HRS Hotel Reviews Scraper — Export Guest Reviews to JSON, CSV & Excel

Scrape every published guest review from any hotel on HRS.com and HRS.de — review text, 1–10 ratings, 12 category scores, traveller type, dates and hotel replies — in seconds. No login, no API key, no cookies.

• ✅ Gets reviews other scrapers miss — HRS splits reviews across 7 language sites. This Actor sweeps all of them and merges the results.
• ✅ Rich data, not just stars — per-category scores (cleanliness, breakfast, beds…), traveller segments, and management responses.
• ✅ Fast and cheap — about 3.5 seconds per hotel, no browser, no CAPTCHA solving.
• ✅ Honest counts — clear reporting of what HRS actually publishes vs. the headline rating number.
• ✅ Export anywhere — JSON, CSV, Excel, XML, or straight into your app via API.

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📌 What This Actor Does

HRS is one of Europe's largest hotel booking platforms, especially dominant in business travel across Germany, Austria and Switzerland. Its guest reviews are detailed — every review carries a 1–10 score plus up to 12 individual category ratings — but HRS offers no public API and no way to export them.

This Apify Actor does that for you. Give it a hotel URL or hotel ID, and it returns a clean, structured dataset of that hotel's reviews and profile.

Who it's for

You are…	You use it to…
Hotel & revenue managers	Track your property's reputation and benchmark against competitors
Hospitality groups & chains	Monitor reviews across an entire portfolio in one run
Market researchers & analysts	Build datasets on European hotel quality and guest sentiment
Data scientists & AI teams	Feed real multilingual review text into sentiment models and LLMs
Travel tech & OTA developers	Enrich listings with review data HRS doesn't expose via API
Agencies & consultants	Produce reputation audits and competitor reports for clients

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✨ Key Features

• Complete review coverage. Sweeps all 7 HRS language sites (German, English, Spanish, French, Italian, Dutch, Polish) and merges them into one deduplicated set.
• Full review detail. Positive comment, negative comment, 1–10 score, recommendation flag, traveller type, and exact timestamp.
• Category-level ratings. Up to 12 scores per review: cleanliness, value for money, breakfast, bed quality, room size, bathroom, reception friendliness, staff service, atmosphere, room layout, restaurant and wellness.
• Hotel management replies. Captures the hotel's public response where one exists.
• Complete hotel profile. Name, star rating, full address, GPS coordinates, image, average score, recommendation rate, and rating breakdowns by traveller segment.
• Bulk scraping. Process one hotel or hundreds in a single run.
• Incremental runs. targetDate collects only reviews newer than your last run.
• Stable review IDs. Every review gets a deterministic ID so you can deduplicate across runs.
• Analysis-ready output. Split and combined review text, so it works with CSV tools and AI pipelines alike.
• No blocking. No CAPTCHAs, no login walls, no anti-bot workarounds needed.

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🧠 Why This Actor Is Different

It solves the problem most HRS scrapers get wrong

An HRS hotel page only shows the reviews written on that language's website.

Take hotel 391864. The English page shows 2 reviews. If your scraper reads that page — which is the obvious thing to do — that's all you get. The German page for the same hotel has 32. The real total is 34.

Scraping one page returns 6% of the available reviews for that hotel. This Actor fetches every language site and merges them, so you get all 34.

It tells you the truth about review counts

HRS displays "67 ratings" for that hotel, but only 34 are published anywhere, in any language. The other 33 are score-only submissions with no written comment, plus ratings older than HRS's ~24-month display window. HRS never serves them — to anyone.

Rather than quietly returning 34 and letting you wonder what broke, this Actor reports both numbers (totalRatings and reviewsScraped) and explains the gap in the run log. No guesswork.

Built on the data layer, not fragile HTML

It reads HRS's own structured server data rather than scraping rendered HTML with CSS selectors. That means cleaner values, no formatting artifacts, and far less breakage when HRS redesigns its pages.

Fast and lightweight

No headless browser, so no browser overhead and no CAPTCHA-solving costs. A 5-hotel run with 67 reviews completes in under 18 seconds.

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⚙️ Input Configuration

Field	Type	Required	Default	Description
startUrls	Array	One of these	–	HRS hotel page URLs. Any language version works.
hotelIds	Array	One of these	–	Numeric HRS hotel IDs. Use instead of, or alongside, startUrls.
languages	Array	No	all 7	Restrict to specific language sites. Leave empty for complete results.
maxReviews	Integer	No	0	Max reviews per hotel, newest first. 0 = unlimited.
targetDate	String	No	–	Only reviews on or after this date (YYYY-MM-DD).
proxyConfiguration	Object	No	–	Optional. HRS does not block requests, so this is rarely needed.

Basic example — one hotel, all reviews

{
  "startUrls": [{ "url": "https://www.hrs.com/en/hotel/391864" }]
}

Bulk example — several hotels

{
  "hotelIds": ["391864", "60754", "464662"],
  "maxReviews": 0
}

Incremental example — only new reviews since your last run

{
  "hotelIds": ["391864"],
  "targetDate": "2025-06-01"
}

💡 Tips for best results

• Leave languages empty. Restricting it is the single most common way to end up with an incomplete dataset. Only narrow it if you specifically want reviews from one market.
• Where to find the hotel ID: it's the number at the end of the URL — hrs.com/en/hotel/391864. Both hrs.com and hrs.de URLs work.
• maxReviews doesn't reduce cost or runtime. HRS sends a whole language's reviews in one page load, so the Actor still fetches everything and then trims. Use it to cap dataset size, not to run faster.
• Run daily or weekly with targetDate set to your last run date for efficient reputation monitoring.
• Skip the proxy unless you're running very large batches.

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📤 Output Format

The Actor stores one dataset record per hotel, with that hotel's reviews nested inside it. Export as JSON, CSV, Excel, XML, or fetch via the Apify API.

{
  "hotelId": 391864,
  "name": "Hotel Brandenburger Tor Potsdam",
  "url": "https://www.hrs.com/en/hotel/391864",
  "stars": 4,
  "street": "Brandenburger Str. 1 - 3",
  "city": "Potsdam",
  "postalCode": "14467",
  "country": "DEU",
  "latitude": 52.399619,
  "longitude": 13.048601,
  "imageUrl": "https://foto.hrsstatic.com/fotos/...jpg",
  "averageRating": 9.1,
  "ratingMax": 10,
  "totalRatings": 67,
  "recommendationRate": 97,
  "categoryAverages": {
    "hotelTidiness": 9.2,
    "friendlinessOfReception": 9.4,
    "breakfastService": 9.3,
    "pricePerformanceRatio": 8.8
  },
  "ratingsByTravellerType": [
    { "travellerType": "BUSINESS", "travellerTypeLabel": "Business traveller", "rating": 9, "recommendationRate": 94.7 }
  ],
  "languagesScraped": ["de", "en", "es", "fr", "it", "nl", "pl"],
  "reviewsScraped": 34,
  "reviewsAvailable": 34,
  "reviews": [
    {
      "reviewId": "5cc88d4ec4709c48",
      "rating": 9.1,
      "ratingMax": 10,
      "recommended": true,
      "reviewerName": null,
      "travellerType": "BUSINESS",
      "travellerTypeLabel": "Business traveller",
      "date": "2024-11-27T08:34:31.260Z",
      "siteLanguage": "de",
      "positiveComment": "freundliches Personal",
      "negativeComment": null,
      "text": "freundliches Personal",
      "hotelReply": "Lieber Gast, vielen Dank für Ihr Feedback! ...",
      "categoryRatings": { "hotelTidiness": 10, "qualityOfBeds": 9 },
      "sourceUrl": "https://www.hrs.com/de/hotel/391864"
    }
  ]
}

Hotel fields

Field	Type	Description
hotelId	Number	HRS hotel ID
name	String	Hotel name
url	String	Canonical HRS hotel page
stars	Number	Official star rating (1–5)
street, city, postalCode, country	String	Full address
latitude, longitude	Number	GPS coordinates
imageUrl	String	Main hotel photo
averageRating	Number	Overall guest score, out of 10
totalRatings	Number	All ratings HRS counts, including unpublished ones
recommendationRate	Number	% of guests who would recommend
categoryAverages	Object	Hotel-wide average per category
ratingsByTravellerType	Array	Score and recommendation rate per guest segment
languagesScraped	Array	Language sites successfully visited
reviewsScraped	Number	Reviews in this record
reviewsAvailable	Number	Reviews found before maxReviews trimmed them

Review fields

Field	Type	Description
reviewId	String	Stable ID, consistent across runs — use it to deduplicate
rating	Number	Guest's overall score, out of 10 (ratingMax)
recommended	Boolean	Whether the guest recommends the hotel
reviewerName	String | null	Display name; null when posted anonymously
travellerType	String	BUSINESS, PRIVATE, MATURE_COUPLE, YOUNG_COUPLE, …
travellerTypeLabel	String	Human-readable version of the above
date	String	ISO 8601 timestamp
siteLanguage	String	Which HRS language site the review came from
positiveComment	String | null	What the guest liked
negativeComment	String | null	What the guest disliked
text	String | null	Both comments combined — convenient for CSV and AI tools
hotelReply	String | null	The hotel's public response, if any
categoryRatings	Object	This guest's individual category scores
sourceUrl	String	Page the review was read from

⚠️ Three things worth knowing about the data

1. Ratings are out of 10, not 5. HRS uses a 1–10 scale. The ratingMax field carries this so nothing downstream has to assume.
2. Reviews are split in two. HRS asks guests separately what they liked and disliked, so positiveComment and negativeComment are distinct fields and either can be empty. The text field joins them for convenience.
3. siteLanguage is the source site, not detected language. It tells you which HRS site a review came from — usually but not always the language of the text. (The English site sometimes carries German-language reviews.) Don't use it as a language label for the review body.

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▶️ How to Use

Step 1 — Find your hotel

Search on hrs.com and open the hotel's page. Copy the URL, for example:

https://www.hrs.com/en/hotel/391864

Step 2 — Add it to the input

Paste the URL into Start URLs, or just the number (391864) into Hotel IDs. Add as many hotels as you like.

Step 3 — Run it

Click Start. Most hotels finish in a few seconds.

Step 4 — Export

Open the Dataset tab and download as JSON, CSV, Excel or XML, or pull it via API:

https://api.apify.com/v2/datasets/<DATASET_ID>/items?format=csv

Common workflows

Monitor your hotel weekly Schedule the Actor to run every Monday with targetDate set to the previous week. You'll only collect new reviews.

Benchmark against competitors Put your hotel and 5–10 nearby competitors into hotelIds in one run, then compare averageRating and categoryAverages to see exactly where you win or lose.

Build a training dataset Run across hundreds of hotel IDs with maxReviews: 0 to build a large multilingual review corpus with matching category scores.

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📈 Use Cases

1. Hotel reputation monitoring

Track your score over time, catch negative reviews within days, and confirm your team is replying. categoryAverages shows precisely which areas — breakfast, cleanliness, value — are pulling your score down.

2. Competitor benchmarking

Scrape every competing hotel in your city and compare average scores, recommendation rates, and category strengths. Discover that competitors consistently beat you on breakfast but lose on location — then price accordingly.

3. Market research & travel analytics

Build datasets covering entire cities or regions. Because HRS is strong in DACH business travel, it's a valuable source for analysing the European corporate hotel market specifically.

4. AI & sentiment analysis

Feed real multilingual guest feedback into sentiment models, topic clustering, or LLM pipelines. Each review arrives with a numeric score and category ratings attached — ideal labelled training data.

5. Due diligence & property investment

Assessing a hotel acquisition or franchise deal? Pull its full review history to check guest satisfaction trends, recurring complaints, and how management handles criticism.

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🛠️ Advanced Tips

Performance. The Actor makes 7 requests per hotel (one per language site) — roughly 3.5 seconds each. A 100-hotel run takes around 6 minutes. Runtime scales with hotel count, not review count.

Cutting requests. If you only need German-market reviews, set languages: ["de"] to make one request per hotel instead of seven. You'll be ~7× faster but you will miss reviews from other sites.

Proxies. HRS doesn't block scraping, so no proxy is needed for normal use. For very large batches, enable Apify Proxy (residential or datacenter) to spread requests across IPs. The Actor automatically retries with a fresh IP if a request fails.

Scaling to thousands of hotels. Split hotel IDs across several runs rather than one huge run — smaller runs are easier to monitor, retry, and resume.

Deduplicating across runs. Use reviewId as your primary key. It's derived from the review's content and stays identical across runs and language sites.

Scheduling. Use Apify Schedules for automated monitoring, and Webhooks to push new reviews straight into Slack, a database, or Google Sheets.

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❓ FAQ & Troubleshooting

Why is reviewsScraped lower than totalRatings? This is expected and correct. totalRatings counts every score the hotel ever received; HRS only publishes reviews that have written text and fall inside its ~24-month display window. Everything HRS makes public is in your dataset — the rest isn't accessible to anyone, including regular website visitors.

The Actor returned very few reviews. Did it fail? Probably not — some hotels genuinely have few published reviews. Check languagesScraped in the output. If it lists all 7 languages, the scrape was complete. Also confirm you didn't restrict languages or set a targetDate that filters out most reviews.

Why does it visit 7 URLs for one hotel? Because HRS only shows reviews on the language site where they were written. Visiting all 7 is the only way to get a complete set. (For hotel 391864, the English page alone would return 2 of 34 reviews.)

Can I get reviews in one specific language? Yes — set languages to e.g. ["de"]. Note this selects the site the review was posted on, which is usually but not always the language of the text.

Do I need a proxy? No. HRS serves these pages without blocking. Proxies are optional and mainly useful for very large runs.

Do I need an HRS account or API key? No. The Actor uses only publicly available data.

"Hotel does not exist on HRS (404 on every locale)" The hotel ID is wrong or the property has been removed. Open the URL in your browser to confirm. The Actor skips it and continues with your other hotels.

Can I scrape hotel prices or availability? No. This Actor focuses on reviews and hotel profile data. Prices depend on dates and occupancy and are out of scope.

Why are some reviews missing a reviewer name? HRS lets guests post anonymously. Those come through as reviewerName: null.

What about GDPR and legal use? The Actor collects only publicly available review data — no personal contact details or private information. Reviewer names appear as HRS publishes them (typically a first name and last initial). You are responsible for using the data in line with applicable laws and Apify's Terms of Service.

Can I export to Google Sheets or a database? Yes. Use Apify's built-in integrations, webhooks, or the Dataset API. CSV export works directly with Sheets and Excel.

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💰 Pricing

This Actor uses pay-per-event pricing: you're charged per review successfully scraped and stored. Hotels that fail to scrape cost you nothing, and hotels with no reviews are free.

Apify platform usage (compute, proxy) is billed separately under your plan.

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📞 Support

Questions, bug reports, or feature requests are welcome.

• Email: me@ahmedhrid.com
• Issues: Use the Issues tab on this Actor's page in Apify Console

If you're reporting a problem, please include the hotel URL or ID and your run ID — it makes diagnosis much faster.

Need a scraper for a different booking platform, or a customised version of this one? Get in touch.

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🔗 Related Keywords

HRS scraper · HRS.com scraper · HRS.de scraper · hotel reviews scraper · hotel review data · guest review scraping · hotel reputation monitoring · web scraping · Apify actor · travel data extraction · hospitality market research · European hotel data · booking platform scraper · hotel ratings API alternative