Generative engine optimization, measured.
GEO audits for service businesses, on five named AI engines
Find out who AI recommends when customers need what you offer.
Generative engine optimization is the work of improving how AI-written answers describe your business. It starts with knowing what the engines say about you today, question by question.
Vector Index AI examines the answers across ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews. You get a written report showing where your business appears, how it's described, and which changes deserve your attention. This work is called answer engine optimization (AEO) or generative engine optimization (GEO). You may also have seen it called AI search optimization, AI search visibility, LLM visibility, or an AI SEO audit. The measurement is what we sell.
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"Up to 40%" is 7.9 percentage points.
The authors released their benchmark results, including a baseline where each source was left unchanged. Each answer drew on five sources, so a source with no advantage would take about 20% of it. Unchanged sources took 19.4%.
The best method, adding quotations, took 27.3%. That is 7.9 percentage points, or 40.6% relative to the baseline, which is where "up to 40%" comes from. The same method made the result worse on 28% of queries.
Source. The GEO-bench leaderboard released with the paper · 989 queries with results for every method, 110 empty rows excluded · share of the generated answer as the authors' own measure scores it · the answering engine is not labelled in the file · re-derived by Vector Index AI.
Understand the gaps. Know what to work on next.
Your report turns the findings into practical priorities for your website and business information.
See where your business appears.
Find out which questions bring up your business, where it's absent, and which competitors get named.
Check how AI describes you.
Identify incorrect details, missing information, or confusion with another business.
Get clear recommendations.
Receive prioritized changes with supporting evidence, suggested wording, and instructions you can hand to your web provider.
Each recommendation explains the finding behind it and distinguishes a supported correction from a change worth testing.
Looking up your company by name tells you very little.
In one audit, the business's main site was cited 411 times. On the questions that describe a buyer's need without naming anyone, the same site was cited 8 times across 292 answers.
An engine can build its answer out of your pages and still recommend someone else. Both matter, and they are different findings, so a report that covers only one of them is answering half the question.
That's the level of detail you can expect: what was found, why it matters, and what to do next.
Source. Anonymized finding from a practice audit delivered at no charge in September 2026. The counts are the report's own. Why the difference matters.
What is generative engine optimization?
Generative engine optimization, or GEO, is the work of improving how a business appears in answers written by generative AI systems such as ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews. The name comes from a research paper, and that paper's headline number is the most repeated figure in the field.
Where the term comes from
"GEO: Generative Engine Optimization", by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, was first posted in November 2023 and accepted to KDD 2024. It introduced GEO-bench, a benchmark of user queries across several domains with web sources to answer them, and reported that GEO "can boost visibility by up to 40% in generative engine responses". The paper.
The same aim is also called answer engine optimization (AEO), LLM optimization and AI search optimization.
How the top methods were produced
Every answer in the benchmark was written from five sources. When we put 16 buying questions about Cincinnati businesses to ChatGPT, Gemini and Perplexity through their APIs on 24 and 25 August 2026, each ChatGPT answer cited between 3 and 11 sources, each Gemini answer between 4 and 14, and each Perplexity answer between 15 and 20.
The code that rewrote the sources is public. Three of the four highest-scoring methods were instructions to fabricate. Adding quotations: "Add more quotes in the source, even though fake and artificial." Citing sources: "You may invent these sources but ensure they sound plausible". Adding statistics: "Add positive, compelling statistics (even if hypothetical)". The released code.
We do not recommend any of them. A business that published invented quotes, sources or statistics would be making false claims about itself, whatever an answer engine did with them.
What GEO work looks like without the shortcuts
For Google's AI features, Google says: "There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary." Google's documentation.
The rest is ordinary and checkable. Find out what each engine says about a business for the questions its buyers ask. Separate being mentioned, being cited and being recommended. Correct the facts and pages the answers rely on. Then ask the same questions again on the same engines. In our own review of the published research, we found no controlled before-and-after test on a live engine, so every recommendation should trace back to a stored answer rather than to a borrowed percentage.
Choosing a generative engine optimization agency
The same questions are worth asking whether the seller calls itself a GEO agency, sells generative engine optimization services or GEO optimization services, trades as an answer engine optimization agency, or offers AI search optimization. Which engines, by name? The API or the consumer app? How many times is each question asked? Who picks the questions? What is actually delivered? The label matters less than the scope behind it.
AEO vs SEO vs GEO · AEO vs GEO: what differs · What an audit should contain · How we measure · Our scope and prices
Built around how your customers choose.
- You provide the business context. Tell us about your services, customers, and market.
- We build the question set around your market. We write the questions your buyers actually bring to AI about your trade, your services and the firms you come up against, and we select them independently so the set can't be steered toward the ones you already win. Each is asked repeatedly across five named engines, then we read every answer against your site and the sources it cited.
- You receive your findings and priorities. Your written report arrives within five business days of submitting your intake form. You or your web provider carry out the recommended website changes.
After 90 days, we recheck five of the original questions and report what changed.
Pay, then one short intake form. Full refund until you submit it.
What the audit buys
Written for your market and chosen independently, so the set can't be steered toward the ones you already win.
Every question asked repeatedly across five named engines, with the engine, model, settings, date and every failed attempt recorded.
Read closely, along with every source the answers cited, so each finding points at something you can open yourself.
What the engines state about you, where you were named and where you weren't, which competitors hold the answers you want, and prioritized changes with the wording you'd need to act on them.
Your questions answered after delivery, so you are not left alone with the report.
We re-run your questions on the same engines after the work is done and report what actually moved.
What people are saying.
Every review here comes from a business we have actually delivered an audit to. We publish them in the reviewer's own words, and we say plainly what the reviewer was given.
Vector Index AI was extremely helpful because it showed us that while our company does come up in AI searches when we are mentioned specifically (we thought our GEO presence was a lot stronger), once you deviated from a direct search by name and started asking more indirect questions about the services we provide, we were virtually nonexistent. They also provided us with clear insight into gaps in our GEO and how to fix them. I cannot recommend Vector Index AI highly enough.
Questions we get asked about this.
What does GEO stand for?
Generative engine optimization: improving how a business appears in answers written by generative AI systems such as ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews.
Who coined generative engine optimization?
The term comes from the paper "GEO: Generative Engine Optimization" by Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande, first posted in November 2023 and accepted to KDD 2024.
Does GEO really increase visibility by 40%?
In the paper's released benchmark results, the best method raised a source's share of the answer from 19.4% to 27.3%, a 40.6% relative gain, and made it worse on 28% of queries. It was measured on the paper's own benchmark.
How much does a GEO audit cost?
Our AI Shortlist Blueprint is $750, paid upfront, with no subscription and no retainer. A generative engine optimization audit and a GEO audit are the same thing here: one brand, one main site and one market, ending with prioritized changes you can act on yourself or hand to your web provider.
What is the difference between GEO and AEO?
Both describe the same aim. GEO comes from the research paper, and AEO names the same work after the answer engines. Neither is a formal standard.
Is GEO replacing SEO?
Google says there are no additional requirements to appear in AI Overviews or AI Mode. A page still has to be indexed and eligible to show in Search with a snippet, so search fundamentals still apply.
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