GelbeSeiten Leads Scraper

Building a contact list off GelbeSeiten by hand means opening each result, copying the phone number, the address, the website, and pasting it all into a sheet one business at a time. This scraper skips that. Give it a German keyword and a city, and every matching business comes back as a clean row with the company name, phone, address, website, and rating already split into fields. It runs on the GelbeSeiten directory, it's cheap, it needs no code, and you only pay for the rows you pull.

What you get

Each business listing comes back as one row, grouped into three kinds of data:

• Who and where — companyName, sectorName, streetAddress, postCode, cityName, fullAddress
• How to reach them — phoneNumber, websiteUrl, listingUrl, businessHours
• Reputation and context — starRating, reviewsTotal, profileSummary, searchPageUrl, searchTerm, searchCity

Quick start

1. Add one or more German keywords to Search terms (for example zahnarzt or friseur).
2. Add the cities you want covered to Cities (for example köln, dresden).
3. Set a Results limit to cap how many listings come back per keyword-and-city pair.
4. Press Start, then export the rows as JSON, CSV, Excel, or XML.

Use cases

• Sales prospecting — pull targeted lead lists for any German city and trade
• Cold outreach — gather phone numbers and websites for campaigns
• Competitor mapping — list every business in a category across several cities
• Market sizing — compare business counts, ratings, and coverage by region
• CRM enrichment — bulk-load German business contacts into your pipeline
• Local SEO work — collect category, address, and rating data to analyse

Input

Field	Type	Required	Description
searchTerms	array of strings	Yes	German keywords to look up; each one is run against every city. Prefilled with zahnarzt.
searchCities	array of strings	Yes	German cities, districts, or regions; each is paired with every keyword. Prefilled with köln.
resultsLimit	integer	No	Most listings to gather per keyword-and-city pair. Pagination runs until the cap is hit. Default 75.
timeoutSeconds	integer	No	Seconds to wait on each page request before giving up. Default 45.

Example input

{
    "searchTerms": ["friseur", "baeckerei", "steuerberater"],
    "searchCities": ["köln", "dresden", "stuttgart"],
    "resultsLimit": 75,
    "timeoutSeconds": 45
}

This runs 9 searches (3 terms × 3 cities) and returns up to 675 rows.

Output

Every business on the results page becomes one row, paginated automatically until your limit is reached. Fields that GelbeSeiten does not show for a given business come back as null rather than guessed.

Example output

{
    "companyName": "Friseur Schöneberg",
    "sectorName": "Friseure",
    "streetAddress": "Hauptstr. 24",
    "postCode": "50667",
    "cityName": "Köln",
    "fullAddress": "Hauptstr. 24, 50667 Köln",
    "phoneNumber": "0221 25 76 25 96",
    "websiteUrl": "https://friseur-schoeneberg.de/",
    "starRating": 4.7,
    "reviewsTotal": 38,
    "profileSummary": "Moderner Friseursalon im Herzen von Köln.",
    "businessHours": "Geöffnet – Schließt um 18:00",
    "listingUrl": "https://www.gelbeseiten.de/gsbiz/45c22f1a-3b99-4c04-9f0e-534ca0cd64d8",
    "searchPageUrl": "https://www.gelbeseiten.de/suche/friseur/koeln",
    "searchTerm": "friseur",
    "searchCity": "köln"
}

Output fields

Field	Type	Description
companyName	string	Trading name of the business
sectorName	string	Industry or trade category
streetAddress	string	Street name and house number
postCode	string	Five-digit German postal code
cityName	string	Town or district
fullAddress	string	Complete address as printed on the listing
phoneNumber	string	Main contact line
websiteUrl	string	Link to the company website
starRating	number	Average customer score out of 5.0
reviewsTotal	integer	Number of customer reviews
profileSummary	string	Short blurb or tagline from the listing
businessHours	string	Open or closed status with next closing time
listingUrl	string	Direct link to the GelbeSeiten profile
searchPageUrl	string	Results page the listing came from
searchTerm	string	Keyword that surfaced the listing
searchCity	string	City that was searched

Tips for best results

• Keep keywords in German. GelbeSeiten is a German directory, so arzt and bäckerei return results where their English equivalents will not.
• List many cities at once. Put every city in searchCities instead of running the actor again per city; each one pairs with each keyword automatically.
• Use resultsLimit for test runs. Start at 25 to confirm the columns fit your sheet, then raise it for the full pull.
• The limit is per pair, not per run. With 3 keywords and 4 cities at a limit of 50, you can get up to 600 rows, so set it with the total in mind.
• Raise timeoutSeconds if large result sets start timing out.
• Ratings show in German comma format on the site and are converted to standard decimals in the output.

How can I use GelbeSeiten business data?

How can I use the GelbeSeiten Leads Scraper to build a German sales list? Add the trades you sell to in searchTerms and your target cities in searchCities. Each row carries companyName, phoneNumber, websiteUrl, and fullAddress, so the export drops straight into a CRM or a dialer with no clean-up.

How can I find all businesses in one category across German cities? Put a single keyword such as rechtsanwalt in searchTerms and list every city you care about in searchCities. The actor pairs the keyword with each city and returns companyName, sectorName, cityName, and listingUrl for the whole set.

How can I collect German business contact data for market research? Set resultsLimit to the volume you need and export to CSV or Excel. With starRating, reviewsTotal, sectorName, and cityName on every row, you can measure business density and reputation by region.

How can I scrape phone numbers and websites from GelbeSeiten? Run any keyword-and-city combination and read the phoneNumber and websiteUrl fields. Both are pulled per listing, and rows where the business hides one of them still carry everything else.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.