OpenAI is testing a new ad format on ChatGPT: when a user clicks on an ad, they don't go to the brand's website but directly open a conversation with an AI agent. No landing pages, no traffic to track with Google Analytics.
For those managing paid campaigns, this changes the underlying logic: the point of contact shifts inside the platform. Classic metrics — sessions, bounce rate, time on site — become irrelevant. What matters is what happens in the chat.
It's not available for everyone yet. But it's worth understanding now, before it arrives in media plans as a standard option. Those managing ad budgets in sectors with long sales cycles or complex products have more to gain from this format than those selling simple, low-priced products.
A click that opens a chat, not a page
The new format announced by OpenAI — described by Digiday — it works like this: the brand creates an ad within ChatGPT, the user clicks on it and instead of landing on a website, they find themselves talking to an AI agent configured by the brand itself.
An AI agent, in this context, is a conversational assistant trained to answer about a specific product or service: it can answer questions, qualify interest, collect contact information, and guide towards a purchase decision.
The structural difference compared to any other form of digital advertising is this: the funnel — that is, the path from the ad to the conversion — never leaves the ChatGPT platform.
What breaks compared to the current logic of campaigns
Anyone managing Google or Meta campaigns knows that the click is just the beginning: it drives traffic to a landing page, and that's where everything is measured. Bounce rate, time on page, form completion, purchase. Every step is trackable and optimizable.
With ChatGPT's click-to-chat format, that chain is broken. Traffic doesn't reach the website. Sessions don't appear in Analytics. Meta's pixel sees nothing.
This creates two concrete problems:
- Attribution : how do you measure if that conversation generated a customer? The topic of advertising attribution is already complex today — when attribution models deceive the budget is a real risk even without adding new opaque channels.
- Creative control : the brand defines the agent's instructions, but the conversation is generative. The AI responds differently to each user. There's no fixed copy to approve.
These are not insurmountable problems, but they should be taken into account before allocating budget.
Who can really benefit from this format
Click-to-chat makes sense when the product or service requires qualification before the sale. Typical sectors:
- B2B software with demos on request
- Professional services (consulting, training, legal)
- Products with custom configurations
- Financial or insurance sectors where demand is complex
In these cases, the AI agent can do the job that a contact form plus a pre-qualification call does today: understand the need, answer initial objections, collect useful data.
It makes less sense for those selling simple, fixed-price products, where the ideal path is still click → product page → cart → purchase. Adding an intermediate conversation slows things down, it doesn't speed them up.
It's also worth looking at what's already happening with integrations between AI platforms and advertising: Amazon Ads on ChatGPT has already opened up this territory for those who sell on marketplaces, and Amazon DSP on ChatGPT Ads shows how Italian B2B can intercept users in the active search phase.
The budget issue: where control ends
One of the less discussed risks of new AI formats is the loss of budget governance. With Google and Meta, automation is advancing, but there are still thresholds, targets, and manually settable rules. The topic is already open: how to stay in control when Google and Meta automate campaigns is a question many marketing managers are already asking themselves.
With a new format like ChatGPT's click-to-chat, governance is even more uncertain. There are no historical benchmarks, no consolidated best practices, no agencies with years of data to rely on.
This doesn't mean avoiding it. It means entering it with a logic of contained testing: separate budget, clear objectives, metrics defined before launching the campaign.
What to do in the coming months, concretely
The format is not yet generally available. But the time before the official launch is useful for preparation:
- Map conversational touchpoints : what questions do salespeople currently receive during the pre-qualification phase? These are the AI agent's instructions.
- Define alternative metrics : if website traffic is no longer the main metric, what replaces it? Completed conversations, data collected, demo requests generated by the chat.
- Isolate the test budget : don't move budget from campaigns that are working. Use a dedicated experimental quota.
- Verify consistency with the rest of the media plan : a format that lives within ChatGPT needs to be integrated into the strategy paid media and advertising overall, not added as an appendix.
A common mistake in these cases is to wait for the format to mature before studying it. When it becomes mainstream, those who haven't already thought about AI agents, attribution, and conversational metrics start late.
SHM Studio follows the evolution of these formats to help companies evaluate where and when it makes sense to experiment, without burning budgets on channels not yet ready for their market.
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