shopping and agentic product discovery.
AI Referral Traffic Is Becoming More Valuable Across Retail
According to Markegy, Adobe’s March 2026 data shows a major shift in the value of AI-referred visits within one year, with retail conversion moving from roughly 50% below non-AI traffic in March 2025 to 42% above it in March 2026. Revenue per visit also shifted from 128% below non-AI traffic to 37% above it during the same period.
For sellers watching Amazon AI referral traffic, the broader retail pattern suggests that AI assistants may influence shoppers before they reach a retailer’s site. Adobe’s consumer survey found that 39% of U.S. consumers had used AI assistants for online shopping, while 79% said AI made them more confident in purchases and 69% said they were less likely to return purchases made with AI’s help.
The Q1 2026 data also showed that AI-referred visitors spent 48% more time on retail sites, viewed 13% more pages per visit, and had a 12% higher engagement rate than non-AI visitors. AI-referred traffic grew across all five industries Adobe tracked, with retail posting the highest increase at 393%, followed by travel at 233%, financial services at 158%, media and entertainment at 84%, and tech and software at 63%.
The findings provide useful context for AI product discovery and AI shopping recommendations, where shoppers can use AI assistants to research and narrow their choices before clicking through. Adobe’s data also reinforces the need to judge traffic by its ability to generate sales and revenue rather than relying on visitor volume alone.
