Tripadvisor Restaurant Reviews Scraper: Extract Restaurant Reviews for SEO and Local Research

Tripadvisor Restaurant Reviews Scraper is an Apify Actor that collects guest reviews from Tripadvisor restaurant pages. Paste one or more Restaurant_Review URLs and get structured review data: ratings, titles, body text, trip type, visitor details, category scores, photos, and owner replies when they exist.

This actor is built for SEO teams, local search work, reputation monitoring, and competitor research. Export results as JSON, CSV, Excel, XML, or HTML, or pull them through the Apify API into your own pipeline.

No proxy configuration is required.

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Why use this actor?

Tripadvisor is one of the main public sources of restaurant reputation signals. Manual copying does not scale when you track many locations, languages, or competitors.

With this actor you can:

• Collect Tripadvisor restaurant reviews in bulk from listing pages
• Keep star ratings plus Value / Service / Food / Atmosphere scores when shown
• Capture reviewer name, hometown, and contribution count
• Include owner or manager replies only when Tripadvisor actually shows one
• Cap how many reviews you collect per run with Max items
• Schedule runs on Apify for weekly or monthly monitoring

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What does Tripadvisor Restaurant Reviews Scraper do?

1. Accepts Tripadvisor restaurant URLs (Restaurant_Review-...)
2. Opens each reviews page and follows pagination (-or15-, -or30-, …)
3. Parses each review card on the page
4. Attaches restaurant metadata (name, address, cuisine, aggregate rating)
5. Adds ownerResponseText / ownerResponseDate only when a management reply is present
6. Pushes one dataset item per review

Invalid non-restaurant URLs are skipped with a warning.

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What data does this actor extract?

Each successful dataset row is one review.

Field	Type	Description
reviewId	string	Tripadvisor review id
reviewUrl	string	Direct link to the review
reviewTitle	string	Review headline
reviewText	string	Full review body
rating	integer	Overall bubble rating (1-5)
publishedDate	string	Written date shown on the page
visitDate	string	Visit / dining month when shown
tripType	string	Couples, Family, Friends, Solo, or Business
language	string	Detected language code when available
helpfulVotes	integer	Helpful vote count when shown
photoUrls	array	Photo URLs attached to the review
subratings	object	Category scores: value, service, food, atmosphere
username	string	Reviewer display name
userProfileUrl	string	Reviewer profile URL
userLocation	string	Reviewer hometown
userContributions	integer	Contribution count from the profile snippet
userAvatarUrl	string	Reviewer avatar image URL
ownerResponseText	string	Owner/manager reply text (only if a reply exists)
ownerResponseDate	string	Owner reply date (only if a reply exists)
restaurantName	string	Restaurant name
restaurantUrl	string	Restaurant page URL
restaurantLocationId	string	Tripadvisor geo id (g)
restaurantId	string	Tripadvisor restaurant id (d)
cuisine	string	Cuisine list when available
priceRange	string	Price range
aggregateRating	string	Overall restaurant score
restaurantReviewCount	string	Total reviews listed for the place
address	string	Restaurant address
scrapedAt	string	UTC collection timestamp
error	string	Present only when a URL fails

Owner reply fields

Not every Tripadvisor review has a management response.

• If the page includes an owner/manager reply, the actor returns ownerResponseText and ownerResponseDate.
• If there is no reply, those two fields are omitted from the item. They are not filled with null.

That keeps the dataset cleaner for SEO exports, spreadsheets, and API consumers.

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How to scrape Tripadvisor restaurant reviews

1. Open Tripadvisor Restaurant Reviews Scraper on Apify.
2. Paste one or more Tripadvisor Restaurant_Review URLs into Restaurant URLs.
3. Set Max items to control how many reviews are collected.
4. Optionally filter by language or minimum rating.
5. Click Start.
6. Download the dataset or call the Apify API when the run finishes.

Example input

{
    "startUrls": [
        "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html"
    ],
    "maxItems": 15,
    "language": "en",
    "minRating": 1,
    "requestTimeoutSecs": 60
}

Example output (no owner reply)

{
    "reviewId": "1071729054",
    "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g608676-d2062969-r1071729054-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html",
    "reviewTitle": "Very good",
    "reviewText": "Great food, very nice service!",
    "rating": 5,
    "publishedDate": "August 6, 2026",
    "visitDate": "Aug 2026",
    "tripType": "Couples",
    "language": "en",
    "helpfulVotes": 0,
    "photoUrls": [],
    "subratings": {
        "value": 5,
        "service": 5,
        "food": 5,
        "atmosphere": 5
    },
    "username": "Zsuzsanna K",
    "userProfileUrl": "https://www.tripadvisor.com/Profile/68zsuzsannak",
    "userLocation": "Budapest, Hungary",
    "userContributions": 1,
    "restaurantName": "Arlberger Dorfstubn",
    "restaurantUrl": "https://www.tripadvisor.com/Restaurant_Review-g608676-d2062969-Reviews-Arlberger_Dorfstubn-St_Anton_am_Arlberg_Tirol_Austrian_Alps.html",
    "restaurantLocationId": "608676",
    "restaurantId": "2062969",
    "cuisine": "Austrian, European",
    "aggregateRating": "3.8",
    "restaurantReviewCount": "217",
    "address": "Dorfstrasse 60, St. Anton am Arlberg, Austrian Alps, 6580, AT",
    "scrapedAt": "2026-09-13T12:00:00+00:00"
}

Example output (with owner reply)

{
    "reviewId": "991861538",
    "reviewTitle": "Great dinner",
    "reviewText": "Friendly staff and excellent local dishes.",
    "rating": 5,
    "username": "Traveler123",
    "restaurantName": "Example Restaurant",
    "ownerResponseText": "Thank you for dining with us. We look forward to welcoming you again.",
    "ownerResponseDate": "January 12, 2026",
    "scrapedAt": "2026-09-13T12:00:00+00:00"
}

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Input parameters

Field	Type	Required	Default	Description
startUrls	array of strings	yes		Tripadvisor restaurant review page URLs (Restaurant_Review)
maxItems	integer	no	15	Maximum reviews to collect in one run (1-1000)
language	string	no	empty	Optional language filter such as en or de
minRating	integer	no	empty	Keep reviews with this bubble rating or higher (1-5)
requestTimeoutSecs	integer	no	60	Per-request timeout in seconds (15-120)

URL requirements

Accepted:

https://www.tripadvisor.com/Restaurant_Review-gXXXXX-dYYYYY-Reviews-Name-City.html

Not accepted:

• Hotel review URLs (Hotel_Review)
• Attraction review URLs (Attraction_Review)
• Generic Tripadvisor search or city pages

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Pagination and limits

Tripadvisor restaurant review pages typically show 15 reviews at a time. The actor follows offset URLs such as:

• ...-Reviews-... (first page)
• ...-Reviews-or15-...
• ...-Reviews-or30-...

Collection stops when:

• maxItems is reached for the run, or
• no further review page is available

Use the default of 15 while testing. Raise maxItems once the output shape looks right.

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Use cases

• Local SEO: pull review themes, rating trends, and common phrases for restaurant landing pages
• Reputation monitoring: schedule runs and watch new Tripadvisor restaurant reviews over time
• Owner reply tracking: see which reviews received a management response and which did not
• Competitor research: compare nearby restaurants on food, service, value, and atmosphere
• Sentiment / NLP datasets: feed review text into classification or reporting tools
• Agency reporting: export client restaurant feedback without manual scraping

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Integrations

You can run this actor from:

• Apify Console (manual runs and schedules)
• Apify API / Apify client (Python, JavaScript, REST)
• Make, Zapier, n8n, or any webhook that can start an Actor run
• Downstream jobs that read the default dataset URL after the run finishes

Typical workflow:

1. Schedule the actor daily or weekly
2. Keep maxItems modest and filter by date in your own warehouse if needed
3. Append new reviews to a sheet, CRM, or SEO dashboard

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Best practices

• Start with 1 restaurant URL and maxItems: 15 to verify parsing
• Prefer full Restaurant_Review URLs, including the -Reviews- segment
• Use language only when you need a single language; leave it empty for mixed results
• Use minRating for complaint mining (1 or 2) or praise sampling (5)
• For large multi-location jobs, split URLs across runs to stay within maxItems

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FAQ

Does this work only for restaurants? Yes. Input URLs should be Tripadvisor Restaurant_Review pages. Hotel and attraction URLs are skipped.

Why are ownerResponseText and ownerResponseDate missing on some rows? Those fields are included only when Tripadvisor shows an owner or manager reply on that review. If there is no reply, the fields are left out on purpose instead of returning null.

Can I scrape multiple restaurants in one run? Yes. Add several URLs to startUrls. maxItems caps the total number of reviews saved.

How many reviews can I get per run? Up to 1000 total (maxItems). The default is 15. Practical volume also depends on how many reviews the restaurant actually has.

Do I need to set up proxies? No. Proxy setup is not required for this actor.

What export formats are supported? JSON, CSV, Excel, XML, and HTML from the Apify dataset UI, plus API access to dataset items.

Can I filter by language or rating? Yes. Use language and/or minRating in the input.

What happens if a page fails? The actor logs the error, pushes a small error item with restaurantUrl and error, and continues with the next URL.

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Related Tripadvisor tools

Pair this reviews scraper with other Tripadvisor actors from the same publisher:

• Tripadvisor Restaurant Listings Extractor: collect restaurant listing data
• Tripadvisor Hotels Extractor: collect hotel listing data

This actor focuses on restaurant review pages for SEO, reputation, and local research workflows.

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Output tips for SEO teams

• Track aggregateRating and restaurantReviewCount alongside individual reviews
• Use subratings to see whether complaints cluster on service, food, value, or atmosphere
• Keep reviewUrl for citation and verification
• Treat missing owner-reply fields as “no public response,” not as a scraper error

Tripadvisor Restaurant Reviews Scraper turns restaurant review pages into structured data you can sort, filter, and feed into SEO tools without copying Tripadvisor by hand.