93.7% of ChatGPT Visitors Also Used Google in September

By Olivia Hart

In September, 93.7% of ChatGPT.com's visitors also visited Google.com, according to a Similarweb audience-overlap figure reported by Search Engine Watch. The overlap ran both ways: 14.1% of Google.com's visitors also visited ChatGPT.com that month.

The numbers demand careful reading. They count people who visited both sites during the month — nothing more. The data does not show which service a user opened first, how often they searched, what they searched for, or whether they bought anything. It also misses app usage on both platforms.

The takeaway in plain words: this is channel overlap, not channel substitution.

What does the overlap figure actually prove?

It proves very little about behavior, and the author of the analysis — an Entrepreneur contributor — is candid about that. The finding "is not proof that someone asked ChatGPT about a product, then searched for it on Google," the analysis states.

The author draws on history to frame the risk: some companies once treated SEO as a separate experiment instead of infrastructure for existing demand. The risk now runs in reverse — treating AI discovery as a replacement for search habits customers still have.

The measurement hazard is concrete. A customer might encounter a brand in an AI answer, then search for it by name. That later visit registers as Google organic traffic, even if the AI interaction created the demand. Or the AI interaction may never produce a site visit at all. The overlap data cannot distinguish between these outcomes.

Why last-click attribution fails here

A referral source records where a session came from. It usually cannot tell you which earlier interactions made the brand worth looking up. That is why last-click reporting is, in the author's framing, "a poor referee for this shift."

Google has started closing part of the gap. Its Search Console generative AI performance report shows impressions for pages appearing in Google's AI search features, including AI Overviews and AI Mode. Even this carries limits: it is visibility data, not proof of incremental traffic or revenue, and it covers only Google's AI features — not ChatGPT or other platforms.

The recommended fix is to keep measurement sets separate but parallel:

• Track traditional search clicks, branded searches, qualified leads and sales.
• Monitor which pages appear in Google's AI features.
• Check whether the brand is cited in a consistent set of relevant AI prompts.
• Add a simple question to lead forms or post-purchase surveys: "Where did you first hear about us?"

No single signal proves AI caused a sale. Together, the author argues, these measures reveal patterns that last-click reports miss.

Should budgets split evenly between Google and AI?

No — and the analysis is explicit on this point. The response is "to stop planning as if every platform reaches a different customer." Treating AI audiences and Google audiences as separate pools invites double-counting, inflated reach estimates and bad budget decisions.

The practical program keeps both disciplines running. Keep investing in the parts of search that help customers find and evaluate a business. Keep product, pricing and value pages current. Then extend the same scrutiny to AI discovery: verify that answer engines describe the business accurately, cite useful sources and include the brand when customers compare options.

Internal alignment matters as much as tooling. If SEO reports falling clicks while AI visibility rises, the author advises against declaring one channel the winner. Look instead at branded search, lead quality, direct visits and conversion trends — and compare patterns over time, not across one month's traffic report.

What the 93.7% figure does not tell you

The author does not read the figure as evidence that Google is safe, or that AI search is harmless to existing traffic. "It doesn't answer either question," the analysis states.

The sharper conclusion: customers can add a new way to discover a business without abandoning the old one. A customer may meet a brand in an AI answer and Google it before acting.

The companies that understand both moments, the author concludes, will make better decisions than the ones still asking which channel gets credit for the whole journey.