ChatGPT advertising

ChatGPT advertising means paying for placement inside the conversations people are having with AI assistants. It is the newest surface in marketing, the least proven and currently the cheapest attention in serious consideration. That combination is exactly why it deserves care rather than hype. The formats are young, measurement is still settling and what is available to buy changes quickly. We run it as a capped experiment with clear hypotheses and a fixed budget agreed in advance. For early movers in competitive markets it buys learning before competitors have a plan. For regulated markets it means every claim checked before spend, exactly as on any other channel. Expect honest reporting on what happened, including when the answer is that nothing much happened yet. We do not promise performance here. Nobody honestly can yet. We promise a well-designed test and reporting that does not flatter it.

People increasingly ask an assistant before they ask a search engine. The assistant summarises the market, recommends a shortlist and, on the surfaces that carry them, shows a sponsored placement inside that answer. Whether this turns into a channel you can depend on for years is unproven, and we are not going to pretend otherwise. What is already true is that attention there is currently cheap and the people doing the asking are often deep in a decision rather than idly browsing. That combination is worth testing carefully and worth testing early, provided the budget is capped and nobody mistakes an experiment for a forecast. The honest framing matters here more than in most channels. Nobody knows whether assistant advertising becomes a major line in your marketing mix or a footnote in a year, including the people selling it. What is knowable is what happens when you spend a defined amount this quarter and whether the people who arrive behave like buyers.

We take a test-and-learn position with clients on this channel. A fixed budget cap agreed in advance, a small number of clear hypotheses and enough measurement to tell you what actually happened. The questions worth answering are simple. Does a placement there produce qualified visits. Do those visitors behave differently from search traffic. What does the same intent cost on Google. Until those are answered, scaling spend is guesswork dressed up as strategy, and guesswork with real money is how new channels get abandoned before anyone learned anything from them. There is a discipline to this that new channels usually lack. The budget cap is set before the creative exists, the criteria for stopping are written down in advance and the reporting template is agreed before the first placement runs. That sounds procedural. It is the only thing standing between an experiment and a slow drift into spend nobody can account for.

The other half of this is becoming the source the assistant recommends, which is where our AI SEO work sits alongside the paid test. In regulated markets every claim is checked before spend, and that matters more here than almost anywhere else, because you are being described as well as advertised. An assistant that repeats a claim back about you has done your marketing for you or your compliance team's worst case study, sometimes in the same sentence. Getting the words right before the money moves is the whole discipline. The two halves reinforce each other. A paid placement beside a recommendation that already cites you carries more weight than a placement alone, and the content work survives long after the campaign stops. That part is worth funding even if the paid test disappoints, and it is the part most likely to still matter next year.