What Adobe’s Latest AI Traffic Report Tells Marketers About the Customer Journey

There are plenty of big growth numbers in the report. AI-driven traffic to retail websites increased 62% year on year in July 2026, while 42% of consumers surveyed said they had now used an AI assistant for online shopping. Travel saw an even bigger 119% year-on-year increase in AI-driven visits, while financial services grew by 31%.

But the growth in AI traffic isn’t actually the most interesting part; it’s what people do when they arrive.

Adobe found that AI-referred retail visitors converted at a rate 60% higher than non-AI traffic in July. They were also 34% less likely to bounce, continuing a pattern Adobe has now observed for more than a year. 

Basically, those visitors are sticking around for longer and engaging more deeply. For marketers trying to understand where AI fits in the customer journey, that distinction matters.

In retail, AI-referred visitors were 34% less likely to bounce than visitors from other channels in July 2026. More importantly, this isn’t being driven by one particularly strong month. Adobe found that AI bounce rates have remained within a relatively consistent 17–20% range for more than a year, compared with non-AI bounce rates sitting around 27%.

Travel shows an even greater difference. Visitors arriving from AI were 42% less likely to bounce than those arriving through traditional sources, with Adobe attributing the consistent gap to travellers arriving with stronger pre-visit intent after their AI research.

That changes how we should think about the value of an AI referral.

The click at the end of that conversation is, therefore, potentially a very different click from the one we have spent years measuring.

The strongest evidence of that comes from Adobe’s conversion data.

In July 2026, AI-referred retail visitors converted 60% better than non-AI traffic. Just a year earlier, the opposite was true: non-AI visitors comfortably outperformed those arriving via AI.

That’s quite a significant reversal in a relatively short period, and is also why looking at AI referral volume alone doesn’t tell us too much. If those visitors are arriving with stronger intent, a smaller number of AI-referred sessions could still have a larger commercial impact. 

The same shift is beginning to appear within travel. Adobe found that the conversion rate from AI-referred traffic was only 1% lower than non-AI traffic in July, the smallest difference recorded since its analysis began in October 2024. AI-referred conversion had increased 16% year on year, while conversion from non-AI traffic had fallen 38%.

It suggests that as people become more comfortable using AI for research, the recommendations they receive are moving closer to the point of decision.

Adobe’s consumer research supports that, too. 77% of consumers using AI for online shopping said they felt more confident about a purchase after using an AI assistant, while 69% said they were less likely to return something they had bought with AI’s help.

Adobe rightfully doesn’t treat AI behaviour as something that’s identical across every industry. Retail, travel and financial services are all seeing growth, but how people use AI varies considerably across industries. 

Adobe’s Citation Readability analysis found apparel had the highest overall score of retail categories, pointing to consistent content structures across homepages, blogs and product pages. Electronics followed at 70%, supported by details specifications and structured technical content. 

It’s a useful indication that visibility isn’t only reliant on your product page. The surrounding editorial, category, and informational content helps create the context both people and AI systems need to understand what a brand sells and how this fits into a user query.

We’ve seen the value of this approach in practice, too. Our work with Joe Browns focused on building visibility beyond branded searches, strengthening category and collection pages, developing topical content and improving the technical foundations supporting them. The result was a 45% year-on-year increase in non-brand clicks in February 2026, alongside continued organic growth throughout the first half of the year. 

We’ve got a bunch of blogs around the travel industry to help you improve your brand visibility

• Why Trust is the Travel Industry’s Most Valuable Currency and How PR Builds It
• The Cruise Market Is Changing. What Does That Mean For Cruise Agents?
• How Multi-Platform Search is Taking Travel and Tourism on a Journey
• The Experience-First Travel Economy: Tourism Trends Defining 2026
• EEAT in the Travel Industry: Creating the Content Holidaymakers Want and Need

Yes, the AI-driven visits to financial services websites grew, but the behaviour after the visit is more interesting. AI-referred visitors spent 44% more time per visit and engaged at a rate 13% higher than visitors from traditional sources. 

People using AI for financial services are asking for banking recommendations, trying to understand complex financial topics, budgeting, investment recommendations and tax information. 

When subjects like these can directly affect someone’s financial situation, the information behind AI models needs to be clear, trustworthy, evidence-led, and consistent with what they find when searching across channels. 

Demi has done a whole blog about rebuilding trust in the finance industry, with yearly stats and key considerations from users looking to choose financial platforms. 

There has been plenty of discussion about what happens to websites as more of the discovery journey moves into AI interfaces. Adobe’s research offers a useful reminder that people still want to validate what they’re told.

66% of consumers said they visit a brand’s website directly to verify an AI recommendation, while 89% said they click the links or sources provided by an AI assistant.

That makes the relationship between AI visibility and your website particularly important.

If an AI assistant recommends a product based on its warranty, price, specifications, or suitability for a particular need, the website has to support that recommendation when the person arrives. Product information needs to be clear, important claims need evidence, and the content somebody lands on needs to continue the journey rather than forcing them to start their research all over again.

The role of the website hasn’t disappeared. If anything, it becomes the place where the recommendation is validated.

And that means brands can’t think about improving AI visibility separately from improving the content and experience people eventually reach.

One of the more interesting additions to Adobe’s report is its analysis of Citation Readability: essentially, how effectively the content on a webpage can be understood, parsed and surfaced by AI systems.

Adobe argues that AI models favour content that is structured, complete and rich in context, while sparse information, missing detail and poor organisation can limit a page’s likelihood of being surfaced and cited.

There is a temptation to look at findings like this and immediately create another AI optimisation checklist, but much of what Adobe describes should already be familiar to anyone working in search.

• Clear information architecture. 
• Useful content. 
• Important information appears where people can actually find it. 
• Strong contextual relevance. 
• Pages that properly answer the question rather than mentioning a topic several times and hoping Google, ChatGPT and the person reading it will work out the rest.

The technology surfacing that information might be changing, but the need to create genuinely useful, understandable content hasn’t.

Adobe’s research builds on something we’re seeing repeatedly as AI becomes a bigger part of search and discovery: the website visit is increasingly the result of a much longer journey happening elsewhere.

In Similarweb’s recent “Downstream Impact of AI Visibility“ research, the company examined what happens when AI influences someone but doesn’t ultimately drive a website referral. Users exposed to a brand recommendation in ChatGPT were more likely to visit that brand later, often through branded search rather than by clicking directly from the AI response.

Adobe gives us another piece of that journey.

When people do arrive directly from AI, they’re bouncing less, showing stronger engagement across the sectors Adobe analysed and, in retail, converting at a higher rate and reporting greater confidence in the purchases they are making.

Similarweb helps us understand what can happen when AI influences a journey but doesn’t send the click, and Adobe helps us understand what happens when AI does send the click.

Put the two together, and measuring AI purely through referral traffic starts to look increasingly limited.

Some of its value happens before the click, when AI introduces and recommends brands. Some happens after the recommendation, when people continue their research through Google, social platforms, reviews and direct visits. And when AI finally generates the click itself, that visitor may already be considerably further along in their decision-making than traditional attribution suggests.

For marketers, that makes AI visibility less about creating another channel report and more about understanding its role across the wider search journey. 

Adobe’s report gives us plenty of numbers, but there are four big things you can do off the back of these to enhance your marketing strategy. 

Build your synthetic personas through the likes of LLMLens to understand the problems, comparisons, use cases, and research questions somebody might ask while they’re figuring out what they want. Don’t focus on the final click, but on the journey it takes to get there, and how present you are while customers are coming to a decision. 

Strong product information matters, but don’t put all of your energy into that and forget the useful content users need. Think guides, comparisons, FAQs, use-case pages, case studies, and supporting content. Adobe’s findings repeatedly point towards structured, contextual and educational content being easier for AI systems to understand. 

Adobe’s data suggests AI-referred visitors can arrive more engaged and, particularly in retail, more likely to convert. That’s valuable traffic to lose because of a slow website, confusing navigation, poor mobile experience, or unnecessary friction at the point of enquiry or purchase. AI might be changing how somebody gets to your website, but all the usual fundamentals of UX and conversion still matter once they get there. 

Instead of trying to perfectly attribute AI into a measurable channel, look at what you can learn from the traffic you can see: which pages AI visitors land on, how they behave when they arrive, whether they engage or convert, and how that changes over time. Combine that with monitoring your AI visibility and what responses are gaining traction to build a broader picture of where your visibility is improving. 

AI might be changing where discovery happens and how much research takes place before someone reaches your website, but the fundamentals haven’t disappeared. Brands still need to understand what their audiences are looking for, create genuinely useful content, and provide an experience that makes it easy for people to take the next step.

The difference is that more of the journey could now be happening before you ever see the visitor. Understanding that part of the journey, and making sure your brand is visible within it, is where the opportunity lies.

We’re helping brands understand where they’re being surfaced across AI search, what’s influencing those recommendations and where the opportunities are to improve.