ChatGPT Advertising: Behaviour Beats Targeting

Advertising within ChatGPT represents a major shift away from traditional keyword-driven strategies towards a deeper understanding of user behaviour. For marketers, this changes the way relevance, creative messaging, and performance measurement need to be approached.

Ads are currently being trialled in ChatGPT in the U.S., appearing to some users across a variety of account types. For the first time, advertising is entering a trusted AI environment where users rely on the platform to help them think, make decisions, and take action. This is very different from simply adding another channel to an existing media plan.

The critical challenge is not targeting users in the conventional sense, but understanding their psychology. If advertisers replicate what works on search engines or social media without considering the AI context, results may be disappointing, and user trust could be damaged.

Success requires a clear grasp of why people turn to ChatGPT and what they hope to achieve. Marketers need to consider attention spans, task relevance, and the broader customer journey. ChatGPT is used as a tool to accomplish goals, rather than a platform for passive content consumption.

Unlike feed-based platforms, users come to ChatGPT with a specific task in mind. They may be looking to solve a problem, refine a shortlist of options, plan a trip, draft a document, or navigate a complex decision. This task-oriented mindset shapes how they interact with ads.

Behavioural patterns in ChatGPT differ significantly from social feeds: attention is narrow and goal-focused, users resist interruptions, and they prioritise clarity and speed over exploration. Ads that don’t directly help users progress with their task are likely to feel irrelevant, regardless of how closely they match the topic.

Trust in AI platforms is still developing, making users less tolerant of poorly targeted or intrusive advertising. Any ad that creates friction can damage the perceived reliability of the AI environment.

In this context, traditional keyword data is no longer the main strategy. In search and SEO, keyword volumes inform planning and reveal user intent. In ChatGPT, users do not search for keywords—they describe situations, ask multi-layered questions, and look for actionable solutions rather than just information. Behavioural insight, rather than keyword demand, becomes the foundation for strategy.

Marketers need to shift from query-based targeting to “behaviour mode” targeting, which focuses on the mindset a user is in when using ChatGPT. These modes can be broken down as:

Explore mode: Users are seeking inspiration or forming perspectives. Ads that work here offer ideas, options, or problem-reframing.
Reduce mode: Users aim to narrow down choices. Effective ads simplify decisions, clarify trade-offs, and reduce effort.
Confirm mode: Users need reassurance. Trust signals such as reviews, guarantees, or credible references are key.
Act mode: Users are ready to complete a task. Ads that remove friction—clear pricing, availability, and next steps—perform best.

While these modes resemble behaviours observed in traditional search, ChatGPT compresses them into a single interface, creating new challenges for ad design.

Relevance in ChatGPT is functional rather than topical. An ad aligned with a category may still fail if it does not actively help the user achieve their goal. Ads that succeed tend to behave more like tools, checklists, guides, templates, or decision aids rather than traditional promotional content. Anything that interrupts workflow or feels like a detour is likely to underperform.

This task-oriented approach to advertising also blurs the lines between paid media, content marketing, and brand credibility. Assets designed for ChatGPT—practical guides, calculators, frameworks, and reassurance-led content—also support SEO, digital PR, and social engagement, strengthening brand trust across multiple channels.

Teams cannot operate in silos. Paid media, SEO, PR, and brand teams need to coordinate, as signals from each channel influence user behaviour and overall perception. The most effective campaigns integrate brand voice, trusted validation, and authority into a cohesive experience.

Traditional metrics such as click-through rates are often insufficient. ChatGPT ads may influence decisions without generating immediate clicks. Alternative measures of success include inclusion on a shortlist, brand recall, assisted conversions, search lift, and downstream sales impact. Measurement strategies must reflect the distributed nature of influence across the user journey.

Ultimately, brands that succeed will be those that understand behaviour deeply. It is not about spending the most or adopting the newest format, but about comprehending how users interact with ChatGPT, what tasks they are outsourcing to AI, and how to support them without breaking trust.

A practical approach is to adopt a “jobs-to-be-done” perspective, mapping the actions users take before making a purchase or commitment, and identifying where AI reduces effort, uncertainty, or complexity. From there, the guiding question shifts from “how do we advertise here?” to “how can we genuinely help at the moment it matters?”

This mindset will not only shape performance in ChatGPT but also the broader future of AI-led discovery, where behavioural intent matters far more than keywords ever did. The brands that master this shift are likely to gain trust, attention, and meaningful engagement in an increasingly AI-driven digital landscape.