When someone asks ChatGPT, Gemini, or Perplexity to compare options and make a recommendation, the AI synthesizes an answer from whatever it understands about the market — and either includes your brand accurately, or leaves it out entirely.
A rough, directional estimate — not a quote — since no generative engine publishes official visibility metrics. Adjust entity consistency and content coverage to see how readiness shifts.
Generative AI systems increasingly act as the first filter in buying decisions — recommending vendors, comparing products, and summarizing markets before a person ever visits a website. If a model's training data and retrieved content don't represent your brand clearly and favorably, you're excluded from that recommendation by default.
AI recommends vendors, compares products, and summarizes markets before a person ever visits a website.
If a model's data doesn't represent your brand clearly and favorably, you're left out of the recommendation.
GEO makes sure the content a model draws from is accurate, well-structured, and genuinely representative.
When the source content is right, the synthesized answer includes you fairly — not left to chance.
We offer both because they solve different problems. AEO optimizes specific pages to be the cited source for a direct factual answer. GEO is broader — it's about how your brand as a whole gets understood, represented, and recommended across generative AI outputs, including comparisons and summaries where no single page is "the answer."
| Focus | AEO | GEO |
|---|---|---|
| Scope | Individual pages and direct answers | Brand-wide entity and content ecosystem |
| Goal | Get cited as the source | Get included and represented accurately |
| Content type | Definitions, FAQs, how-tos | Comparisons, reviews, category content, brand mentions |
| Success looks like | A direct citation in an answer | Accurate inclusion in recommendations and summaries |
Category comparison prompts drive a large share of buying decisions — models need to describe what you build and who it's for, accurately and consistently.
Firms are recommended by name. Consistent descriptions across directories, review sites, and press decide whether models name you.
Accuracy is non-negotiable — outdated or inconsistent claims get corrected and reinforced so models represent you correctly.
Comparison and review content determines whether AI recommends your storefront over competitors in "best of" answers.
Trust signals and consistent entity presence decide whether models describe you favorably in recommendations.
Consistent entity presence across every location and directory prevents confusion and incorrect recommendations.
At scale, sub-brand ambiguity hurts representation — entity clarity matters even more when your structure is complex.
Running real comparison and recommendation prompts across major engines to baseline current representation.
Prompt testing across major engines to baseline current representation.
Entity consistency review and comparison & category content build-out.
Review sites, directories, and industry publications strengthened and aligned.
Recurring prompt testing tracks inclusion, sentiment, and accuracy over time.
Pricing depends on category competitiveness, current entity consistency, content volume needed, and whether ongoing multi-engine monitoring is included.
Request a Custom Proposal| Factor | Why it drives your quote |
|---|---|
| Category competitiveness | Harder categories need more comparison and category content. |
| Entity consistency | More inconsistencies mean more correction and alignment work. |
| Content volume | More pages and comparison content mean more build time. |
| Multi-engine monitoring | Ongoing prompt testing across engines adds recurring scope. |
GEO builds on top of solid technical SEO and works alongside AEO — most brands benefit from running both.
| Traditional SEO | GEO |
|---|---|
| Optimizes for ranking position | Optimizes for accurate inclusion in AI-generated recommendations |
| Success measured by clicks and rankings | Success measured by representation and sentiment across engines |
| Page-level optimization | Brand and entity-level optimization |
| Competes on the search results page | Competes to be part of the synthesized recommendation |
Full write-ups, budgets, and before/after numbers live on our case studies page — a few highlights below.
"We had no idea ChatGPT was describing us with outdated pricing until the audit surfaced it — that alone was worth the engagement."
Aisha Khan — E-commerceDubai, UAE"We started showing up in 'best of' comparisons generated by AI tools that we'd never appeared in before."
Marcus Webb — SaaSChicago, IL"The entity consistency work fixed inconsistencies across our own site we hadn't even noticed ourselves."
Emily Carter — Professional ServicesAustin, TXGEO is the practice of optimizing your brand's entity presence and content so generative AI systems like ChatGPT, Gemini, and Perplexity understand, represent, and include you accurately in comparisons, recommendations, and summaries.
AEO focuses on individual pages becoming the cited source for a direct factual answer. GEO is broader, focusing on how your brand as a whole is represented and recommended across generative AI outputs, including comparisons where no single page is the answer.
No. No agency can guarantee inclusion, since generative engines don't publish official visibility metrics and outputs vary by prompt and over time. We focus on the entity consistency, content, and trust signals that correlate with accurate, favorable representation.
GEO works best on a solid technical and on-page SEO foundation, and pairs naturally with AEO. If your site has significant technical issues, we typically recommend addressing those in parallel.
We run structured comparison and recommendation prompts across major generative engines before and after work begins, track entity consistency and content coverage improvements, and monitor sentiment and accuracy over time.
This is common and a core part of what a GEO audit surfaces. We identify where inaccurate or outdated information is likely coming from and work to correct it across your site and third-party sources.
Yes. Entity clarity becomes more important at scale, where multiple product lines or sub-brands can create ambiguity for AI systems trying to understand who you are.
Whether you're starting GEO from scratch or want to know why competitors keep showing up in AI comparisons and you don't, we'll show you exactly where the gap is.