TL;DR
GEO is the practice of getting your brand mentioned, cited, and recommended inside AI-generated answers (ChatGPT, Google AI Overviews, Perplexity, Gemini, Copilot). It overlaps with SEO but optimizes for a different unit of distribution: the answer, not the click. Run a four-step loop — research, optimize, monitor, report — and treat it as a quarterly board-level discipline.
Key takeaways
- GEO ≠ SEO. SEO ranks pages; GEO earns citations inside AI-generated answers. The fundamentals overlap, the optimization target is different.
- The four-step GEO loop: research prompts → optimize content + technical + off-page → monitor mentions, citations, share of voice, sentiment → report to the C-suite.
- Don't block AI bots. GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, and Google-Extended should be allowed in your
robots.txtif you sell B2B SaaS. - Comparison and 'best of' queries are now answered by AI engines before users click. If you're not in the answer, you're not in the shortlist.
- First 90 days: baseline (days 1–30), quick wins (days 31–60), operating rhythm (days 61–90). Measurable mention-rate lift typically inside one quarter.
What is GEO (Generative Engine Optimization)?
GEO (Generative Engine Optimization) is the discipline of making your brand the answer when a buyer asks an AI engine a question relevant to your category. The "engines" are LLM-powered surfaces: ChatGPT, Google AI Overviews and AI Mode, Perplexity, Gemini, Microsoft Copilot, and whatever Anthropic ships next.
The core shift is mechanical. Classic SEO optimizes a page so a crawler can rank it. GEO optimizes a brand, an entity, and a body of content so a model can retrieve and cite it while composing an answer. The deliverable is no longer a #1 ranking; it's being mentioned in the response and ideally cited as a source with a clickable link.
When I joined Storyblok in 2018, the entire SaaS marketing playbook was 'rank for your category keywords.' Today, half the time, your buyer never sees a SERP. They see one synthesized answer. The companies treating GEO as a board-level discipline in 2026 are the ones still around in 2028.
GEO vs. SEO: what's the same, what's different
SEO and GEO share fundamentals (crawlability, schema, internal linking) but optimize for different units of distribution. Here's the side-by-side I use in every CMO briefing:
| Dimension | SEO | GEO |
|---|---|---|
| Unit of distribution | A ranked URL | A cited mention inside an answer |
| Measurement | Position, clicks, impressions | Mentions, citations, share of voice, sentiment |
| Crawler | Googlebot | GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, Google-Extended |
| Content unit | Page | Passage / entity / claim |
| Authority signal | Backlinks | Citations, brand mentions across the open web |
| Lag | Weeks to months | Days to weeks (then re-cached) |
The continuity matters more than the difference. Strong technical SEO is table stakes for GEO. The new work is on top.
Why GEO matters now for B2B SaaS
Three structural changes are hitting B2B SaaS first and hardest in 2026:
- Comparison and "best of" queries are being answered before the click. "Best headless CMS," "Notion vs. Coda," "Stripe alternatives" — buyers get a synthesized answer from ChatGPT or AI Overviews. If your brand isn't in the answer, you're not in the consideration set.
- Buyer journeys are starting in LLMs. Recent buyer surveys put 30–50% of B2B research originating in a chat interface. That number only grows.
- Branded search is decoupling from intent. The funnel isn't "search → site → sales call." It's "ask LLM → maybe visit a few sources → arrive shortlisted." If you're not in the LLM answer, you don't reach the shortlist.
Why I started OtterlyAI
I built OtterlyAI because I kept watching B2B SaaS brands lose pipeline they didn't know they were losing. You can't fix what you can't see. OtterlyAI is the visibility layer for AI search — track your mentions, citations, share of voice, and sentiment across ChatGPT, Perplexity, Gemini, AI Overviews, AI Mode, and Copilot, then act on it.
The GEO stack: research, optimize, monitor, report
Every GEO program I've seen succeed runs the same four-step loop.
1. Research
You can't optimize for prompts you don't know about. Map the 50–200 prompts your buyers actually type into AI engines. Start from sales call transcripts, support tickets, and SEO keyword data, then expand with query fan-out tooling. Categorize prompts by stage: problem-aware, solution-aware, comparison, evaluation, replacement.
2. Optimize
Three layers:
- Technical: ensure GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and OAI-SearchBot can crawl. Ship a sane
robots.txt, valid structured data, and clean canonical signals. - Content: publish passages that LLMs love to cite — direct definitions, comparison tables, statistics with sources, named-entity clarity. Reduce hedging and intro fluff.
- Off-page: earn citations on the sources LLMs trust. For B2B SaaS that's G2, Capterra, TrustRadius, the right trade publications, well-cited Reddit and Wikipedia adjacencies, and product-comparison content from independent reviewers.
3. Monitor
Track prompt-level performance across engines. The metrics that matter: brand mention rate, citation rate, share of voice vs. competitors, sentiment (NSS), and prompt-coverage. This is where most teams fall down — they treat GEO as a one-time content project instead of an ongoing measurement discipline.
4. Report
Translate the data into a board-ready narrative. Mentions trending up? Show it next to demo requests and pipeline. Sentiment dropping in a key prompt set? Triage the cited sources and fix them.
The first thing I tell every CMO who asks me about AI search: you're being described whether you measure it or not. The question is whether you want to own the narrative or hand it to your competitors.
First 90 days of GEO for a B2B SaaS marketing leader
Days 1–30 — Baseline. Audit crawlability (bots, robots.txt, structured data). Pick 50 priority prompts. Run a baseline scan across ChatGPT, AI Overviews, Perplexity, Gemini. Document mention rate, citation rate, top competitors, top cited sources.
Days 31–60 — Quick wins. Fix the technical issues. Rewrite the 10 most-visited pages with passage-level optimization (definitions, comparison tables, sourced stats). Get listed/refreshed on the third-party sources LLMs are citing for your competitors.
Days 61–90 — Operating rhythm. Stand up a weekly GEO scorecard. Bake GEO into your content brief template. Add a "GEO score" to the editorial checklist. Brief the CRO and product marketing on what shows up in answers — they need to know what buyers are being told.
Common GEO mistakes
- Treating GEO as SEO with extra steps. The optimization unit is different. Keyword density doesn't help. Direct, sourced, citation-worthy passages do.
- Blocking AI crawlers. Some teams reflexively blocked GPTBot in 2023. If you sell B2B SaaS, that decision is almost certainly costing you pipeline today. Audit your
robots.txt. - Optimizing without measuring. If you're not tracking prompt-level visibility, you're guessing.
- Ignoring sentiment. Being mentioned negatively is worse than not being mentioned. Watch how engines describe you.
Tools and resources
You need a GEO platform for prompt-level visibility tracking (I built OtterlyAI for exactly this), a strong analytics stack (GA4 + your CRM), a structured-data validator like Google's Rich Results test, and the same SEO research tools you already use (Ahrefs, Semrush) for the underlying keyword and citation work. Pair these with the deeper guides on AI search visibility and tracking brand mentions in AI search.
Get a GEO baseline for your SaaS in 24 hours
OtterlyAI gives you a baseline visibility report across every major AI engine — mentions, citations, share of voice, sentiment, and the actual answers AI engines are giving about your category. Most B2B SaaS teams find at least three competitors being recommended above them in answers they didn't know existed.
Where this is going
The 2026 reality: AI engines are now a real distribution channel. The companies treating GEO as a board-level marketing discipline are pulling away from the ones still arguing about whether ChatGPT counts. Pick your camp.
FAQs
What is GEO in simple terms?
GEO (Generative Engine Optimization) is the practice of making your brand visible inside AI-generated answers from ChatGPT, Google AI Overviews, Perplexity, Gemini, and Copilot. It's how you stay in the consideration set when buyers ask an AI engine instead of typing a Google search.
Is GEO different from SEO?
Yes — and they're complementary, not competing. SEO optimizes a page so a crawler ranks it; GEO optimizes a brand and its content so a model retrieves and cites it inside an answer. Most strong SEO foundations (crawlability, structured data, internal links) are required for GEO.
Does GEO replace SEO?
No. Google still drives a large share of B2B SaaS pipeline, and AI Overviews themselves are part of Google SERPs. Run them as one program with two surfaces.
How do I measure GEO success?
Track prompt-level brand mention rate, citation rate, share of voice vs. competitors, sentiment (NSS), and engine-by-engine coverage. Connect those metrics back to demo requests, signups, and pipeline.
What's the first GEO step for a SaaS marketing leader?
Run a baseline. Pick 50 prompts your buyers actually ask, scan them across the major engines, and benchmark mention rate, citation rate, and share of voice against three competitors. You'll know exactly where to invest within a week.
Who is Thomas Peham?
Thomas Peham is the CEO and founder of OtterlyAI, a Generative Engine Optimization platform. He was previously VP of Marketing at Storyblok and has been working in B2B SaaS marketing since 2014. His work on AI search has been covered in TechCrunch, CMSWire, and Trending Topics.