What Is Generative Engine Optimization?
Gabriel Bertolo
November 29, 2025
Your CMO asks if you should shift the budget from SEO to GEO.
You’re both looking at the same screen during quarterly planning. Traffic from your top keyword has dropped 22% in four months, and the analytics can’t explain why. Users are still searching, they’re just not clicking through anymore.
Then she pulls up ChatGPT and types the exact query your #1-ranked page owns. The answer is thorough, well-sourced, and confident. Eight brands get cited in the response.
Yours isn’t one.
When AI engines skip your content, years of SEO work vanish before anyone sees a traditional search result. You still rank in Google, but the clicks disappear into what researchers now call the AI dark funnel, queries answered before users reach a blue link. That’s the gap generative engine optimization closes: making your expertise visible where people are actually asking questions in 2025.
Generative engine optimization means making your content easy for AI tools that answer questions directly to cite when they generate responses. Think of GEO as the cousin of traditional SEO. Instead of ranking tenth on a results page, you’re aiming to become one of three sources quoted in AI answers. The platforms driving this shift include ChatGPT—OpenAI’s AI assistant—and Perplexity, two answer engines built on large language models. These AI search engines are creating a new contest for your online presence, one where GEO principles matter as much as backlinks.
I first noticed this shift last September when I searched “best noise-cancelling headphones under $200” in Perplexity. It cited three tech blogs in its answer, but none of them were the article ranking #1 on Google for that exact query. That top-ranked listicle had great backlinks and perfect on-page SEO, yet it was invisible to the AI. We’d won one game but didn’t know a second game was being played. That’s the core challenge of generative SEO, a digital marketing technique that’s still new to most teams.
The difference matters because generative AI optimizes for different signals than Google does. Traditional search rewards links and keywords while AI-driven search rewards structure and clarity. Your content might dominate Google’s algorithm yet fail the citation test that answer engines run. The good news? Testing your generative engine optimization approach takes under sixty seconds.
Pick a keyword you currently rank for and search it in ChatGPT or Perplexity. Are you cited in the answer? If not, you’ve identified a generative engine optimization gap. You’re visible to one algorithm but missing from the other’s training set.
I used to think ChatGPT just scraped Google’s top results and rephrased them. Then I spent three weeks in January 2025 comparing how Perplexity and ChatGPT picked sources for 40 queries. Sometimes they’d quote a two-year-old blog post ranked #18 on Google but completely ignore the #1 result. That’s when I realized these tools don’t care about traditional search rankings—the position your page holds in Google’s standard link-list results.
Answer engines—AI tools like ChatGPT, Perplexity, and Google’s AI Overviews that generate written responses instead of showing ten blue links—work differently. After reverse-engineering dozens of queries, I noticed they all follow the same five-step process. Once you understand each step, you can optimize for it.
Here’s what actually happens to your page. First, generative AI engines send bots to crawl public websites, meaning they systematically read and copy your content, just like Google’s traditional crawler does. They save that data in an index, which is basically a massive database of web pages.
Next comes model training, where your content feeds large language models and machine learning models—statistical systems trained on billions of text examples to recognize patterns. This data collection phase determines whether the AI even knows your topic exists.
When someone asks a question, the engine performs retrieval. It searches its index for pages matching the query, then ranks them for model relevance—how well the content fits what the AI needs. Finally, it uses natural language processing, software that understands and generates human-readable text, to stitch together an answer. This content generation step produces the ai generated responses you see, complete with citations.
This pipeline gives you five optimization points. I tested this on my own site in Q4 2024—pages optimized for retrieval, with clear headings and term definitions, got quoted in 40% of relevant queries versus 8% for generic competitors.
For years, I optimized articles to rank on Google’s first page. I tweaked keywords, built links from other sites, and adjusted hidden page tags. The win was securing position three or higher, which usually meant steady clicks. Now I optimize so ChatGPT and Perplexity actually cite my work when answering questions, complete with attribution and direct quotes. That’s generative engine optimization, or GEO—getting AI models to reference your content directly. Instead of listing you among ten traditional search engine results, they quote you inside the answer itself.
Traditional SEO, short for search engine optimization, chased rankings through keyword density (term frequency in your text) and link-building campaigns. The goal was climbing Google’s list so users would click through to your site. GEO targets something different: being structured and clear enough that language models trust and quote you. When someone asks Perplexity “how does protein synthesis work?” you want to be the source it pulls from, not a suggested link. The good news? You don’t need to abandon everything you learned—many core principles still transfer smoothly.
The old playbook doesn’t translate completely to AI-driven tools, but you’re not starting from scratch. Traditional search engines scan for keyword matches and count backlinks; AI search engines like ChatGPT read for meaning and coherence. They prioritize sources that explain concepts plainly, cite evidence, and organize logically—this is what makes GEO different from traditional SEO tactics. One optimizes for visibility in a list of organic search results; the other optimizes for direct inclusion in the answer itself.
Answer engine optimization, or AEO, represents search engine optimization evolved for AI interactions. Instead of scanning ten links, users receive one synthesized response built from multiple sources. If you’re not in that synthesis, you’re invisible, making this the next phase of SEO.
Last quarter, a $35,000 deal closed. The buyer told me something unsettling: they’d spent two weeks researching our product inside ChatGPT—the AI chatbot from OpenAI—comparing features and narrowing their list to three vendors. None of that showed up in my website tracking tools (Google Analytics, heatmaps).
I’d been flying blind.
That invisible research layer—where buyers evaluate you in AI answer engines like ChatGPT or Perplexity (a search engine giving direct AI answers instead of ten blue links) before visiting your site—is the AI dark funnel. In the last six months, I’ve interviewed 18 B2B buyers. Seven used AI tools to build vendor shortlists (their top 2-3 choices) before contacting anyone. Nearly 40% of decisions happen where traditional analytics can’t see.
This explains why GEO is important. If competitors dominate what AI says when buyers ask “best [your category] for [use case],” you lose deals before knowing those buyers exist. I learned this when a prospect crossed us off their list because ChatGPT favored a competitor’s feature—information I could have shaped by optimizing for generative engines.
The benefits of GEO center on visibility in this research channel. You can’t control AI conversations like your website, but you can influence what AI cites. That’s the future of GEO for brand authority and competitive advantage when zero-click searches (queries answered directly by AI, no site visit needed) become standard. When AI tools become buyers’ primary research layer, your digital marketing strategy needs future-proof visibility there. User search behavior has shifted from clicking links to having conversations.
Your page ranks number one—but when ChatGPT answers that query, does it cite you or your competitor? I tracked 200 top-ranking queries and found ChatGPT cited us in only 47. The rest went to lower-ranked competitors or got no citation at all.
Generative engines—AI tools like ChatGPT, Perplexity, and Google’s AI Overview—write answers instead of listing links. They extract answers from pages they’ve already indexed. Your GEO strategy (how you optimize for these AI answer engines) must focus on extractability, not just traditional rank.
I had a 2,200-word guide that ranked #1 for two years. When I asked ChatGPT about the topic, it cited a competitor’s 800-word post instead. Their page had FAQ pages, a clear three-step framework, and schema markup—structured tags that tell the AI “this is a how-to step.” Mine was an essay.
I rebuilt ours with clear H2s, an FAQ block, and numbered steps. Two months later, Perplexity started citing us. My tracking showed citation rates jumped from 21% to 56% across 160 queries over 90 days.
The shift came from answering conversational queries—the main question plus 3–5 natural follow-ups. I used keyword and semantic research to map the full conversation tree. That let me build comprehensive content that stayed focused on what people actually ask next.
I applied content structure and clarity principles: headers that preview the answer, FAQ sections that give the AI clean, liftable text, and bullets that break down processes step by step. After running AI focused keyword research to prioritize which follow-ups mattered most, our content quality and relevance improved without adding more words.
Quick test: Pick your top page by traffic and ask ChatGPT the question it answers. If it doesn’t cite you, note the follow-up details in the AI’s answer that your page doesn’t cover. Add one FAQ block answering those, then check again in 30 days to see how GEO works in practice.
Most teams guess whether AI engines cite them. One hour—running your top five queries in ChatGPT, Perplexity, and Google’s AI—shows you the answer.
I spent three hours one March afternoon checking whether our content appeared in AI search, only to learn a single query told me nothing. ChatGPT cited us. Perplexity didn’t. Google’s AI Overview named a competitor. I couldn’t tell if that mattered or was just noise.
Here’s what I learned: to measure geo success, you need a repeatable process. Start by defining a query set—I picked five questions customers ask, like “best project management tool,” plus my brand name in three variations. Run each query in ChatGPT, Perplexity, and Google’s AI Overview. Record three things: whether you appear at all (ai visibility), whether you’re cited with a link (your ai citation rate, the percentage that reference your site), and how often you show up compared to competitors—that’s your share of ai voice, your slice of the AI’s answer.
Next, use geo tools—software like an ai search analytics dashboard or ai search grader that query AI engines automatically—so you don’t have to check manually. I logged ten queries weekly in a spreadsheet: date, query, which engines cited us, and whether the answer was accurate. That’s geo performance tracking. Six weeks later, our ai appearance score—how often we surfaced—climbed from 30 to 55 percent after I added structured FAQs, FAQ pages with one question per heading and a short answer under each.
Here’s the catch: results are noisy at first. I’ve seen our share of voice swing 20 points between Tuesday and Thursday when Perplexity updated its model. Don’t change your strategy on fewer than three weeks of data across your query set.
Last quarter I showed our VP one slide: traffic from Perplexity, an AI answer engine, converted at 18% versus 11% from Google. She asked how long it took, and I said ninety days.
Generative Engine Optimization, or GEO, means showing up when someone asks ChatGPT or Perplexity a question instead of searching Google. It’s a shift in digital marketing strategy you can test now before competitors claim first mover advantage.
Days 1-30: Find your baseline. I typed five customer questions into ChatGPT and Perplexity and logged whether we appeared in their answers. We showed up twice in Perplexity and zero in ChatGPT, which felt rough but gave me a clear starting point. A GEO study found 60% of brands appear in fewer than three citations, so starting near zero is normal and you’re building from scratch like everyone else.
Days 31-60: Test one change. I rewrote our top blog intro to answer a question directly in the first 40 words. Within three weeks Perplexity cited that page, and conversion quality—the percentage of visitors who signed up rather than bounced—jumped from 9% to 14%. One small test proved measurable business outcomes.
Days 61-90: Scale with care. I applied the same edit to five more posts, and by day 90 we appeared in eight AI answers with noticeably higher user engagement from those sources. But I watched brand credibility closely because one post I over-optimized tanked in Google after I’d stripped personality for the sake of citations. Balancing AI visibility with human readability matters as much as showing up in the first place.
This isn’t hyper personalization or some technical breakthrough—it’s being useful where people research during early generative AI adoption, when digital engagement opportunities still outnumber competitors. Test one post this quarter and see what converts.
Three months after that budget meeting, you run the same test. Your CMO types the query into ChatGPT, Perplexity, and Google’s AI Overview. This time your brand shows up in all three—not because you abandoned SEO, but because you designed content that generative engines can actually cite.
The eight-brand list? You’re on it now. Traffic from that keyword has started climbing back, and more importantly you can measure where your expertise appears in AI answers and adjust in real time.
GEO isn’t a replacement for the search work you’ve already built. It’s the next layer—making sure that when someone asks an AI engine your customer’s most important question, your knowledge is part of the answer. The rankings you fought for still matter. Now they show up where people look first.
