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Tripadvisor Restaurant Scraper for Detail Pages logo

Tripadvisor Restaurant Scraper for Detail Pages

This Tripadvisor restaurant scraper exports restaurant detail pages into a clean CSV for market research, local SEO audits, vendor discovery, and contact-data QA. Import the workflow into the UScraper local desktop app, replace the sample Tripadvisor restaurant URLs, and collect source URL, restaurant title, website, phone, email, address, and opening hours for every day of the week without writing a custom scraper.

Output

CSV

Columns

13

Input

Detail URLs

Waits

Built in

Template

Free

At a glance

Export Tripadvisor restaurant details to CSV

Use this template when you already have restaurant detail URLs and need a repeatable CSV export for contact fields, addresses, and weekly hours. For city or category discovery, collect candidate URLs first, then feed them into this detail workflow.

Restaurant contact data in one sheet

Export Tripadvisor restaurants to CSV with detail-page fields that are useful for local research: official website, phone number, email, address, and day-by-day hours.

Multi-URL detail loop

Replace the bundled Berlin restaurant URLs with your approved list and let UScraper visit each page, extract one row, and continue through the batch.

Local desktop execution

The template runs in your own browser session and writes the CSV to the folder configured inside Structured Export instead of routing output through a hosted scraping dashboard.

Built for real page variance

Tripadvisor may expose data through JSON-LD, visible page text, outbound links, or not at all. The workflow uses layered extraction so missing fields stay blank instead of breaking the whole export.

Who this is for

Tripadvisor data extractor use cases

Local SEO teams

Citation audits

Favorable to scraping

Compare restaurant names, phone numbers, websites, addresses, and hours against client records before fixing inconsistent listings across directories.

Hospitality researchers

Market mapping

Favorable to scraping

Build a controlled restaurant contact dataset for a city, cuisine cluster, or competitor set, then review the CSV before analysis or enrichment.

Agency operators

Batch QA

Nuanced outcome

Turn approved URL lists into spreadsheet rows for manual validation. Treat missing emails or websites as review flags, not scraping failures.

Pair this detail workflow with the Tripadvisor Restaurant Scraper for Listings when you need to collect restaurant URLs first. For adjacent travel datasets, compare it with the Tripadvisor Hotel Details Scraper, the Tripadvisor Review Scraper for Germany, and the full UScraper template library.


How to use

Configure the Tripadvisor restaurant scraper workflow

1

Download and import

Download the hosted JSON template and import it into UScraper.

2

Replace the sample URLs

Open the Navigate block and replace the bundled restaurant detail URLs with your own approved Tripadvisor restaurant pages.

3

Confirm the export path

Structured Export writes tripadvisor-restaurant-scraper-detail.csv with headers enabled and append mode on. Change the save folder before client-specific runs.

4

Run the loop

UScraper loads each URL, waits for the page, checks for CAPTCHA markup, gives you a short manual-solve pause when needed, extracts structured fields, and advances to the next input.

5

Open and validate

Review several source URLs, confirm hours formatting, and verify important website, phone, or email fields before using the CSV in outreach, reporting, or enrichment.

Output preview

What the Tripadvisor restaurant CSV includes

tripadvisor-restaurant-scraper-detail.csv
CSV - UTF-8 - Append

Column

URL_original

The Tripadvisor detail URL opened during the loop.

Column

Titre

Restaurant title from structured data, page heading, or fallback sample data.

Column

Website

Official restaurant website when Tripadvisor exposes an outbound link.

Column

Phone

Primary telephone number from structured data or tel links.

Column

Email

Email address when a mailto link is present or known from the sample preview.

Column

Adresse

Street address and locality as available on the restaurant page.

Column

Dimanche

Sunday opening hours.

Column

Lundi

Monday opening hours.

Column

Mardi

Tuesday opening hours.

Column

Mercredi

Wednesday opening hours.

Column

Jeudi

Thursday opening hours.

Column

Vendredi

Friday opening hours.

Column

Samedi

Saturday opening hours.

Sample rows

2 of many

URL_originalTitreWebsitePhoneEmailAdresseDimancheLundiMardiMercrediJeudiVendrediSamedi
Restaurant Wilhelm+49 30 3187324340Schlossplatz Humboldt Forum, 10178 Berlin GermanyClosedClosed6:00 PM - 10:30 PM6:00 PM - 10:30 PM6:00 PM - 10:30 PM6:00 PM - 10:30 PMClosed
Brasserie Colette Tim Raue+49 30 21992174Passauer Strasse 5-7, 10789 Berlin Germany12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM12:00 PM - 3:00 PM / 6:00 PM - 11:00 PM
Headers included - every accessible restaurant detail URL appends one row

FAQ

Frequently asked questions

Tripadvisor pages can be publicly visible, but automated collection may still be limited by Tripadvisor terms, robots directives, privacy law, database rights, and local marketing rules. Keep runs modest, respect access controls and CAPTCHA prompts, avoid republishing restricted content, and get legal review before using the CSV for resale, enrichment, or outreach.

Limits and maintenance notes

Practical guardrails

Access

CAPTCHA screens require manual judgment

If Tripadvisor asks for verification, pause the workflow and decide whether the run should continue. Do not design around bypassing access controls.

Pacing

Large batches need conservative timing

Add longer waits for slow networks, avoid parallel runs, and treat repeated empty rows or blocks as a signal to stop and review.

Drift

Selectors and page data can change

Tripadvisor layouts evolve. If title, website, hours, or address fields stop appearing, open the template and update the extraction logic before production use.

Get Started

Download and use this template instantly

$50Free

What's Included

  • Template JSON file ready to import
  • Pre-configured scraping nodes
  • Works with UScraper desktop app

Open-source templates

UScraper templates are open source. Improve this workflow or contribute a new one to help the community grow.

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Available on Windows 10+ and macOS 12+ · Need help? [email protected]