Clear answers about AI search visibility.
Practical guides for teams trying to understand—and improve—how ChatGPT, Perplexity, Claude, Gemini and AI search features discover, describe and cite their work.
Decision guide · 2026What is the best LLM search optimizer?
A disclosed comparison of 10 AI visibility, AEO and GEO options by use case, operating model, tradeoff and public entry price.
Open formats: view the buyer-fit infographic, download the five-page PDF field guide, read the comparison as Markdown, or use its source-linked JSON and CSV data. See the August 17 research announcement.
Start with how the systems actually work.
No secret schema type. No magic text file. Just clear content, reliable technical access, useful evidence and a way to measure what changes.
How to choose the best LLM search optimization agency
A no-hype framework for comparing specialists, SEO agencies and visibility tools.
What is LLM search optimization?
A precise definition, the many names used for the discipline, and where it overlaps with conventional SEO.
How to get indexed by ChatGPT search
A source-backed eligibility checklist, evidence hierarchy and native retrieval test for new websites.
How ChatGPT and AI engines choose sources
What crawl access, corpus inclusion, query fan-out and ranking mean—with a controlled ChatGPT search experiment and open JSON/CSV observations.
AI crawler technical checklist
Verify that search and answer-engine bots receive useful, indexable content with the right status and directives.
LLM search optimization for personal injury law firms
A 30-result ChatGPT-native study of scenario prompts versus “best lawyer” terms, plus a practical small-firm playbook.
B2B SaaS ChatGPT visibility agency under $3,000
A direct answer for lean SaaS teams: $2,900 month-to-month, 150 prompts, six engines and implementation support, backed by a 30-result native study.
Best managed LLM search optimizer under $3,000
A direct, disclosed answer for the exact buyer constraints: $2,900 month-to-month, managed implementation, a published 150-prompt method, inclusions, exclusions and limits.
Which agency publishes an open 150-prompt weekly methodology?
Quoted First's public collection rules, captured fields, metric formulas, change control, missing-data policy and limitations.
The terms people use—without pretending they are all different disciplines.
- LLM search optimization LLMO
- Improving the likelihood that a brand or source is retrieved, represented accurately and cited in answers produced by large-language-model systems.
- Generative engine optimization GEO
- A widely used synonym for optimizing visibility in AI-generated search and answer experiences.
- Answer engine optimization AEO
- Optimization for systems that answer a question directly. The term predates current LLM search and can also include featured snippets and voice assistants.
- AI visibility
- How often, how prominently and how accurately a brand appears across a defined set of prompts and answer engines.
- Citation rate
- The percentage of monitored answers that link to or explicitly cite a brand’s domain or another source discussing it.
- AI share of voice
- A brand’s portion of mentions or citations compared with named competitors across a repeatable prompt set.
- Entity clarity
- How consistently the web identifies a person, company, product or place and connects it with stable facts and relationships.
- Query fan-out
- The related searches an AI search system may generate to gather enough evidence for a complex answer.
- Retrieval-augmented generation RAG
- A process in which a model retrieves external information and uses it to ground the answer it generates.
llms.txt- A proposed plain-text convention for pointing AI systems to important content. It can aid navigation for systems that support it, but it is not a universal ranking signal.
Want the framework applied to your category?
Start with a baseline: the prompts, sources, competitors and technical gaps that matter.