HRS Hotel & Reviews Scraper — Hotels, Ratings & Guest Reviews

HRS Hotel & Reviews Scraper — Hotels, Ratings, Amenities & Guest Reviews

Extract European hotels and guest reviews from HRS.com as clean, structured data without coding or manual copy-pasting. This high-performance HRS scraper collects hotel profiles across Germany, Austria, Switzerland, France, Italy, Spain, the Netherlands, Poland, and international markets. Get verified star ratings, official address details, GPS coordinates, amenities, accepted payment options, gallery photos, overall guest ratings, and rich guest reviews with positive/negative commentary, reviewer travel type, hotel management responses, and per-category scores (cleanliness, breakfast, bed quality, reception service, price-performance ratio).

Point the scraper at specific hotel URLs or numeric IDs, or leave the input empty to automatically scrape HRS hotels through public sitemap discovery with seamless support for 1,000+ deep pagination and bulk data export.

Export seamlessly to JSON, CSV, Excel, or consume programmatically via the Apify REST API.

---

⚡ At a Glance

Feature	Details
Target Website	HRS.com (Global & European Hotel Booking Platform)
Data Extracted	Hotel names, star ratings, full address, GPS geo coordinates, guest ratings, review counts, amenity lists, payment methods, photos, detailed guest reviews with per-category breakdowns
Supported Locales	English (en), German (de), Spanish (es), French (fr), Italian (it), Dutch (nl), Polish (pl)
Discovery Modes	Direct hotel URLs / IDs or automated XML sitemap discovery across 270,000+ hotel properties
Deep Pagination	Unlocked for 1,000+ items (set maxItems: 0 for unlimited discovery)
Delivery Speed	100 hotels in ~15–30 seconds via concurrent HTTP streaming
Proxy Compatibility	Apify Datacenter Proxies (Residential fallback supported)
Export Formats	Dataset JSON, CSV, XLSX, XML, or direct REST API / Webhooks

---

🔎 Why Scrape HRS Hotel & Review Data?

HRS (Hotel Reservation Service) is Europe's premier business travel and corporate lodging network, cataloging over 270,000 hotels across key European metropolitan regions and international trade hubs. HRS hotel pages contain high-signal hospitality intelligence: verified star categories, guest score aggregates on a 1–10 scale, complete postal addresses, and uniquely detailed sub-category review ratings.

Unlike generic review sites where guests only assign an overall score, HRS reviews provide granular feedback across 10 distinct service facets: room cleanliness, price/performance ratio, breakfast quality, bed comfort, staff friendliness, bathroom quality, room layout, and hotel ambiance.

Key strategic benefits of automated HRS scraping:

• Hospitality Benchmarking: Compare guest satisfaction scores and individual category ratings between your property and competitors in Munich, Berlin, Paris, Vienna, Zurich, or London.
• Review Intelligence & NLP: Conduct sentiment analysis on business traveler feedback versus leisure travelers to detect operational deficiencies and strengths.
• OTA & Market Research: Map European corporate hotel supply, star distributions, and amenity offerings across metropolitan areas.
• Reputation Auditing: Monitor management response rates and public feedback trends across hotel chains and franchise groups.
• B2B Lead Generation: Extract corporate hotel contacts, addresses, and facility portfolios for hospitality service vendors and software suppliers.
• Machine Learning & Analytics: Feed clean, normalized hotel profiles and review text directly into travel recommendation algorithms and BI dashboards.

---

📊 Comparison Matrix

Capability	HRS Scraper (This Actor)	Manual Copy-Paste	Generic Scrapers	Official GDS / Corporate APIs
Data Throughput	100 hotels in < 30 seconds	1 hotel in 3–5 minutes	10–20 hotels / min (slow browsers)	Rate-limited / Contract-gated
Granular Category Scores	✅ Full 10 categories	🟡 Tedious extraction	❌ Often missing sub-scores	❌ Usually aggregated only
Management Responses	✅ Captured in full	🟡 Manual transcription	❌ Inconsistent parsing	❌ Not exposed
Automated Discovery	✅ 270K+ sitemap crawl	❌ None	❌ Fragile crawl rules	❌ Search parameter bounds
Zero Browser Overhead	✅ Pure HTTP execution	❌ N/A	❌ Heavy Chrome memory load	✅ Lightweight
Operational Cost	🟢 Fractions of a cent	🔴 High labor cost	🟡 High server compute cost	🔴 Thousands in licensing

---

✨ Key Features & Capabilities

• ✅ Unified Hotel & Review Records: Each dataset record pairs full property metadata with all embedded guest reviews for frictionless analysis.
• ✅ Automated Sitemap Discovery: Leave the URL list empty to discover and extract thousands of European hotels automatically from live sitemaps.
• ✅ 1,000+ Deep Pagination: Easily scale data pipelines from quick 50-hotel snapshots to massive 1,000+ or 10,000+ property catalogs without artificial cutoffs.
• ✅ Granular Category Scores: Capture exact 1–10 ratings for room cleanliness, breakfast service, bed quality, reception courtesy, sanitary facilities, and overall value.
• ✅ Reviewer Demographics: Identify whether feedback was submitted by corporate business travelers or leisure guests, along with travel dates and language codes.
• ✅ Hotel Response Capture: Scrape official hotel management replies to see how properties engage with customer feedback.
• ✅ Multi-Language Support: Extract native hotel descriptions and reviews in 7 languages (English, German, French, Spanish, Italian, Dutch, Polish).
• ✅ Zero Browser Overhead: Pure HTTP extraction delivers fast page processing and lower memory consumption compared to heavy headless browsers.
• ✅ Deduplication Engine: Built-in URL and ID normalization guarantees 0 duplicate entries across high-volume runs.

---

🎯 High-Impact Use Cases

1. Revenue Management & Competitor Benchmarking

Hotel owners and asset managers evaluate local market performance by analyzing nearby competitors' star tiers, average guest scores, and amenity packages. Pinpoint whether neighboring properties outperform your hotel on breakfast satisfaction or price-to-quality perception.

2. Corporate Travel & Supply Procurement

Corporate travel managers and relocation consultants analyze lodging quality near corporate business parks, airports, and exhibition centers to negotiate corporate booking rates.

3. Review Sentiment & Customer Experience Audits

Hospitality consultants mine thousands of negative and positive comments across European hotel chains to identify systemic complaints regarding room maintenance, noise levels, or Wi-Fi reliability.

4. Travel Tech & OTA Aggregation

Emerging travel agencies, hotel booking portals, and metasearch engines populate their catalogs with validated geographic coordinates, amenities, and authentic European guest testimonials.

5. Hotel Franchise Development & Site Selection

Commercial real estate investors evaluating new hospitality developments examine hotel density, prevailing star categories, and guest satisfaction gaps within targeted zip codes.

---

📥 Input Configuration

Parameter	Type	Default	Description
hotelUrls	Array	["https://www.hrs.com/en/hotel/393", ...]	Direct HRS hotel page URLs or numeric hotel IDs. Leave empty to enable automatic sitemap discovery.
startUrls	Array	[]	Advanced Apify request list sources for custom URL crawls.
includeReviews	Boolean	true	When enabled, parses and attaches embedded guest reviews to each hotel record.
maxReviewsPerHotel	Integer	0	Maximum reviews to save per hotel (0 = all embedded reviews on the page).
language	String	"en"	HRS site language: en (English), de (German), es (Spanish), fr (French), it (Italian), nl (Dutch), pl (Polish).
maxItems	Integer	100	Maximum number of hotels to scrape. Set to 0 for unlimited extraction.
maxConcurrency	Integer	10	Number of simultaneous HTTP requests (1 to 20).
proxyConfiguration	Object	{ "useApifyProxy": true }	Apify proxy configuration (datacenter proxy recommended).

---

📤 Output Data Fields

Every scraped hotel is returned as a structured JSON object. The table below details all fields along with data types and availability rates.

🏨 Hotel Profile & Overview

Field	Type	Coverage	Description
hotelId	String	🟢 High	Unique numeric HRS hotel identifier (e.g., "393").
name	String	🟢 High	Full name of the hotel property.
url	String	🟢 High	Canonical HRS hotel page URL.
stars	Number	🟢 High	Official HRS star rating (e.g., 4, 4.5, 5).
description	String	🟡 Conditional	Editorial summary and property description.
scrapedAt	String	🟢 High	ISO 8601 UTC timestamp of the scrape execution.

📍 Location & Geographic Coordinates

Field	Type	Coverage	Description
streetAddress	String	🟢 High	Street name and house number.
postalCode	String	🟢 High	Local postal / zip code.
addressLocality	String	🟢 High	City or municipality name (e.g., "Köln").
addressRegion	String	🟡 Conditional	State or province region.
addressCountry	String	🟢 High	Country name (e.g., "Germany").
latitude	Number	🟢 High	WGS84 geographic latitude coordinate.
longitude	Number	🟢 High	WGS84 geographic longitude coordinate.

⭐ Guest Ratings & Metrics

Field	Type	Coverage	Description
rating	Number	🟢 High	Aggregated guest satisfaction rating on a 1–10 scale (e.g., 8.4).
bestRating	Number	🟢 High	Top scale boundary (typically 10).
reviewCount	Number	🟢 High	Total verified guest reviews registered on HRS.
reviewsExtracted	Number	🟢 High	Count of full guest review objects attached to this record.

🛎️ Facilities, Amenities & Media

Field	Type	Coverage	Description
amenities	Array	🟢 High	Normalized list of hotel amenities (e.g., ["WLAN", "Restaurant", "Air conditioning", "Elevator"]).
paymentAccepted	String	🟡 Conditional	Supported payment methods (e.g., "Mastercard, Visa, American Express").
images	Array	🟢 High	High-resolution property and room image URLs.

💬 Detailed Guest Reviews (reviews[])

When includeReviews: true, each item in the reviews array includes:

Field	Type	Coverage	Description
travellerName	String	🟢 High	First name or display handle of the reviewer.
travellerType	String	🟢 High	Traveler profile: "BUSINESS", "LEISURE", or "OTHER".
date	String	🟢 High	Date when the review was submitted (e.g., "2026-03-12").
locale	String	🟢 High	Review submission language code (e.g., "en", "de").
ratio	Number	🟢 High	Overall review score given by this guest (1–10 scale).
guestPositiveComment	String	🟡 Conditional	Positive guest remarks and highlights.
guestNegativeComment	String	🟡 Conditional	Constructive criticism or complaints regarding the stay.
hotelResponse	String	🟡 Conditional	Official management response statement.
hotelRecommendation	Boolean	🟡 Conditional	Whether the guest formally recommends this property.
votes	Object	🟢 High	Sub-category scores: hotelTidiness, pricePerformanceRatio, breakfastService, qualityOfBeds, friendlinessOfReception, sanitaryFacilities, etc.

---

💻 Sample Output Record

{
  "hotelId": "393",
  "name": "Excelsior Hotel Ernst",
  "url": "https://www.hrs.com/en/hotel/393",
  "stars": 5,
  "rating": 9.2,
  "bestRating": 10,
  "reviewCount": 384,
  "streetAddress": "Trankgasse 1-5",
  "postalCode": "50667",
  "city": "Cologne",
  "country": "Germany",
  "latitude": 50.9419,
  "longitude": 6.9568,
  "amenities": [
    "WLAN",
    "Air conditioning",
    "Fitness center",
    "Restaurant",
    "Bar",
    "24-hour reception",
    "Concierge service",
    "Valet parking"
  ],
  "paymentAccepted": "Mastercard, Visa, American Express, Diners Club",
  "images": [
    "https://img.hrs.com/image/upload/v1/hotel/393/exterior_1.jpg",
    "https://img.hrs.com/image/upload/v1/hotel/393/lobby_1.jpg"
  ],
  "reviewsExtracted": 11,
  "reviews": [
    {
      "travellerName": "Alexander M.",
      "travellerType": "BUSINESS",
      "date": "2026-02-18",
      "locale": "en",
      "ratio": 9.5,
      "guestPositiveComment": "Outstanding location directly opposite Cologne Cathedral. Impeccable concierge service and quiet executive rooms.",
      "guestNegativeComment": null,
      "hotelResponse": "Thank you for choosing Excelsior Hotel Ernst. We look forward to welcoming you back on your next corporate visit to Cologne.",
      "hotelRecommendation": true,
      "votes": {
        "hotelTidiness": 10,
        "pricePerformanceRatio": 9,
        "hotelAmbiance": 10,
        "friendlinessOfReception": 10,
        "breakfastService": 9,
        "qualityOfBeds": 10,
        "roomConfiguration": 9,
        "roomSize": 9,
        "sanitaryFacilities": 10,
        "serviceOfHotelEmployees": 10
      }
    }
  ],
  "scrapedAt": "2026-11-10T13:45:00.000Z"
}

---

🛠️ Programmatic Integration & Code Examples

Integrate HRS hotel data into your automated pipelines via Python, Node.js, or cURL.

Python Integration

from apify_client import ApifyClient

# Initialize client with your Apify API token
client = ApifyClient("YOUR_APIFY_TOKEN")

# Run the actor with customized inputs
run = client.actor("haketa/hrs-scraper").call(
    run_input={
        "hotelUrls": [
            "https://www.hrs.com/en/hotel/393",
            "https://www.hrs.com/en/hotel/14311"
        ],
        "includeReviews": True,
        "maxReviewsPerHotel": 10,
        "language": "en",
        "maxItems": 100
    }
)

# Fetch dataset results
dataset_items = client.dataset(run["defaultDatasetId"]).list_items().items
for hotel in dataset_items:
    print(f"Hotel: {hotel.get('name')} | Rating: {hotel.get('rating')} | City: {hotel.get('city')}")

Node.js Integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
    token: 'YOUR_APIFY_TOKEN',
});

const run = await client.actor('haketa/hrs-scraper').call({
    hotelUrls: ['https://www.hrs.com/en/hotel/393'],
    includeReviews: true,
    language: 'en',
    maxItems: 50,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Fetched ${items.length} hotels from HRS dataset.`);

cURL API Request

curl -X POST "https://api.apify.com/v2/acts/haketa~hrs-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "hotelUrls": ["https://www.hrs.com/en/hotel/393"],
    "includeReviews": true,
    "maxItems": 50
  }'

---

🚀 Quickstart Guide

1. Create an Apify account or log in to your existing workspace.
2. Navigate to the HRS Hotel & Reviews Scraper page on the Apify Store.
3. Choose your configuration:
   • Provide a list of hotel URLs / IDs in hotelUrls.
   • Or clear hotelUrls to trigger automatic sitemap discovery.
4. Set your desired Maximum hotels (maxItems), e.g., 100 for a sample or 1000 for comprehensive data extraction.
5. Click Start to run the scraper.
6. Once the run completes, preview the dataset table and export your records in JSON, CSV, or Excel.

---

⚡ Performance, Scaling & Best Practices

• Deep 1,000+ Result Runs: When harvesting an entire country or region, clear hotelUrls and set maxItems: 1000 or higher. The built-in sitemap crawler reads sub-sitemaps automatically without running out of pages.
• Fast Profile-Only Mode: If you do not require guest review text and category votes, set includeReviews: false. This cuts payload processing time and memory by over 40%.
• Optimal Concurrency: The default maxConcurrency: 10 provides an optimal balance between throughput and connection stability. For large datasets, you can safely set it up to 15 or 20.
• Language Consistency: Always configure language according to your reporting requirements. English (en) and German (de) feature the highest density of detailed traveler reviews.
• Incremental Schedules: Configure Apify daily or weekly crons to capture newly published reviews and monitor changes in aggregate star ratings.

---

❓ Frequently Asked Questions

How does automatic sitemap discovery work? When no hotel URLs or IDs are supplied in hotelUrls, the actor fetches the official HRS XML sitemap index. It inspects sub-sitemaps containing over 270,000 active European and international hotels, de-duplicates URLs, and queues them for extraction up to your configured maxItems limit.

Can I scrape thousands of hotels in a single run? Yes. The pagination and discovery loop is unlocked for 1,000+ items. You can set maxItems to 1,000, 5,000, or any number.

How fresh is the extracted hotel data? All pages are requested live during execution. Ratings, amenity lists, pricing indicators, and reviews reflect the current state on HRS at run time.

Are both business and leisure reviews captured? Yes. HRS categorizes traveler profiles into BUSINESS and LEISURE. This distinction is preserved in the travellerType field.

What category scores are extracted from reviews? Up to 10 granular rating categories are captured per review: hotelTidiness, pricePerformanceRatio, hotelAmbiance, friendlinessOfReception, breakfastService, qualityOfBeds, roomConfiguration, roomSize, sanitaryFacilities, and serviceOfHotelEmployees.

Can I export the data directly into BigQuery, Snowflake, or Google Sheets? Yes. You can download the dataset as CSV/Excel or configure Apify Integrations (Make, Zapier, Google Drive, Airbyte) to stream data directly into your cloud data warehouse.

Do I need personal HRS account credentials? No. This actor extracts publicly accessible hotel directory information without requiring account login or authentication cookies.

How does this actor compare to browser-based scrapers? Because this actor utilizes direct HTTP stream processing rather than heavy headless browser instances, it uses significantly less memory (512 MB is sufficient) and executes up to 10× faster.

What happens if a hotel page URL is invalid or discontinued? The scraper automatically handles 404 and 410 HTTP responses without halting execution, logging a notice and proceeding to the next valid property in the queue.

Can I target hotels by city or region? You can supply hotel URLs filtered by city from your own list, or run automatic discovery and filter the exported dataset by the city or addressLocality column.

---

🔗 Related Travel & Hospitality Scrapers

Expand your travel intelligence pipeline with complementary actors from Haketa:

• Expedia Hotels Scraper — Prices, Ratings & Reviews
• Booking.com Scraper — Hotel Listings & Reviews
• Luma Event Scraper — Events, Hosts & Community Calendars
• Meetup Scraper — Events, Groups & Member Leads
• Eventbrite Scraper — Venues & Event Intelligence
• Furnished Finder Scraper — Monthly Corporate Rentals

---

📋 Changelog

• v1.2 (2026-11) — Unlocked deep 1,000+ pagination and sitemap discovery scale; optimized prefill execution to complete in under 2 minutes; refined zero-duplicate URL deduplication; updated schema validation standards and output metadata.
• v1.1 (2026-08) — Added granular 10-category review vote extraction (votes object); enhanced hotel management response detection; normalized multi-language support across 7 European locales.
• v1.0 (2026-05) — Initial release featuring automated XML sitemap discovery, JSON-LD schema parsing, embedded guest review extraction, and proxy rotation.