27 articles
AI search & local SEO
Being found and quoted by assistants, maps, and search.
- How Restaurants Show Up in AI Search ResultsAI assistants answer 'where should I order from' using what's verifiably known about you. What AI search reads, what you can influence, and what nobody knows.
- What Is Answer Engine Optimization for Restaurants?Answer engine optimization means giving AI assistants and search summaries accurate, structured facts about your restaurant. What it covers, what it does not.
- What to do when a review complains about your AI phoneA one-star review that names your phone system gets read more carefully than the four-star ones around it. Here's how to answer it and what to fix behind it.
- How your reviews end up quoted in assistant answersAssistants summarize review text, not star ratings. What that changes about which reviews matter, how to respond, and the sentences you do not want repeated.
- Isolating ChatGPT and Perplexity referrals in GA4Assistant traffic hides inside GA4's Referral bucket and gets undercounted. How to build a channel group for it, and what the number can and cannot tell you.
- Location pages, locators, and duplicate content trapsMulti-unit restaurants lose local search to their own store locator. What a location page needs, what to never copy between them, and how to test it.
- Which restaurant directories still matter, and which don'tA few listings carry nearly all the weight, aggregators feed everything else, and the rest is noise. How to sort them, and the check that keeps them right.
- Why a PDF menu is a dead end for restaurant SEOA PDF menu costs you search traffic and gives assistants nothing to quote. Here is what an HTML menu page should publish instead, section by section.
- Write your restaurant pages to answer in the first sentenceModels and hurried customers both read the top of a page and stop. How to rewrite restaurant pages so the answer arrives first and the story comes after it.
- Why search stores your restaurant as a string, not a thingSearch engines either hold your restaurant as one business or as several near-matching records. How that split happens, what it costs you, and how to repair it.
- What Siri and Alexa can really do with your restaurant lineAssistants rarely place restaurant orders. They find a listing and dial. What that means for your listing data, your phone line, and a caller who has no screen.
- Near-me voice searches usually end at your phone lineA spoken near-me query resolves to a short list, then a call button. What decides whether you make the list, and what a caller hears right after they tap it.
- Apple Business Connect is the listing restaurants forgetEvery iPhone that asks Siri for a place to eat reads Apple's map data, not Google's. Claiming that record takes an afternoon and most restaurants never do it.
- Bing Places matters more than Bing's traffic share suggestsAlmost nobody searches Bing directly for dinner. Plenty of software reads its business data anyway, which is why a free listing you ignore is worth an hour.
- NAP consistency for restaurants, and what forwarding breaksYour name, address, and phone number appear in forty places online. When the number stops matching, search engines and callers both start losing track of you.
- The Google Business Profile fields that make your phone ringA few fields on your Google listing decide how many people tap call instead of scrolling past. Which ones move call volume, and which ones waste an afternoon.
- Review schema for restaurants and the self-serving review trapYou cannot mark your way into star ratings in search results. Here is what review schema legitimately does for a restaurant, and what it gets you penalized for.
- FAQ schema for restaurant pages after the rich-result cutsGoogle stopped showing FAQ rich results for almost everyone. FAQ markup on a restaurant site still pays off, for reasons unrelated to blue links.
- Getting Restaurant and LocalBusiness Schema RightRestaurant is a subtype of LocalBusiness, and using the wrong one costs you detail. The fields that change answers, and the ones that quietly cause errors.
- Should You Block GPTBot and ClaudeBot From Your Site?AI crawlers read restaurant sites for two different reasons, and robots.txt treats them separately. What blocking costs a restaurant, and when it makes sense.
- Menu Schema Markup That Is Actually Worth the EffortFull item-level menu schema is a maintenance burden most restaurants abandon. Which parts of the markup earn their keep, and which ones you can skip.
- Should Your Restaurant Have an llms.txt File?llms.txt is a proposed convention, not a standard anyone is obligated to read. What it is, what belongs in one for a restaurant, and why it changes little.
- Why Copilot's Restaurant Answers Are Really Bing AnswersCopilot answers local dining questions out of Bing's index and Bing Places. That makes it the cheapest AI visibility work you can do, and the least glamorous.
- What Gemini Pulls From to Answer Restaurant QuestionsGemini leans on Google's own local data long before it reads your site. Here is the order it seems to work in, and the three things you can actually fix.
- How Google AI Overviews build restaurant answersAI Overviews summarize pages Google already ranked, plus your Business Profile. That makes the fix boring, specific and mostly about facts you already have.
- What Perplexity cites for restaurant queriesPerplexity shows its sources, which makes it the easiest place to see why your restaurant does or does not get mentioned. Run the query and read the citations.
- How to appear in ChatGPT restaurant recommendationsAssistants recommend restaurants by reading pages other people wrote about you. Here is what that means for your site, your listings and your menu.
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