The Modern Buyer Journey - What marketers need to know in 2026

For most of the internet's commercial history, search worked the same way: you typed a query, got a list of links, and started clicking. Marketers could see exactly where buyers were going and what was influencing them. That visibility is disappearing.

Today, a growing share of buyers never make it to your website. They ask ChatGPT, Perplexity, or Google's AI Mode a direct question and get a synthesised answer back — complete with vendor comparisons, category summaries, and implicit recommendations. By the time some of them eventually reach your site, they've already decided what they think about you.

This piece examines how that shift is reshaping the buyer journey, what it means for brand discovery, and why the metrics most marketing teams still rely on are telling an incomplete story.

The numbers behind AI search adoption

AI-assisted search is still a small fraction of total internet traffic — but it's growing fast enough that any marketer ignoring it is taking a calculated risk.

According to SE Ranking's 2025 study, AI platforms currently account for around 0.15% of all global internet traffic, compared to 48.5% from organic search. That gap is enormous. But the growth rate tells a different story: AI referral traffic increased roughly seven times between 2024 and 2025. A separate analysis by Previsible, which tracked nearly two million LLM-driven sessions between November 2024 and November 2025, found that ChatGPT alone grew 3.26x year-over-year and now accounts for 84.2% of all AI referrals.

The more important data point for marketers, though, isn't volume — it's intent. According to Seer Interactive, visitors arriving from LLMs convert at dramatically higher rates than organic search visitors: 15.9% for ChatGPT, 10.5% for Perplexity, versus Google's organic conversion rate of 1.76%. Semrush research found that LLM visitors convert 4.4x better than traditional organic visitors overall. These are people who've already done their research inside the AI interface. They arrive pre-qualified.

Sources: SE Ranking (2025); Previsible State of AI Discovery Report (2025); Seer Interactive (June 2025); Semrush (July 2025)

How the buyer journey has been compressed

The traditional B2B or considered-purchase journey was always somewhat linear: problem awareness, category research, vendor shortlisting, comparison, decision. Each stage happened across multiple websites. Marketers could observe that progression through analytics and use content to intervene at each step.

AI search collapses several of those stages into a single interaction.

Ask ChatGPT 'what are the best customer support platforms for ecommerce?' and within seconds you receive an answer that has already identified the category, summarised the key vendors, and assigned attributes to each. The AI has done in one response what used to require reading four or five different articles.

For buyers, this is obviously useful. For brands, it has a less comfortable implication: the AI becomes the first interpreter of your product. Before a prospect visits your website or reads your messaging, the model has already told them what you stand for and how you compare to alternatives.

The Previsible report makes this structural shift explicit: when LLMs handle early comparison and filtering, upstream visibility becomes the gatekeeper to consideration.

Zero-click influence: discovery without attribution

A Bain & Company survey found that around 80% of consumers now rely on zero-click results in at least 40% of their searches, with organic web traffic estimated to have dropped between 15% and 25% as a result. By mid-2025, zero-click searches accounted for roughly 65% of all queries globally, according to analysis from Onely.

AI-powered tools extend this phenomenon significantly. An entire research journey — awareness, comparison, provisional preference — can now happen inside a chat interface without any outbound click at all. A buyer who types 'what CRM should a B2B SaaS company use?' into ChatGPT, reads the response, and decides on a shortlist has just completed several stages of a vendor evaluation. Nothing registers in any brand's analytics.

Digiday spoke to Edward Cowell, global VP of SEO at WPP Media, who summarised the dynamic plainly: 'There's more of the consumer discovery and evaluation happening within these AI summaries. But people still want to buy stuff. You still go into the website to transact.'

This is why brand presence inside AI answers is a genuine business problem, not just an organic search metric. When a brand consistently appears in AI responses to category questions, it benefits from repeated exposure at the earliest stages of consideration — even if that exposure is never tracked. When it doesn't appear, it may never enter the buyer's initial thinking at all.

Sources: Bain & Company; Onely (December 2025); Digiday (February 2026)

AI doesn't just retrieve your brand — it defines it

There's a meaningful difference between a search engine that surfaces your content and an AI system that interprets it.

When an AI model generates an answer about a product category, it assigns attributes. It doesn't just list vendors — it describes them. A project management tool gets labelled 'best for structured workflows' or 'built for creative teams.' A CRM gets characterised as 'enterprise-grade' or 'a good starting point for smaller teams.' These descriptions arrive before any buyer has engaged with your own marketing materials.

Those labels come from aggregated signals across the internet: review platforms, industry publications, comparison articles, Reddit threads, documentation, press coverage, community forums. The model synthesises all of that into a simplified narrative about what each brand represents.

The practical implication is that your brand perception in AI search often has little to do with your website copy. It reflects the broader information ecosystem around you — the third-party sources that talk about you, the context in which your product gets mentioned, and the consistency of those signals over time.

BrightEdge's September 2025 analysis found that 83.3% of AI Overview citations came from pages outside the traditional top-10 search results, suggesting that content depth, readability, and freshness matter more than conventional SEO signals like domain authority.

Sources: HubSpot (January 2026); BrightEdge (September 2025)

Why third-party sources now matter more than your own website

Because AI answers are built from aggregated third-party signals, the question of 'where does your brand appear online' has taken on new strategic weight.

If your product is consistently mentioned in comparison articles on respected industry blogs, cited in G2 reviews, referenced in community discussions on Reddit, or covered in trade publications, those references become part of the knowledge base AI models draw from.

Conductor research published in early 2026 found that nearly one-third of digital marketing leaders now list generative engine optimisation (GEO) as their most critical performance challenge. An average of 12% of 2025 digital budgets was allocated to GEO initiatives, with 32% of digital leaders naming it their top priority for 2026.

There's also a specific risk worth naming: AI brand drift — when LLMs spread outdated or incorrect information about a company without the brand knowing it's happening. If inaccurate information is more consistently present in third-party sources than accurate information, models can perpetuate those inaccuracies at scale.

Sources: Conductor / MarTech (February 2026); eDesign Interactive (February 2026)

What to measure when clicks are no longer the signal

Website traffic and conversions still matter. But they primarily capture buyers who've already completed the research phase and decided to visit. They're a late-stage metric in a journey that now starts much earlier — inside an AI interface.

To understand how AI is affecting your brand's discoverability, you need to track different signals:

AI visibility — how frequently your brand appears in responses to relevant prompts across major platforms (ChatGPT, Perplexity, Gemini, Google's AI Mode). This requires systematic prompt testing, not just analytics dashboards.

Competitive context — which competitors appear alongside you, and in what framing. Are you consistently positioned as an alternative to a stronger brand, or as the default recommendation in your category?

Attribute accuracy — what characteristics does the AI associate with your product? Are those characterisations consistent with how you want to be known?

Source influence — which third-party publications, review sites, and community platforms are shaping the AI's understanding of your brand? Where are the gaps?

This is the core problem that platforms like GetMentioned are designed to address — giving marketers visibility into how their brand appears in the AI discovery layer, and which sources are shaping that narrative.

Source: MarTech (November 2025)

The bottom line

AI search has not killed the buyer journey. People still research vendors, still read reviews, still visit websites before they commit to a purchase. What has changed is where the earliest and most formative stages of that journey now happen.

Before a buyer arrives at your homepage, they may already have a shortlist, a preference, and a set of associations with your brand name — all shaped by an AI system that aggregated signals from sources you may never have thought of as marketing channels.

The question for marketers is no longer just 'how do we rank in search?' It's 'how do we appear in the answer?' And then, equally important: does that answer accurately represent who we are?

GetMentioned helps marketers track AI visibility across major LLM platforms, monitor brand mentions in AI-generated answers, and understand which third-party sources are shaping how their company is perceived.