Most GEO advice breaks the moment you split ChatGPT from Google

Google AI Overviews and Perplexity overlap on 55% of cited domains. ChatGPT overlaps with either by less than 6%. If you're still following one big GEO checklist, you're probably optimizing for three different systems as if they were one.

How should B2B SaaS approach ChatGPT vs Google AI SEO?

Treat Google AI Overviews and Perplexity as citation engines, and treat ChatGPT as a separate bet that often doesn't pay publishers back. The biggest useful claim in Geology's report isn't about prompts or formatting. It's that there are two ecosystems, not three.

In Geology's 3,000+ prompt study, Google AI Overviews and Perplexity shared 55% domain overlap. ChatGPT shared less than 6% with either. That matters because broad GEO advice usually assumes the same pages, the same tweaks, and the same distribution logic will work everywhere.

They won't. Geology also says 30% of ChatGPT queries produced zero citations because web search never triggered. FAQ and how-to queries had 0% web search activation. "Best X" and comparison queries were the ones that reliably triggered citations, at 75% to 94%.

If you run a B2B SaaS, that changes the question. Stop asking, "How do I rank in AI?" Ask which AI surfaces actually cite sources in your category, and which ones mostly keep the user inside the answer box.

The popular GEO checklist looks weak in this dataset

A lot of the advice getting passed around right now sounds easy because it's mechanical. Add FAQ blocks. Clean up schema. Reformat pages for bots. The problem is Geology's report says those moves had little measurable effect in this B2B SaaS dataset.

The report found:

• Pages over 5,000 words received 50% more AI citations than mid-length pages
• Pages with 30+ external links got cited 60% more often
• FAQ pages trended slightly negative at a 0.94x citation ratio
• Schema markup showed only a weak correlation at r=0.103

That's a very different playbook from the usual "just add structure" advice.

The pages that seem to win here look more like serious resource pages than polished SEO templates. Longer pages. More source links. More evidence. More depth. Less time spent decorating thin content.

That should feel familiar to any founder who actually knows their market. The strongest content for AI citation may end up being the same content that already helps humans trust you: detailed comparisons, implementation guides, original data, and pages that cite the web instead of pretending to be the whole web.

Google just gave teams a way to measure one part of this directly

Google made this less theoretical on 3 June 2026 when it launched Search Generative AI performance reports in Search Console, per Google Search Central. That matters because teams can now separate AI Overview visibility from normal search reporting instead of hand-waving about being "optimized for LLMs."

You still won't get a clean dashboard for every AI product. ChatGPT remains murkier, and Ahrefs has already pointed out that AI Overviews create mention, citation, and click-loss problems that standard traffic reports don't fully capture. But Google's reporting at least gives founders one hard place to start.

If your category gets meaningful discovery from Google AI Overviews, you can now watch that directly. If it doesn't move, that's useful too. It tells you your GEO work may be aimed at the wrong surface, or that the traffic payoff isn't there even if citations are.

Measurement is the real upgrade here. Not because every number will be perfect, but because it gets you out of the fantasy phase.

The practical move is to pick your AI surfaces before you pick your tactics

A tiny SaaS team does not need another universal content checklist. A tiny SaaS team needs a decision about where effort has a shot at producing trackable discovery.

Start with three questions:

1. Does Google AI Overviews show up on the commercial queries that matter to us?
2. Does our category get cited by Perplexity or ChatGPT in a way that sends any discoverable demand?
3. Are we publishing pages that deserve citation because they contain proof, comparison, and sources?

Then build for the surfaces that actually return value.

For Google AI Overviews and Perplexity, Geology's report points toward deeper pages with stronger citations. For ChatGPT, the same report suggests you may only see web citation upside on certain query types, especially comparisons and "best" terms. That means some AI usage may matter for brand awareness but never turn into measurable publisher upside.

That's the part people don't want to hear. There may not be one AI search strategy at all. There may be one measurable strategy for Google, a related one for Perplexity, and a separate decision about whether ChatGPT is worth chasing in your category.

If you only have a few hours a week, that's actually good news. It means you can stop trying to "optimize for AI" in the abstract and start testing the surfaces that can still send you credit.