Behavior Trumps Targeting in ChatGPT Ads
▼ Summary
– ChatGPT is testing ads in the U.S., marking the first time advertising enters a trusted AI task environment, which requires a new marketing approach.
– Unlike passive feed-based platforms, ChatGPT is a task environment where users have narrowed, goal-oriented attention and a low tolerance for irrelevant interruptions.
– Success depends on understanding user behavior modes (like Explore, Reduce, Confirm, Act) rather than targeting keywords, as people use ChatGPT to outsource thinking for specific outcomes.
– Relevance in this context is functional; ads must be useful tools or guides that help complete the task, not just topically related brand messages.
– Measurement must evolve beyond clicks to include influence on decisions, like shortlist inclusion or brand recall, requiring integrated team strategies and behavioral insight.
The introduction of advertising within ChatGPT represents a fundamental shift in digital marketing, moving beyond traditional targeting to prioritize user psychology and behavior. This new AI-driven environment demands a fresh approach, as replicating strategies from search or social platforms will likely lead to poor performance and could damage user trust. Success hinges on understanding that people use ChatGPT as a task-based tool, not a passive feed, which fundamentally alters how they perceive and interact with ads.
People open ChatGPT with a specific goal in mind, whether it’s solving a problem, planning a trip, or making a complex decision. In this focused, task-oriented setting, user behavior changes significantly. Attention narrows to completing the objective, a phenomenon known as goal shielding, where anything not directly helpful feels like an irrelevant interruption. Users develop tunnel focus, prioritizing clarity and momentum over exploration. This makes clicks harder to earn; an advertisement must feel functionally useful to the immediate task, not just topically related. Given that trust in AI is still forming, tolerance for intrusive or poorly matched advertising is exceptionally low.
This shift is profound because it removes a traditional marketing cornerstone: search volume data. For years, keywords illuminated user intent, demand, and competition. In ChatGPT, people are not searching; they are outsourcing thinking. They describe situations and ask layered questions to achieve outcomes. Without query data to optimize against, the strategic foundation moves from keyword demand to behavioral insight. Marketers must now ask: What job is the user trying to get done? Which part of their journey are they outsourcing to AI? What kind of help do they need right now?
Consequently, planning must shift from keyword intent to targeting user behavior modes, the mindset someone is in when they engage with the AI. These modes can be categorized to guide creative strategy. In Explore mode, users are shaping perspectives or seeking inspiration; effective ads here offer ideas or reframe problems. In Reduce mode, users are simplifying choices; ads should clarify differences and highlight trade-offs to reduce effort. In Confirm mode, users seek reassurance, making trust signals like proof, reviews, and guarantees critical. In Act mode, users aim to complete a task, so ads that remove friction by clearly stating pricing, availability, and next steps will perform best.
A critical principle for advertisers is that relevance in ChatGPT is functional, not merely topical. An ad perfectly aligned to a category will still fail if it doesn’t help the user progress. In this environment, anything creating extra work feels like friction. Therefore, high-performing ads will resemble tools, templates, guides, checklists, shortcuts, or decision aids that integrate seamlessly into the user’s flow. Generic brand awareness messages or content that feels like a detour are likely to underperform.
The assets that make a strong ChatGPT ad, practical guides, frameworks, calculators, and reassurance-led content, also serve a broader strategic purpose. Helpful content becomes a bridge across marketing channels, building authority for SEO, earning credibility through digital PR, and reinforcing brand trust on social and owned channels. This convergence breaks down traditional silos. Effective ads in this space may blend brand voice for consistency, a trusted voice through expert validation, and an amplified voice via media coverage, blurring the lines between advertising, content, and credibility.
Measuring success also requires a reset. Judging these ads solely by click-through rate is inadequate, as their influence may be more subtle. An ad might help a brand enter a user’s shortlist, build reassurance, or be remembered for a later conversion on another channel. More meaningful indicators could include shortlist inclusion, brand recall, assisted conversions, uplift in branded search or direct traffic, and downstream conversion lift. This distributed impact necessitates closer collaboration across teams, with measurement frameworks that account for influence across the entire customer journey.
Ultimately, this is more than a new ad format; it’s a behavioral shift. The brands that succeed will be those that best understand what people use ChatGPT for, which journey moments are outsourced to AI, and how to support those moments without breaking trust. A practical starting point is jobs-to-be-done thinking: map the actions before a purchase or commitment and identify where AI reduces effort or uncertainty. The central question becomes, “How can we be genuinely helpful at the moment it matters?” This mindset will define performance not just in ChatGPT, but across the broader future of AI-led discovery, where behavioral intent will matter far more than keywords ever did.
(Source: MarTech)
