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How it works

How Restomend Makes Restaurants
Easier for AI to Recommend.

We identify the questions diners ask, evaluate the evidence around your restaurant, strengthen what AI can understand and verify, and measure how often you appear.

The Shift

Restaurant Discovery Is
Becoming a Conversation.

Ten open tabs became one sentence, typed to something that answers back.

Diners no longer have to open ten tabs, study several lists, and compare dozens of restaurants.

They can describe exactly what they want and ask AI for a recommendation.

What they actually type

  • “Best sushi restaurant near me”

  • “Best family-friendly Italian restaurant”

  • “Romantic restaurant with outdoor seating”

  • “Best tacos near downtown”

  • “Restaurant for a client dinner”

  • “Best gluten-free restaurant nearby”

The Moment

One Question Can Decide Which
Restaurants Get Considered.

The diner asks

“What is the best Italian restaurant in Chicago for an anniversary?”

If your restaurant is not included, the diner may never visit your website, inspect your menu, or see your advertising.

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The answer

  1. 01 Restaurant A Handmade pasta, quiet room, strong wine list.
  2. 02 Restaurant B Long-running trattoria, known for the tasting menu.
  3. 03 Restaurant C Neighbourhood favourite, easy to book midweek.
  4. 04 Where is your restaurant?

Mechanism

Recommendations Are Built
From Evidence—Not Luck.

Three things have to be true before your name is spoken aloud.

01

Understand

AI needs to know:

  • What the restaurant is
  • Where it is
  • What it serves
  • Who it is best for
  • Why it is different
02

Trust

AI looks for confirmation across:

  • Website
  • Menu
  • Listings
  • Reviews
  • Publications
  • Guides
  • Local sources
03

Recommend

The restaurant must then be:

  • Relevant
  • Credible
  • Accurately represented
  • Easy to choose

Restomend strengthens
every stage.

The RESTO Method™

Five Systems Behind a More
Recommendable Restaurant.

Each system ends in a document you keep, whatever happens next.

  1. R

    Recommendation Mapping

    We identify the dining questions that matter to your restaurant, and who is being recommended for them today.

    What it covers

    Cuisine, signature dish, neighbourhood, nearby landmarks, price range, occasion, atmosphere, group size, dietary needs, family friendliness, outdoor seating, late-night dining, and tourist versus local intent.

    You receive

    Restaurant Recommendation Demand Map

  2. E

    Experience and Entity Clarity

    We make the restaurant’s identity and experience unmistakable, and identical everywhere it is described.

    What it covers

    Name, address, phone, hours, cuisine and regional style, price range, signature dishes, chef and story, atmosphere, occasions, dietary options, accessibility, parking, takeout and delivery, reservation provider, menu URL and social profiles.

    You receive

    Restaurant Information Integrity Report

  3. S

    Source Authority

    We strengthen the credible third-⁠party evidence around the restaurant. Never by buying links or manufacturing consensus.

    What it covers

    Local and food publications, tourism organizations, neighbourhood guides, hotel concierge resources, culinary associations, relevant directories, venue and event partners, community organizations, and genuine guest reviews.

    You receive

    Restaurant Source and Authority Map

  4. T

    Technical Readability

    We make sure the information that matters can be read by diners, search engines and AI systems alike.

    What it covers

    Crawlable pages, HTML menus instead of PDFs, clear page hierarchy and internal links, restaurant structured data, accurate metadata, accessible images and text, sitemaps, location pages, clear reservation actions and mobile usability.

    You receive

    AI-Readable Restaurant Website Plan

  5. O

    Ongoing Observation and Optimization

    We re-⁠run the same questions on a schedule, compare, and act on what moved.

    What it covers

    Recommendation frequency, top-three inclusion, competitor appearances, supporting sources, incorrect information, how the restaurant is described, sentiment, reservation readiness and changes across platforms.

    You receive

    Restomend Recommendation Report

The prompt universe

We Test the Questions
Your Diners Actually Type.

Not one keyword. Dozens of intents, phrased the way people talk.

  • Cuisine

    “Best Oaxacan food in Barcelona”

  • Signature dish

    “Where to get real mole negro”

  • Neighbourhood

    “Good dinner spots in Gràcia”

  • Occasion

    “Somewhere special for an anniversary”

  • Dietary need

    “Vegetarian tasting menu near me”

  • Landmark

    “Dinner near Park Güell tonight”

  • Group size

    “Restaurant for twelve people Friday”

  • Atmosphere

    “Quiet, low-lit room for a first date”

Illustrative example, for a fictional restaurant in Barcelona.

Measurement

One Screenshot Is
Not a Strategy.

No mystery score. You see exactly what changed, and what it was measured against.

AI answers can change by platform, location, wording, date, conversation, and available information. Restomend measures repeated performance across a controlled set of restaurant questions.

Recommendation rate

Seven months of repeat testing on one controlled prompt set.

What gets reported

Recommendation Rate

18 / 75

How often the restaurant appears across the tested answers.

Top-Three Inclusion

31 %

How often it appears among the first three suggestions.

Competitor Share

2.4 ×

How frequently competitors appear by comparison.

Source Coverage

6

Which credible sources support the restaurant.

Information Accuracy

4 / 5

Whether public restaurant details are correct.

Reservation Readiness

3 / 4

Whether a diner can act on the recommendation.

Ethical standards

Recommended by
Evidence, Not Tricks.

Recommendations should be earned through accurate information, authentic reputation, strong guest experiences and credible third-party evidence. Anything else is a risk we won’t put on your name.

Restomend does not use

  • Fake reviews
  • Purchased reviews
  • Review gating
  • Scripted customer testimonials
  • Fabricated awards
  • Fake publications
  • Spam directories
  • Bought links or placements
  • Mass-produced low-quality articles
  • Misleading structured data
  • Guaranteed recommendation claims
  • Claims of controlling AI platforms

Timeline

What Happens During
the First 90 Days?

No mystery phase. You can see the whole ninety from day one.

  1. Days 1–10

    Establish the Baseline

    • Prompt testing
    • Competitor mapping
    • Source analysis
    • Information audit
    • Website review
    • Menu review
    • Reservation-path audit
  2. Days 11–30

    Fix the Foundation

    • Information corrections
    • Category alignment
    • Website improvements
    • Menu improvements
    • Structured-data corrections
    • Reservation improvements
  3. Days 31–60

    Strengthen the Evidence

    • Reputation system
    • Source-development work
    • Local authority opportunities
    • Restaurant content
    • Third-party profile optimization
  4. Days 61–90

    Measure and Improve

    • Repeat testing
    • Recommendation comparison
    • Competitor analysis
    • Source analysis
    • Accuracy review
    • Next-quarter roadmap

Your team provides access, restaurant context, and approvals. Restomend handles the execution.

FAQs

Questions About
the Method.

The short answers. The long ones are on the FAQ page.

All Questions
Why do AI answers change?

They vary by platform, location, wording, date, the rest of the conversation, and what information is available at that moment. That is precisely why we test a controlled prompt set repeatedly instead of taking one screenshot.

Which AI platforms do you monitor?

The mainstream consumer assistants and AI search surfaces your diners actually use. The exact set is agreed at the start of the engagement and named in every report, along with the dates tested.

How quickly can results change?

Information corrections can surface within weeks. Source authority takes longer, because it depends on other people publishing. Ninety days is enough to establish a baseline, fix the foundations, and measure again.

Does traditional local SEO still matter?

Yes. Listings, maps data, reviews and a readable website are among the sources assistants draw on. We build on that work rather than replace it.

AI Is Already Recommending
Restaurants in Your City.

Is yours one of them?

See how often your restaurant appears, which competitors are being selected, and what may be holding your recommendation visibility back.

Free restaurant AI snapshot. No credit card. No obligation. See a sample snapshot

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