How ChatGPT Selects Local Business Citations
When a ChatGPT user with browsing enabled asks "who is the best plumber in Austin" or "what HVAC company should I use in Denver," the model runs a web search, reviews the top results, and synthesizes an answer. The synthesis process weights:
Specific Facts Over Generic Content
"This HVAC company has 4.9 stars across 847 Google reviews and serves the greater Denver metro area" is more likely to be extracted than "we have great reviews and serve the Denver area."
Direct, Declarative Answers Over Hedged Language
Pages with direct, declarative answers over hedged or promotional language. The model is looking for information it can attribute confidently.
Structured Heading Hierarchies
Pages with structured heading hierarchies that match the question format. H2s phrased as questions give the model clear extraction points.
Entity Verification Signals
A business with a verified GBP, consistent NAP across directories, and high review count is more likely to be cited as a named entity than an unverified business.
The Content Difference Between Getting Cited and Getting Skipped
Consider two plumbing companies in Austin, both competing for the ChatGPT citation when a user asks "who does water heater replacement in Austin."
Company A
Company A has a service page with the headline "Water Heater Replacement" and two paragraphs of general copy: "We install all major brands of water heaters. Our licensed plumbers will assess your needs and recommend the best solution for your home. Call us for a free estimate."
Company B
Company B has a service page with an AEO nugget: "Water heater replacement in Austin typically takes three to four hours for a standard 40 to 50-gallon tank water heater, with total installed costs ranging from $900 to $1,800 depending on tank size, fuel type, and labor complexity. Tankless units cost $2,500 to $4,500 installed and qualify for a 30% federal tax credit under the Inflation Reduction Act." Below that, structured FAQ content covering cost, timeline, signs of failure, and warranty.
ChatGPT cites Company B. Not because Company B has better service, but because Company B's content is structured to be cited.
Perplexity AI and Other LLMs
Perplexity AI, the search-native LLM, operates on a similar content selection model as ChatGPT with browsing, it retrieves from the live index and synthesizes answers. Perplexity places slightly higher weight on recency (recently published or updated content) and source authority. The same AEO content structure that works for Google AI Overviews and ChatGPT works for Perplexity. The emerging LLM landscape. Google Gemini, Microsoft Copilot, Meta AI, all use similar retrieval-augmented generation approaches when answering local service queries. Building AEO-native content is not platform-specific optimization. It is a structural approach that works across all current and near-future AI retrieval systems.
SEO Local