AEO for Restaurants: How to Get Your Restaurant Found by AI Search

Restaurant AEO (AI Engine Optimization) is the practice of optimizing your restaurant's website, menu pages, Google Business Profile, and food content so that AI search engines — ChatGPT, Perplexity, Google AI Overviews, and Apple Intelligence — recommend your restaurant when diners ask where to eat. When someone asks an AI "What is the best Thai restaurant near me?" or "Where can I get a great steak dinner in Chicago for under $100?" restaurant AEO is what determines whether your restaurant appears in that answer or gets passed over for a competitor. Unlike traditional restaurant SEO, which optimizes for search engine result pages and directory listings, restaurant AEO focuses on the specific signals that AI models use to evaluate, trust, and recommend dining establishments in conversational responses.

Why Restaurants Need AEO

The way people choose where to eat is undergoing a fundamental transformation. Instead of opening Yelp, scrolling through Google Maps, or reading a "best of" article, a growing number of diners are asking AI engines directly: "What is the best Italian restaurant in the West Village for a date night?" or "Where can I get authentic birria tacos in LA?" The AI responds with a curated, opinionated answer — naming specific restaurants, describing their signature dishes, citing review highlights, and noting price range and ambiance.

This shift is accelerating across every type of dining query. Diners are asking AI engines:

• "Best sushi restaurant near me" — AI names specific restaurants with signature rolls, omakase options, fish sourcing, and review highlights
• "Restaurants with outdoor seating downtown that are good for groups" — AI recommends restaurants matching multiple criteria simultaneously, citing patio capacity, group-friendly menus, and reservation availability
• "Where to eat gluten-free in Austin" — AI identifies restaurants with dedicated gluten-free menus, cross-contamination protocols, and celiac-friendly reviews
• "Romantic restaurant for anniversary dinner under $200" — AI recommends restaurants that match ambiance, price range, and occasion, citing tasting menus and intimate dining rooms
• "Best brunch spot with bottomless mimosas" — AI names restaurants with specific brunch offerings, weekend hours, and drink specials
• "Authentic Mexican food, not Tex-Mex" — AI differentiates based on cuisine authenticity signals, chef backgrounds, and review content that describes regional Mexican dishes

For restaurants, this shift is an enormous opportunity. Restaurant discovery is one of the highest-volume local search categories — "restaurants near me" is consistently among the most-searched queries on Google. When AI engines recommend your restaurant by name instead of showing a generic list, that recommendation carries extraordinary weight. Unlike Google Maps where you compete with every restaurant on a crowded map, an AI recommendation is personal and specific: "Saffron Kitchen is a family-owned Thai restaurant in East Austin known for their hand-pounded curry pastes and a 4.7-star rating across 620 Google reviews." The diner arrives pre-decided.

Restaurants that have optimized for AI search report that AI-referred diners arrive with higher intent and specific expectations. When an AI engine recommends your restaurant by name — describing your signature dish, your ambiance, and your price range — the guest has already chosen you before they walk through the door. That is the power of restaurant AEO.

The Restaurant AEO Framework: 7 Pillars

This framework covers the seven core areas that determine whether AI engines discover, evaluate, and recommend your restaurant. Each pillar reinforces the others — schema helps AI find you, menu content tells AI what you serve, reviews validate your quality, location data ensures geographic accuracy, food content establishes authority, event pages capture special occasion queries, and technical foundations ensure AI can access everything.

Pillar 1: Restaurant Schema Markup

Restaurant-specific schema is the foundation of restaurant AEO. While any business can use LocalBusiness schema, restaurants have access to specialized schema types that communicate dining-specific information to AI engines: cuisine type, menu items, opening hours, price range, service options, reservation availability, and dietary accommodations. These schema types give AI engines the structured, machine-readable data they need to confidently recommend your restaurant for specific dining queries.

The essential schema properties for restaurants:

• Restaurant @type — The core schema type for your establishment. More specific than LocalBusiness, it tells AI engines exactly what kind of business you are and unlocks restaurant-specific properties like servesCuisine, menu, and acceptsReservations.
• servesCuisine — The cuisine types your restaurant serves. Be specific: "Northern Thai," "Neapolitan Pizza," "Contemporary Japanese" rather than just "Asian" or "Italian." This is how AI engines match your restaurant to cuisine-specific queries.
• menu / hasMenu — A URL pointing to your structured menu page. AI engines follow this link to understand what you serve. If your menu is a PDF, the AI cannot read it — this property only works when it points to HTML content.
• openingHoursSpecification — Detailed hours for each day of the week, including different hours for lunch and dinner service, brunch hours, happy hour windows, and seasonal variations. Accurate hours prevent AI from recommending you when you are closed.
• priceRange — Use the dollar-sign convention ($, $$, $$$, $$$$) to signal your price tier. This is one of the most frequently filtered criteria in dining queries.
• acceptsReservations — Whether you take reservations and through which platform. Link to your OpenTable, Resy, or direct booking page so AI engines can direct diners to reserve immediately.
• aggregateRating — Your overall rating and review count. This is one of the most influential signals for AI recommendations, providing quick validation of quality.

Here is a comprehensive Restaurant schema template with all the properties AI engines prioritize:

{
  "@context": "https://schema.org",
  "@type": "Restaurant",
  "name": "Saffron Kitchen",
  "description": "Family-owned Northern Thai restaurant in East Austin serving hand-pounded curry pastes, charcoal-grilled meats, and regional dishes from Chiang Mai and Chiang Rai. All curries made from scratch daily.",
  "url": "https://www.saffronkitchenaustin.com",
  "logo": "https://www.saffronkitchenaustin.com/images/logo.png",
  "image": [
    "https://www.saffronkitchenaustin.com/images/restaurant-interior.jpg",
    "https://www.saffronkitchenaustin.com/images/khao-soi.jpg",
    "https://www.saffronkitchenaustin.com/images/patio-dining.jpg"
  ],
  "telephone": "+1-512-555-0847",
  "email": "hello@saffronkitchenaustin.com",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "2105 East 7th Street",
    "addressLocality": "Austin",
    "addressRegion": "TX",
    "postalCode": "78702",
    "addressCountry": "US"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 30.2612,
    "longitude": -97.7220
  },
  "servesCuisine": ["Northern Thai", "Thai"],
  "menu": "https://www.saffronkitchenaustin.com/menu",
  "hasMenu": {
    "@type": "Menu",
    "url": "https://www.saffronkitchenaustin.com/menu",
    "hasMenuSection": [
      {
        "@type": "MenuSection",
        "name": "Curries",
        "hasMenuItem": [
          {
            "@type": "MenuItem",
            "name": "Khao Soi",
            "description": "Northern Thai coconut curry with egg noodles, pickled mustard greens, crispy shallots, and your choice of chicken or tofu. Mildly spicy.",
            "offers": {
              "@type": "Offer",
              "price": "18.00",
              "priceCurrency": "USD"
            },
            "suitableForDiet": [
              "https://schema.org/GlutenFreeDiet"
            ]
          }
        ]
      }
    ]
  },
  "acceptsReservations": "True",
  "openingHoursSpecification": [
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Tuesday","Wednesday","Thursday"],
      "opens": "11:00",
      "closes": "21:00"
    },
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Friday","Saturday"],
      "opens": "11:00",
      "closes": "22:00"
    },
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": "Sunday",
      "opens": "10:00",
      "closes": "15:00",
      "description": "Brunch service only"
    }
  ],
  "priceRange": "$$",
  "paymentAccepted": "Cash, Credit Card",
  "currenciesAccepted": "USD",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.7",
    "reviewCount": "623",
    "bestRating": "5"
  },
  "areaServed": {
    "@type": "City",
    "name": "Austin, Texas"
  },
  "sameAs": [
    "https://www.yelp.com/biz/saffron-kitchen-austin",
    "https://www.tripadvisor.com/saffron-kitchen-austin",
    "https://www.instagram.com/saffronkitchenatx",
    "https://www.opentable.com/saffron-kitchen"
  ]
}

Use our free Schema Generator to build Restaurant schema without writing JSON by hand. Enter your restaurant details and copy the generated JSON-LD directly into your website.

Pillar 2: Menu Optimization for AI

Your menu is the most important content on your restaurant website — and how you present it determines whether AI engines can recommend you for specific dish and dietary queries. The number one mistake restaurants make is publishing their menu as a PDF or an image. AI engines cannot extract text from a PDF menu. A gorgeous, professionally designed PDF that looks beautiful on your website is completely invisible to ChatGPT, Perplexity, and Google AI Overviews. Your menu must be HTML text.

Essential menu optimization strategies:

• HTML text, never PDF — Every dish name, description, ingredient, and price must be real text on the page, not embedded in an image or document. This is non-negotiable for AI visibility. If you currently use a PDF menu, converting it to an HTML page is the single highest-impact change you can make.
• Clear category structure — Organize your menu with clear headings: Appetizers, Salads, Entrees, Pasta, Seafood, Steaks, Desserts, Beverages. Use HTML heading tags (h2, h3) so AI engines understand your menu hierarchy. This structure matches how diners query: "restaurants with good seafood near me" maps directly to your Seafood section.
• Descriptive dish names and descriptions — "Khao Soi" alone means nothing to most AI engines. "Khao Soi — Northern Thai coconut curry with egg noodles, pickled mustard greens, crispy shallots, and your choice of chicken or tofu" tells AI exactly what the dish is, what cuisine tradition it comes from, and what ingredients it contains.
• Dietary labels on every applicable item — Mark items as vegetarian, vegan, gluten-free, nut-free, dairy-free, halal, or kosher with consistent labels or icons with alt text. When someone asks "Where can I eat vegan in downtown Portland?" AI engines scan menu pages for dietary markers. A restaurant with 12 clearly labeled vegan dishes will be recommended over one that has vegan options but does not label them.
• Prices on every item — Always include prices. "Market price" and "ask your server" are invisible to AI engines and prevent your restaurant from matching price-range queries like "affordable sushi near me" or "upscale Italian restaurant for special occasion."
• Seasonal and special menus — If you have lunch, dinner, brunch, happy hour, or seasonal menus, create separate sections or pages for each. This captures time-specific queries like "best brunch spots" and "restaurants with happy hour specials near me."

Consider adding a brief paragraph at the top of your menu page describing your culinary approach: "Our menu features Northern Thai dishes prepared using traditional techniques — hand-pounded curry pastes, charcoal-grilled proteins, and ingredients sourced from local Texas farms and specialty Thai importers." This context helps AI engines understand your restaurant's identity beyond just a list of dishes.

Pillar 3: Review Ecosystem Strategy

Reviews are the most powerful trust signal for restaurant AI recommendations. AI engines do not just look at your star rating — they analyze the content of reviews, the platforms where reviews appear, how recently they were posted, and how you respond. A comprehensive review ecosystem strategy across multiple platforms dramatically increases your chances of being the restaurant AI recommends.

The key platforms for restaurant reviews:

• Google Business Profile — Your most important review platform. Google AI Overviews directly uses your Google reviews when generating restaurant recommendations. Aim for volume above all — 200+ reviews signals an established restaurant. Encourage guests to mention specific dishes, the occasion, and what made the experience memorable. A review that says "The khao soi was the best I have had outside of Thailand, perfect for our anniversary dinner" gives AI engines cuisine validation, dish specificity, and occasion context.
• Yelp — Still the dominant restaurant review platform in many markets, especially coastal US cities. AI engines like ChatGPT and Perplexity frequently cite Yelp data when making restaurant recommendations. Ensure your Yelp profile has current photos, accurate hours, and your full menu. Respond to reviews — both positive and negative — as response patterns are parsed as service quality signals.
• TripAdvisor — Critical for restaurants in tourist-heavy markets or near hotels and attractions. TripAdvisor reviews carry significant weight for "best restaurants in [city]" queries from travelers using AI engines. Keep your TripAdvisor profile updated with seasonal menus, current photos, and accurate information.
• OpenTable — Provides verified diner reviews from people who actually made and honored reservations. OpenTable reviews signal confirmed dining experiences, which AI engines weight as more trustworthy. If you use OpenTable for reservations, actively encourage post-meal reviews through the platform.

Review response strategy matters as much as review volume. Respond to every review within 24-48 hours. For positive reviews, thank the guest personally and reference their specific feedback. For negative reviews, acknowledge the issue, explain what you are doing to address it, and invite the guest to return. Never be defensive or dismissive. AI engines parse your response pattern as a signal of how you treat guests — a restaurant that responds thoughtfully to every review, including critical ones, signals higher service standards.

Pillar 4: Location & Hours Content

Restaurant discovery is inherently local — virtually every dining query includes geographic intent, whether explicit ("restaurants in Williamsburg") or implied ("restaurants near me"). This makes local AEO a critical component of restaurant optimization. AI engines combine your structured data, Google Business Profile, review platforms, and website content to determine your location, hours, and service area.

Essential location and hours content:

• Google Business Profile optimization — This is the single most important local signal for AI restaurant recommendations. Ensure your profile includes accurate hours for every service (dine-in, takeout, delivery), current photos updated at least quarterly, your full menu linked from the menu section, all service attributes checked (outdoor seating, wheelchair accessible, Wi-Fi, parking), and regular Google Posts about seasonal menus, events, and specials.
• NAP consistency — Your restaurant Name, Address, and Phone number must be identical across every platform: your website, Google Business Profile, Yelp, TripAdvisor, OpenTable, DoorDash, Uber Eats, Instagram bio, and Facebook page. Even small inconsistencies — "St" vs. "Street," a different suite number, an old phone number on one platform — create trust issues for AI engines that cross-reference your information.
• Accurate and detailed hours — Include separate hours for different services: lunch service, dinner service, brunch hours, happy hour, late-night kitchen, and bar-only hours. Update hours immediately for holidays, seasonal changes, and special closures. Nothing damages trust with AI engines faster than recommending a restaurant that turns out to be closed when the diner arrives.
• Multiple location management — If you operate multiple locations, each needs its own Google Business Profile, its own page on your website with location-specific content, and its own schema markup. Never use a single generic page for all locations. Location-specific content like "Our East Austin location features a covered patio and live music on Friday nights" helps AI engines differentiate and recommend the right location.
• Neighborhood and landmark references — Reference your neighborhood, nearby landmarks, and cross streets on your website. "Located on East 7th Street in the heart of East Austin, two blocks from the Graffiti Park" helps AI engines match your restaurant to neighborhood-specific queries and provides context for visitors unfamiliar with the area.

Pillar 5: Food Content That AI Cites

Beyond your menu, publishing food-related content on your website creates the depth and authority signals that make AI engines trust your restaurant as an expert in your cuisine. This content serves double duty: it attracts food-curious visitors who may become diners, and it establishes your restaurant as a primary source that AI engines cite when answering food-related questions.

The types of food content that perform best for restaurant AEO:

• Chef profiles and culinary stories — A detailed chef profile that describes their training, culinary philosophy, and journey to your restaurant gives AI engines a rich narrative to cite. "Chef Niran spent 12 years cooking in Chiang Mai before bringing Northern Thai techniques to Austin" is the kind of specificity AI engines use to validate authenticity and recommend with confidence.
• Ingredient sourcing and philosophy — Content about where your ingredients come from, your relationships with local farms, your approach to seasonal cooking, or how you import specialty items. "We source our fish daily from the Gulf and our curry pastes use chilies imported from Northern Thailand" signals quality and care that AI engines pick up on.
• Dietary and allergen guides — Create dedicated pages for dietary accommodations: "Dining Gluten-Free at Saffron Kitchen," "Our Vegan Menu," "Nut Allergy Dining Guide." These pages directly match high-volume AI queries like "gluten-free restaurants near me" and "vegan-friendly Thai food." Detail your cross-contamination protocols, ingredient substitution options, and which menu items are naturally allergen-free.
• Cuisine education content — If you serve a cuisine that many diners are unfamiliar with, educational content like "A Guide to Northern Thai Cuisine" or "What Makes Neapolitan Pizza Different" positions your restaurant as the authoritative source on that cuisine in your market. When someone asks an AI "What is khao soi?" and your restaurant has the best explanation, you become the cited source and the recommended destination.
• Cooking tips and recipes — Sharing signature recipes or cooking techniques may seem counterintuitive, but it builds enormous authority. A restaurant that publishes "How We Make Our Hand-Pounded Curry Paste" demonstrates expertise that AI engines respect. The content gets cited when people ask about cooking techniques, and those same users become diners who want to taste the real thing.

Pillar 6: Event & Catering Pages

Private dining, catering, and special events represent a significant revenue stream for restaurants — and a major opportunity in AI search. Queries like "restaurants with private dining rooms near me," "catering for a corporate event in Austin," and "where to host a rehearsal dinner" are high-intent queries where AI engines actively seek specific recommendations. If your restaurant offers event services, dedicated pages with structured data will capture these queries.

Essential event and catering content:

• Private dining page — Describe each private or semi-private space: capacity, layout, audio-visual capabilities, minimum spend requirements, and photos. Include specific use cases: "Our Garden Room seats 30 for a seated dinner, ideal for rehearsal dinners, birthday celebrations, and corporate team dinners." This specificity helps AI engines match your space to event queries.
• Catering menu page — Publish a dedicated catering menu as HTML text with per-person pricing, minimum orders, service options (drop-off, full-service, buffet), and dietary accommodation capabilities. A structured catering page captures "catering near me" and cuisine-specific catering queries.
• Event schema markup — For recurring events like wine dinners, live music nights, and seasonal prix fixe menus, use Event schema to give AI engines structured access to your event calendar. This captures queries like "restaurants with live music tonight" and "wine dinner events near me."
• Holiday and seasonal event pages — Create pages for holiday offerings: Thanksgiving takeout menus, Valentine's Day prix fixe dinner, New Year's Eve celebration, Mother's Day brunch. These capture high-volume seasonal queries months in advance. Update annually — AI engines reward fresh content.

Here is an Event schema example for a recurring restaurant event:

{
  "@context": "https://schema.org",
  "@type": "FoodEvent",
  "name": "Friday Night Wine Dinner at Saffron Kitchen",
  "description": "Five-course Northern Thai tasting menu paired with natural wines from small-batch producers. Limited to 24 guests.",
  "startDate": "2026-03-06T19:00:00-06:00",
  "endDate": "2026-03-06T22:00:00-06:00",
  "location": {
    "@type": "Restaurant",
    "name": "Saffron Kitchen",
    "address": {
      "@type": "PostalAddress",
      "streetAddress": "2105 East 7th Street",
      "addressLocality": "Austin",
      "addressRegion": "TX",
      "postalCode": "78702"
    }
  },
  "offers": {
    "@type": "Offer",
    "price": "95.00",
    "priceCurrency": "USD",
    "availability": "https://schema.org/LimitedAvailability",
    "url": "https://www.saffronkitchenaustin.com/events/wine-dinner"
  },
  "organizer": {
    "@type": "Restaurant",
    "name": "Saffron Kitchen"
  }
}

Pillar 7: Technical Foundations

All your content optimization is wasted if AI engines cannot access and crawl your website efficiently. The technical foundation of your restaurant website determines whether AI crawlers can discover your schema, read your menu, and index your content. Many restaurant websites built on platforms like Squarespace, Wix, or WordPress with heavy themes have technical issues that prevent AI engines from accessing content properly.

Essential technical optimizations:

• robots.txt configuration — Ensure your robots.txt file allows AI crawlers to access your site. Many website platforms block certain crawlers by default. Check that Googlebot, GPTBot, PerplexityBot, and other AI crawlers are not blocked. Our robots.txt analyzer can check your configuration for free.
• llms.txt file — A llms.txt file is a plain-text file at your domain root that tells AI engines what your restaurant is and where to find key information. It includes a brief description, links to your menu, hours, reservation page, private dining information, and any other pages you want AI engines to prioritize.
• Fast mobile site — Most restaurant searches happen on mobile devices. Your website must load quickly on a phone — ideally under 3 seconds. Heavy image galleries, embedded video, and complex animations slow your site and cause AI crawlers to time out before indexing your content. Use compressed images and lazy loading.
• Image optimization — Restaurant websites are image-heavy, and rightfully so — beautiful food photography drives diners. But every image needs an alt tag describing the dish: "Khao Soi — Northern Thai coconut curry with egg noodles and crispy shallots" is an alt tag AI engines can read. Use modern image formats (WebP, AVIF) and appropriate sizing to keep page load times fast.
• Structured URLs — Use clean, readable URLs that describe your content: /menu, /private-dining, /catering, /about/chef-niran. Avoid auto-generated URLs with random strings or IDs that give AI engines no context about page content.

Cuisine-Specific AEO Strategies

Different cuisine types face unique AEO challenges and opportunities. Here are strategies for the most common restaurant categories.

Fine Dining & Upscale

Fine dining queries are occasion-driven — anniversary dinners, business entertaining, celebrations. Optimize for occasion-based queries by describing your ambiance, tasting menus, wine program, and private dining options in detail. Publish your wine list online with sommelier notes. Create content about your sourcing philosophy and chef's approach. Use priceRange "$$$$" in your schema to match diners with appropriate budgets. Include dress code and reservation policies prominently.

Casual & Family Dining

Casual dining queries focus on value, variety, and accommodations — "family-friendly restaurants," "restaurants with kids menus," "good lunch spots near me." Highlight your kids menu and family accommodations (high chairs, changing tables, kids eat free nights). Publish pricing prominently — "affordable" queries require visible prices. Create content around value propositions: lunch specials, happy hour menus, daily specials, and combo deals.

Ethnic & Regional Cuisine

Authenticity is the key signal for ethnic and regional cuisine queries. AI engines evaluate chef backgrounds, ingredient sourcing, cooking technique descriptions, and review content that validates authenticity. Publish your chef's culinary background and training extensively. Create educational content explaining your regional cuisine — what makes Sichuan different from Cantonese, what defines Oaxacan cooking, why Northern Thai food is distinct from Central Thai. Use specific cuisine descriptors in your schema: "Northern Thai" not just "Thai," "Neapolitan Pizza" not just "Italian."

Fast Casual & Quick Service

Speed, convenience, and ordering options dominate fast-casual queries. Emphasize your online ordering, delivery partners, drive-through availability, and mobile app in your schema and website. Publish your full menu with prices online — fast casual diners are price-sensitive and compare options before choosing. If you have multiple locations, each needs a dedicated page with location-specific hours, ordering links, and reviews.

Cafes, Bakeries & Coffee Shops

Cafe queries often include functional criteria — Wi-Fi availability, laptop-friendliness, outdoor seating, and hours. Include these attributes in your schema and website content. Publish your coffee sourcing, roasting partners, or baking process. Create content around specialties: "Our Guide to Pour-Over Coffee" or "Why We Use 48-Hour Sourdough Fermentation." If you serve breakfast or brunch, optimize for morning-specific queries with dedicated breakfast menu pages.

Delivery & Online Ordering Optimization

A significant portion of restaurant AI queries relate to delivery and takeout — "restaurants that deliver near me," "best Thai takeout," "late night food delivery." Optimize these signals:

• List delivery platforms in your schema — Include sameAs links to your DoorDash, Uber Eats, Grubhub, and direct ordering pages. AI engines use these to confirm delivery availability and direct users to order.
• Direct ordering page — If you offer direct online ordering, create a dedicated page with clear ordering instructions, delivery radius, minimum order, and estimated delivery times. Direct ordering pages capture diners who prefer ordering without third-party fees.
• Takeout-specific menu — If your takeout menu differs from your dine-in menu, publish it separately. Some dishes travel better than others — a curated takeout menu that notes "travels well" or "best enjoyed within 30 minutes" shows thoughtfulness that AI engines and diners appreciate.
• Service option attributes — In your Google Business Profile and schema, clearly indicate which service types you offer: dine-in, outdoor seating, takeout, delivery, curbside pickup, drive-through. Each attribute expands the range of queries your restaurant can match.

Free Tools to Get Started with Restaurant AEO

You do not need a large budget or a marketing agency to start optimizing for AI search. These free tools can help you assess and improve your restaurant's AI visibility today:

• Vida AEO Audit — Run a free AI readiness audit on your restaurant's website. Checks your Restaurant schema, menu accessibility, technical access, and 31 other AEO scoring factors. Takes 30 seconds and gives you a prioritized action plan specific to restaurants.
• Schema Generator — Build Restaurant, Menu, and FoodEvent schema types without writing code. Enter your restaurant details and copy the generated JSON-LD.
• FAQ Schema Generator — Create FAQPage schema for your restaurant FAQ section. Generates both the visible HTML and the JSON-LD schema markup.
• Robots.txt Analyzer — Check whether your website is blocking AI crawlers. Many restaurant website platforms block GPTBot and other AI crawlers by default without restaurant owners knowing.
• Google Business Profile — If you have not already claimed and optimized your Google Business Profile, do it immediately. It is free, and your profile data directly powers Google AI Overviews for local restaurant queries.