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Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦Modern websites, ranked in AI search✦Cited by ChatGPT, Perplexity & Google AI Overviews✦32% of our own traffic comes from AI search✦
AI Search Visibility

When your customers ask ChatGPT, does it say your name?

A systematic plan to get your business mentioned by name when ChatGPT, Perplexity, Claude, and Google AI Overviews answer the questions buyers in your area are actually asking.

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The challenge
Your customers are asking ChatGPT direct questions. "Best dentist in north Toronto that does Invisalign." "Who can install a new kitchen in Burlington under 8 weeks." "Real estate agent in Westboro for first-time buyers." The model answers with names. The names that come up are the businesses whose sites the engine could actually read and trust. Those businesses did not show up by accident. They have content the retrieval layer can parse, schema that nails the entity, and consistency across the directories the engines pull from. Most local businesses have none of this. Their site was built for traditional Google search in 2019 and the AI engines walk past it.
How we solve it
LLM citation work is folded into Engine builds and runs every month on the Growth and Authority retainers. We map the specific questions your buyers ask AI engines for each stage of the journey (research, comparison, decision), then our strategists run those queries weekly across ChatGPT, Perplexity, Claude, Gemini, OpenAI search, and Google AI Overviews. We see what sources currently get cited, including which competitor sites the engines like and why. Then we ship the content: definitional first paragraphs, FAQPage schema on the buyer questions, comparison content that beats the competitor sources, Reddit and Wikipedia seeding on Authority, and citation-friendly structural patterns the retrieval layer prefers. We measure results monthly and iterate based on what the engines actually do, not what we hope they do, with monthly AI-traffic tracking on cite-met.com showing which AI crawlers read your pages.

Key benefits

Cited by name, not described

When an AI assistant answers a buyer question in your category, it says your business name. It does not wave at "a local provider" and leave you out.

You show up at the buying moment

We go after the queries that signal someone is ready to buy, so your name lands at the point in the AI-assisted search where the decision gets made.

Both ways a model can cite you

We cover the two paths to a citation: what the model learned in training (parametric) and what it pulls from a live search (retrieval). Miss one and you miss half the queries.

Our process

  1. 01

    Citation Intent Mapping

    We list the buyer questions where an AI citation sways the decision, and note who gets cited for each one today.

  2. 02

    Citation Content Architecture

    We build the content the retrieval layer likes to quote: a clear definition, a comparison the model can lift, and claims that point to a source.

  3. 03

    Training Data Influence

    We grow your presence on the high-authority sources the LLMs train on, so your brand is in the model before it ever runs a search.

  4. 04

    Retrieval Optimization

    We tune your site for the crawlers and indexes that feed live AI search, so the engine can fetch and read you in real time.

  5. 05

    Citation Tracking & Expansion

    We watch your citations across the major LLMs, measure your share against competitors, and move into the next set of queries.

Proof you can check

4 → 30

pages for Starlit Homes, a NetZero builder whose self-built site became a page per model plus a building-science blog.

Read the case study

6 → 190+

pages for Zebra Home Cinema, rebuilt from a 6-page WordPress site with 22 city pages and 96 posts.

Read the case study

90 days

for Lotso Travel's blog to rank one slot under Rogers and Telus on Canadian roaming-versus-eSIM searches.

Read the case study

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Related insights

AEO & AI Search

How to Get Cited by ChatGPT, Gemini, and Perplexity: The Technical Playbook

Agentic AI

RAG for AI Agents: Retrieval-Augmented Generation Done Right

Explore related solutions

Answer Engine Optimization

Answer Engine Optimization is the actual technical work that gets your business mentioned by name when ChatGPT, Perplexity, Claude, and Google AI Overviews answer the questions your customers ask.

Structured Data Automation

Schema markup is the translation layer between your content and ChatGPT, Perplexity, Claude, and Google AI Overviews. We bake it in at the template level so every new page ships with the right structured data automatically.

AI Overview Optimization

For a growing chunk of search queries, Google answers directly at the top of the page now. The blue links sit underneath. We make sure your business is one of the sources the summary actually pulls from.

Industries that ship this

Accountants and CPAs

Accounting firms sites with AccountingService schema.

Real Estate

Real estate agents and developers sites with RealEstateAgent schema.

Custom AV Installers

AV installers sites with LocalBusiness schema.

Want to verify?

Industry sources we cite.

3 links · External

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