AI Search Optimization for Local Business

AI search optimization works fundamentally differently from traditional Google ranking. Instead of competing on backlinks and keywords, you're competing on entity clarity and structured data parseability. Here's the playbook.

Step 1: Deploy llms.txt

A simple text file at yourdomain.com/llms.txt that tells AI assistants the canonical facts about your business. ChatGPT, Claude and Perplexity check for it. Includes: business name, address, phone, services, pricing, hours, and key differentiators in plain language.

Step 2: FAQ schema everywhere

AI assistants extract content from FAQ schema preferentially , it's structured, parseable, and quote-ready. Every page on your site should have FAQ schema for the questions relevant to that page.

Step 3: Entity consistency

Your business name, address and phone must match exactly across your website, Google Business Profile, Bing Places, social media, and all citations. AI models cross-reference these to verify your business exists and is the entity they should recommend.

Step 4: Specific data, not vague claims

"We've served 150+ clients across 50 states" outperforms "we're the best" in AI extraction. Models pull specific numbers, prices, timelines and proper nouns. Vague marketing copy gets ignored.

Step 5: Conversational content

AI users ask questions ("what's a good GMB expert in Houston?"). Your content should be findable when written in answer-form. We restructure key pages to lead with the question, then the answer, then the elaboration.