SEO, GEO & AIO: AI Visibility for Restaurants

Local pack optimization

1. Start from the real searches and AI prompts customers actually use to find restaurants. Most SEO advice guesses at what people type. Sitework works from real data instead: the keyword searches actually driving traffic in your trade, and the actual prompts real users enter into ChatGPT, Gemini, and Perplexity when they're looking for restaurants, including which brands those tools name in response today. That last part is the leverage. Once you can see a competitor being cited for a specific prompt, and why, your plan tells you exactly what to publish to answer that prompt better, so your business is the one named the next time someone asks.
2. Add Menu schema markup so your dishes become machine-readable data, not just pictures. Schema markup is structured code embedded in your page that tells search engines exactly what something is, rather than making them infer it from surrounding text. There is a dedicated Menu schema type for restaurants that lets you label each dish, its price, and its dietary attributes as discrete data fields. A menu trapped in a PDF or a photo is invisible to this system entirely. Once marked up properly, a search for a specific dish or dietary need can surface your restaurant directly, and AI tools can quote your actual menu instead of guessing what you serve.
3. Choose a cuisine-specific primary category, then layer secondary categories for proximity ranking. Google's local pack, the three-business map result at the top of a local search, ranks on three factors: relevance, distance, and prominence. Your primary Google Business Profile category is the single strongest relevance lever you control. “Restaurant” competes against every food business in your radius; “Neapolitan Pizza Restaurant” competes against a handful. Secondary categories for takeout, delivery, or catering then capture separate search intents without diluting your primary signal.
4. Build occasion pages that match informational search intent, not just transactional. Search intent is the underlying goal behind a query. “Pizza near me” is transactional, someone ready to order now. “Best date night restaurants in [neighborhood]” is informational, someone still deciding. Most restaurant sites only serve the transactional query, which is also the most competitive. Occasion and neighborhood pages capture the informational search that happens earlier, when there is less competition and the diner has not yet chosen a competitor.
5. Build review velocity, not just review volume. Review velocity is the rate at which new reviews arrive over time, and Google weighs it separately from your total count. A restaurant with 40 reviews all posted in one burst two years ago signals less active prominence than one earning six fresh reviews a month. This is why a steady, systematic ask, timed to when the check closes and the experience is still fresh, outperforms an occasional bulk push, both for local pack ranking and for how current your reputation looks to a diner comparing options.
6. Establish consistent entity signals so AI tools cite you confidently. An entity is how search engines and AI models represent your restaurant as a distinct real-world thing, a specific cuisine, at a specific location, with specific attributes, rather than as a page of words. When your site, Google Business Profile, delivery platform listings, and directory profiles all describe you consistently, models like ChatGPT and Gemini can name you with confidence. Conflicting descriptions across those sources are the most common reason a good restaurant gets skipped in an AI-generated recommendation.