Allegro Scraper | Products, Prices and Sellers (2026)

From SilentFlow. Creators of Pinterest Scraper and Leboncoin Scraper, with 420,000+ combined lifetime runs.

Every Allegro offer as one complete row: the brand, the price and the price with delivery, the price before the discount, the condition, the category path, every parameter with the EAN, the stock, how many people bought it, the product rating with its star breakdown, the delivery date, the return terms, and the company behind the seller with its tax ID, REGON, KRS and address. Our test run returned 100 LEGO Technic offers in 7 seconds, each one read in full with the company behind its seller, without an Allegro account. Allegro Czechia, Slovakia and Hungary work the same way.

Why choose this actor?

Copying Allegro prices into a spreadsheet one offer at a time? Seeing an unknown login undercut your price and not knowing which company is behind it? Tracking the same offers every week by searching for them again?

• 56 fields filled per offer, not 22. On the default run (100 offers for lego technic), 56 of the 65 fields carry a value on at least half the rows, and every row had its brand, EAN, set number, stock, product rating with its five-star breakdown, delivery price, price with delivery, delivery date, return terms and seller company: the category path, every parameter, how many people bought it, the Smart!, free return and best price flags, and the seller's company name, tax ID, street, city, country, rating share and Super Seller badge. The REGON, KRS, representative and opening hours come in the same row when Allegro publishes them. The most used Allegro scraper shows 22 fields in its README example, and its stock, EAN, rating details and seller company only come with extra switches.
• Keywords, Allegro URLs and offer numbers, on four marketplaces. Search by keyword, paste any Allegro search, category or offer address, or paste bare offer numbers (18583540376) to follow the same offers over time. In our test, three offer numbers gave three complete rows in under a second. Pick Czechia, Slovakia or Hungary and the same keyword returns that country's offers in its language and currency: 40 Czech offers in 6 seconds, priced in CZK. The most used Allegro scraper takes keywords and URLs, not offer numbers.
• Seven form fields, none of them required. Keywords, URLs and offer numbers at the top, then the country, a cap and a price range. The prefilled input runs as is, and every offer is read in full, seller company included, without a toggle to switch on. The most used Allegro scraper has 14 fields, with the seller's company and the full offer behind two separate switches.

Try your first 100 offers

Paste this input in the JSON tab of the Input page and press Start. It reads the 100 LEGO Technic offers Allegro ranks first, each one in full, with its seller.

{
  "searchQueries": ["lego technic"],
  "maxItems": 100
}

It runs on the Apify Free plan. Each offer becomes one row of your dataset: open the Output tab to see the table, switch to the Sellers view to compare the companies behind the offers, or export the rows as JSON, CSV or Excel.

Copy to your AI assistant

Paste this block into Claude, ChatGPT or Cursor to give it the full picture of this scraper:

You have access to the Allegro Scraper on Apify: silentflow/allegro-scraper

It reads Allegro (allegro.pl, allegro.cz, allegro.sk, allegro.hu) without an account and returns one row
per offer. Every row includes the full offer (brand, parameters, EAN, stock, buyers count, product rating
and star breakdown, delivery price and date, return terms) and the seller (login, company name, tax ID,
REGON, KRS, representative, address, country, opening hours, positive rating share, Super Seller badge).

Input schema (no field is required, at least one of searchQueries, startUrls or offerIds is needed):
- searchQueries (array of strings): keywords searched on Allegro, local language or English ("lego technic").
- startUrls (array of {url}): Allegro addresses on any of the four domains. Search pages keep their
  filters (string, price_from, price_to). Also /kategoria/...-{id}, /oferta/...-{id} (/nabidka/, /ponuka/,
  /ajanlat/ on cz, sk, hu) and /produkt/...?offerId={id}. Seller storefronts and searches for used
  offers (stan=używane) are skipped: searches list new offers, in Allegro's own order.
- offerIds (array of strings): offer numbers (18583540376), new or used. A pasted offer URL also works.
- country (string, default "pl"): marketplace of keywords and offer numbers: pl, cz, sk or hu
  (a name such as "czechia" or a domain such as "allegro.cz" also works).
- maxItems (integer, default 100): max rows for the whole run, across keywords, URLs and ids.
- minPrice, maxPrice (integers, in the marketplace's currency): price band for keywords and search addresses.
The price band written in a URL wins over the form's for that URL. Offer numbers are never filtered.

Output per offer (65 fields, null when absent):
- id (string, offer number), url (string), title (string), productId (string), productUrl (string)
- condition (string, local language: Nowy, Używany...), brand (string), ean (string), manufacturerCode (string)
- categoryId (string), categoryName (string), categoryPath (string, "Department > ... > leaf")
- parameters (object, parameter name -> value, local language),
  sellingFormat (BUY_NOW | AUCTION | ADVERTISEMENT), status (ACTIVE | ENDED ...)
- sellerId, sellerLogin, sellerUrl (strings), isSuperSeller (boolean), sellerPositivePercent (number),
  sellerPositiveCount, sellerNegativeCount (integers, last 12 months), sellerCompanyName, sellerTaxId,
  sellerStreet, sellerZipCode, sellerCity, sellerCountryCode, sellerRegon, sellerKrs,
  sellerRepresentative, sellerOpenHours (strings), isSellerVerified (boolean)
- price (number), currency (PLN | CZK | EUR | HUF), originalPrice (number), discountPercent (integer),
  lowestDeliveryPrice (number, 0 when free), priceWithDelivery (number, price + lowestDeliveryPrice),
  isSmart, isFreeReturn (booleans), returnPeriodDays (integer), returnPolicyLabel (string),
  hasBestPriceGuarantee, isSponsored (booleans), stockAvailable, buyersCount (integers),
  popularityLabel (string), rating (number, product rating out of 5), ratingsCount (integer),
  ratingLabel (string), ratingDistribution (array of {score, count, percentage}),
  currentBid (number), bidsCount (integer)
- deliveryLabel (string, local language), estimatedDeliveryDate (YYYY-MM-DD), endsAt (RFC 3339)
- imageUrl (string), images (array of strings), imagesCount (integer)
- marketplace (allegro.pl | allegro.cz | allegro.sk | allegro.hu), searchQuery (string, the keyword,
  URL or id that found the row), position (integer, rank in the search), scrapedAt (RFC 3339),
  dataType ("offer")

Use apify-client for Python or JavaScript: client.actor("silentflow/allegro-scraper").call(run_input=...).

How to scrape Allegro products

Three inputs, from the simplest to the most complete. Each one runs as is.

Get the top 100 offers for a keyword

{
  "searchQueries": ["lego technic"],
  "maxItems": 100
}

The offers Allegro shows first for the keyword, each with its brand, price, price with delivery, the price before a discount, condition, parameters, stock, buyers count, product rating and star breakdown, delivery date, return terms and seller company. Polish keywords match more titles than English ones, because sellers write in Polish (ekspres do kawy rather than coffee machine).

Compare coffee machines between 500 and 3,000 PLN

{
  "searchQueries": ["ekspres do kawy"],
  "minPrice": 500,
  "maxPrice": 3000,
  "maxItems": 30
}

In our test run this input returned 30 coffee machines priced between 599 and 2,599 PLN in 2 seconds, each with its brand (Philips, Krups, De'Longhi and others), stock, return terms and seller, and the seller's KRS number on 25 of the 30 rows. Sort the table by buyersCount to see which machines actually sell, or by rating to see which ones buyers like.

Read a category, a search page and two offers in one run

{
  "startUrls": [
    { "url": "https://allegro.pl/kategoria/laptopy-491?string=lenovo&price_to=3000" },
    { "url": "https://allegro.pl/listing?string=rower%20g%C3%B3rski&price_from=1500" }
  ],
  "offerIds": ["18903897166", "17914549769"],
  "maxItems": 80
}

The category address keeps its keyword and its price ceiling, the search address keeps its price floor, and the two offer numbers are read directly. Rows found twice are kept once.

Input parameters

Parameter	Type	Default	What it does
searchQueries	array of strings	prefilled lego technic	Keywords searched on Allegro, one search per keyword, results combined without duplicates.
startUrls	array of URLs	none	Allegro search, category, offer or product-on-offer addresses, on allegro.pl, .cz, .sk or .hu.
offerIds	array of strings	none	Offer numbers, read directly. A pasted offer address also works.
country	string	pl	Marketplace of keywords and offer numbers: pl (Poland), cz (Czechia), sk (Slovakia), hu (Hungary). A name (czechia) or a domain (allegro.cz) also works.
maxItems	integer	100	Maximum number of offers for the whole run.
minPrice	integer	none	Keep offers priced at or above this amount, in the marketplace's currency.
maxPrice	integer	none	Keep offers priced at or below this amount, in the marketplace's currency.

No field is required: the prefilled keyword is enough to start. Give at least one keyword, one address or one offer number.

Country	Domain	Currency	Language of titles and parameters
pl	allegro.pl	PLN	Polish
cz	allegro.cz	CZK	Czech
sk	allegro.sk	EUR	Slovak
hu	allegro.hu	HUF	Hungarian

Accepted address formats

You paste	Example	You get
Search page	https://allegro.pl/listing?string=iphone%2015&price_from=1500	The offers of that search, with its phrase and price band
Category	https://allegro.pl/kategoria/smartfony-i-telefony-komorkowe-165	The offers of the category, most relevant first
Category with a keyword	https://allegro.pl/kategoria/laptopy-491?string=lenovo	The category narrowed to the keyword
Offer	https://allegro.pl/oferta/smartfon-apple-iphone-15-...-18583540376	That one offer
Product page on an offer	https://allegro.pl/produkt/...?offerId=18583540376	That one offer
Offer number	18583540376	That one offer
Czech, Slovak or Hungarian offer	https://allegro.cz/nabidka/...-18156342184, /ponuka/..., /ajanlat/...	That one offer, in that country's language and currency
Czech, Slovak or Hungarian search	https://allegro.sk/listing?string=lego%20technic	The offers of that search on that marketplace

Seller storefronts (/uzytkownik/... and their Czech, Slovak and Hungarian versions), product pages without an offerId and searches for used offers (stan=używane) are named in the log and skipped. Every other address is read.

What data can you extract from Allegro?

65 fields per offer, flat, in seven groups. On the default run, 56 of them carry a value on at least half the rows (53 to 61 per row). The discount fields (originalPrice, discountPercent) fill when the offer is on sale, endsAt when the offer has an end date, the auction fields (currentBid, bidsCount) on auctions, and the seller's REGON, KRS, representative and opening hours when Allegro publishes them for that seller.

Group	Fields
Identity	id, url, title, productId, productUrl
Content	condition, brand, ean, manufacturerCode, categoryId, categoryName, categoryPath, parameters, sellingFormat, status
Seller	sellerId, sellerLogin, sellerUrl, isSuperSeller, sellerPositivePercent, sellerPositiveCount, sellerNegativeCount, sellerCompanyName, sellerTaxId, sellerStreet, sellerZipCode, sellerCity, sellerCountryCode, sellerRegon, sellerKrs, sellerRepresentative, sellerOpenHours, isSellerVerified
Price and demand	price, currency, originalPrice, discountPercent, lowestDeliveryPrice, priceWithDelivery, isSmart, isFreeReturn, returnPeriodDays, returnPolicyLabel, hasBestPriceGuarantee, isSponsored, stockAvailable, buyersCount, popularityLabel, rating, ratingsCount, ratingLabel, ratingDistribution, currentBid, bidsCount
Time	deliveryLabel, estimatedDeliveryDate, endsAt
Media	imageUrl, images, imagesCount
Meta	marketplace, searchQuery, position, scrapedAt, dataType

A few facts that help when you use the data:

• id is Allegro's offer number and never changes; url is the permanent offer address. productId groups every seller's offer of the same catalogue product, so you can compare sellers of one product.
• price, originalPrice, lowestDeliveryPrice and priceWithDelivery are numbers in the marketplace's currency (currency), never text. originalPrice is the price Allegro strikes through next to a discount, the lowest price of the last 30 days before the cut. priceWithDelivery is the price plus the cheapest delivery, what the buyer pays at least.
• brand comes from the offer's brand parameter, or from the catalogue product when the seller left the parameter out (every LEGO set, for one). It was filled on all 100 rows of the default run.
• buyersCount is the number of people who bought the offer recently, as Allegro prints it under the price ("16 osób kupiło"). stockAvailable is the quantity the seller has left.
• rating and ratingsCount are the product's ratings across all its offers, out of 5. ratingLabel is Allegro's verdict ("Rewelacyjny") and ratingDistribution the five bars of the histogram, from 5 stars to 1, each with its count and share.
• returnPeriodDays is the number of days the buyer has to send the item back (14 on 94 of the 100 default rows, up to 60 on others), returnPolicyLabel Allegro's own words, isFreeReturn whether the return is free.
• sellerPositivePercent, sellerPositiveCount and sellerNegativeCount cover the seller's last 12 months.
• sellerCompanyName, sellerTaxId, sellerRegon, sellerKrs, sellerRepresentative and the address are the trader details Allegro publishes for business sellers. sellerTaxId is written without dashes or spaces (9482602184). A private seller has none, and those fields are null.
• estimatedDeliveryDate is Allegro's delivery promise turned into a date (2026-10-06 for "dostawa we wtorek"), the latest day of a range. deliveryLabel keeps Allegro's own words. Both work on the four marketplaces.
• isSponsored says whether the search slot was a paid one ("Promowane"). It is null for offers read by number, which were not found through a search.
• Image URLs point to Allegro's image server and stay valid while the offer exists.
• Titles, conditions, parameter names and labels are Allegro's original text, in the marketplace's language. marketplace names the domain the row was read on.

Output example

One row of the default run, as it appears in the dataset (JSON view):

{
  "id": "17627592635",
  "url": "https://allegro.pl/oferta/lego-technic-42092-helikopter-ratunkowy-nowe-17627592635",
  "title": "LEGO Technic - 42092 Helikopter ratunkowy - Nowe",
  "productId": "64cc049d-515d-49e1-b6eb-88edce2268a2",
  "productUrl": "https://allegro.pl/produkt/lego-technic-42092-helikopter-ratunkowy-64cc049d-515d-49e1-b6eb-88edce2268a2?offerId=17627592635",
  "condition": "Nowy",
  "brand": "LEGO",
  "ean": "5702016369571",
  "manufacturerCode": "42092",
  "categoryId": "17873",
  "categoryName": "Technic",
  "categoryPath": "Dziecko > Zabawki > Klocki > LEGO > Zestawy > Technic",
  "parameters": {
    "Bohater / Bajka": "brak",
    "Certyfikaty, opinie, atesty": "CE",
    "EAN (GTIN)": "5702016369571",
    "Faktura": "Wystawiam fakturę VAT",
    "Liczba elementów": "325",
    "Materiał": "plastik",
    "Minimalny wiek dziecka": "3",
    "Nazwa zestawu": "42092",
    "Numer produktu": "42092",
    "Płeć": "chłopcy, dziewczynki",
    "Stan": "Nowy",
    "Waga produktu z opakowaniem jednostkowym": "0.45 kg",
    "Wiek dziecka": "8 lat +"
  },
  "sellingFormat": "BUY_NOW",
  "status": "ACTIVE",
  "sellerId": "39218039",
  "sellerLogin": "_ACorp_",
  "sellerUrl": "https://allegro.pl/uzytkownik/_ACorp_",
  "isSuperSeller": true,
  "sellerPositivePercent": 99.5,
  "sellerPositiveCount": 409,
  "sellerNegativeCount": 2,
  "sellerCompanyName": "ACorp Adam Cybulski",
  "sellerTaxId": "7661977014",
  "sellerStreet": "Konopnickiej 19",
  "sellerZipCode": "62-100",
  "sellerCity": "Wągrowiec",
  "sellerCountryCode": "PL",
  "sellerRegon": "360426295",
  "sellerKrs": null,
  "sellerRepresentative": "Adam Cybulski",
  "sellerOpenHours": "poniedziałek - sobota: 09:00–17:00; niedziela: zamknięte",
  "isSellerVerified": true,
  "price": 329,
  "currency": "PLN",
  "originalPrice": 395,
  "discountPercent": 17,
  "lowestDeliveryPrice": 10.49,
  "priceWithDelivery": 339.49,
  "isSmart": true,
  "isFreeReturn": true,
  "returnPeriodDays": 14,
  "returnPolicyLabel": "Zwrot za darmo, 14 dni na odstąpienie od umowy",
  "hasBestPriceGuarantee": false,
  "isSponsored": false,
  "stockAvailable": 1,
  "buyersCount": 1,
  "popularityLabel": "1 osoba kupiła 1 sztukę",
  "rating": 4.98,
  "ratingsCount": 2055,
  "ratingLabel": "Rewelacyjny",
  "ratingDistribution": [
    { "score": 5, "count": 2016, "percentage": 98 },
    { "score": 4, "count": 35, "percentage": 1 },
    { "score": 3, "count": 3, "percentage": 0 },
    { "score": 2, "count": 1, "percentage": 0 },
    { "score": 1, "count": 0, "percentage": 0 }
  ],
  "currentBid": null,
  "bidsCount": null,
  "deliveryLabel": "dostawa we wtorek",
  "estimatedDeliveryDate": "2026-10-06",
  "endsAt": null,
  "imageUrl": "https://a.allegroimg.com/original/11d949/8b4d5d1344c88d9d1b58ed7f8cfa/LEGO-Technic-42092-Helikopter-ratunkowy-Nowe",
  "images": [
    "https://a.allegroimg.com/original/11d949/8b4d5d1344c88d9d1b58ed7f8cfa/LEGO-Technic-42092-Helikopter-ratunkowy-Nowe",
    "https://a.allegroimg.com/original/11185a/4c4bfbe64a6ca23f126e8dff6d28/LEGO-Technic-42092-Helikopter-ratunkowy-Nowe-Numer-produktu-42092",
    "https://a.allegroimg.com/original/11a574/63ae51e147c0ab5a340d15a25c88/LEGO-Technic-42092-Helikopter-ratunkowy-Nowe-Marka-LEGO",
    "https://a.allegroimg.com/original/11f6b7/2f9372f04fe3b2b822a67b995118/LEGO-Technic-42092-Helikopter-ratunkowy-Nowe-Wiek-dziecka-8-lat"
  ],
  "imagesCount": 4,
  "marketplace": "allegro.pl",
  "searchQuery": "lego technic",
  "position": 93,
  "scrapedAt": "2026-10-03T22:50:33Z",
  "dataType": "offer"
}

Advanced usage

Watch your own offers every morning

{
  "offerIds": ["18903897166", "17914549769", "18583540376"],
  "maxItems": 3
}

Schedule this input daily in Apify (Schedules tab). Each run returns the current price, stock, buyers count and delivery promise of each offer, so a price cut or a stock-out shows up the next morning. An offer that has ended is named in the log.

Find every company selling a brand

{
  "searchQueries": ["lego 42143", "lego ferrari daytona sp3"],
  "maxItems": 200
}

Open the Sellers view: each row names the seller's company, tax ID, REGON, KRS, representative, city, country and opening hours. Group by sellerTaxId to count how many offers each company runs, look the KRS number up in the Polish court register, and filter sellerCountryCode to spot sellers shipping from abroad.

Read Allegro Czechia, Slovakia or Hungary

{
  "searchQueries": ["lego technic"],
  "country": "cz",
  "maxItems": 40
}

In our test run this input returned 40 offers from allegro.cz in 6 seconds, with Czech titles and parameters, prices and delivery in CZK, the delivery date and the return terms ("Vrácení zdarma"). Set country to sk for euros on allegro.sk or hu for forints on allegro.hu, or paste an address from one of those domains: it is read on its own marketplace. Run the same keyword on each country to compare a product's price across the four markets.

Split a broad keyword into price bands

{
  "startUrls": [
    { "url": "https://allegro.pl/listing?string=rower&price_to=1000" },
    { "url": "https://allegro.pl/listing?string=rower&price_from=1000&price_to=3000" },
    { "url": "https://allegro.pl/listing?string=rower&price_from=3000" }
  ],
  "maxItems": 600
}

A popular keyword has more offers than one search ranks. Three price bands give three searches with their own ranking, so cheap and premium offers both make it into the dataset. Duplicates between bands are removed.

Send the rows to Google Sheets or your database

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("silentflow/allegro-scraper").call(run_input={
    "searchQueries": ["ekspres do kawy"],
    "maxItems": 100,
})

rows = client.dataset(run["defaultDatasetId"]).list_items().items
cheapest_delivered = sorted((r for r in rows if r.get("priceWithDelivery")), key=lambda r: r["priceWithDelivery"])
for r in cheapest_delivered[:10]:
    print(r["priceWithDelivery"], r["price"], r["brand"], r["title"], r["sellerCompanyName"], r["sellerKrs"])

The dataset is also available as CSV or Excel from the Output tab, or at https://api.apify.com/v2/datasets/{DATASET_ID}/items?format=csv with your token, ready for Google Sheets, Looker Studio or a nightly import.

FAQ

What is Allegro? Allegro.pl is Poland's largest online marketplace, the Polish counterpart of Amazon and eBay, where shops, brands and private sellers list their products side by side. Most Polish online shops sell there too.

What does this scraper extract? One row per offer: price, price with delivery, former price and discount, condition, brand, EAN, manufacturer code, category path, every parameter, stock, buyers count, product rating with its verdict, number of ratings and five-star breakdown, delivery price and date, return period and terms, Smart!, free return, best price guarantee and sponsored flags, the seller's login, company, tax ID, REGON, KRS, representative, address, country, opening hours, rating share and Super Seller badge, and every photo.

Do I need an Allegro account or an API key? No. The scraper reads the offers any visitor can see. No login, no password, no Allegro developer app.

Can I search in English? Yes, but sellers write their titles in Polish, so Polish keywords return more offers (telewizor 55 cali rather than 55 inch tv). Brand and model names work in both.

How many offers can I get per keyword? It depends on the keyword. A narrow keyword returns a few hundred offers, a broad one (laptop) many more. To go further, split the keyword into price bands with search addresses, as shown in Advanced usage. maxItems caps the whole run.

Does it return used offers? Keyword, search and category results list new offers. A used offer is read in full, like any other, when you paste its address or its number. Search addresses that ask for used offers (stan=używane) are named in the log and skipped, so you never get new offers when you asked for used ones.

Can I sort the results by price or by newest? Allegro's search order is kept as it is (most relevant first, position gives the rank). Sort the dataset by price, priceWithDelivery, buyersCount or rating in the Output tab or in your spreadsheet. To be sure the cheapest offers of a broad keyword are in the dataset, add a maxPrice, or split the keyword into price bands as shown in Advanced usage.

Does it return the offer description and the warranty? No. The rows carry every parameter of the offer, the EAN, the return terms (returnPeriodDays, returnPolicyLabel, isFreeReturn) and the product's ratings, but not the seller's free-text description, the warranty terms or the text of individual reviews. When the warranty is one of the offer's parameters, it is in parameters.

Can I get the seller's email or phone number? Not from the rows: Allegro does not publish them with the offer. Each business seller comes with what identifies the company in the public registers: company name, tax ID, REGON, KRS, representative, street, city and country, plus the opening hours Allegro shows. The KRS and the tax ID lead to the company's own registered details.

How fresh is the data? Every run reads Allegro live, at the time of the run. Nothing is cached. Schedule the run to follow prices over time.

Can I track the same offers over time? Yes. Paste the offer numbers in Offer IDs and schedule the run. Each run returns the offers' current price, stock and buyers count.

Why is the seller's company empty on some rows? Allegro publishes trader details (company name, tax ID, address) for business sellers. Private sellers have none, and the fields are null on their rows. The REGON, KRS and representative appear when the seller entered them: on the default run, the KRS on 20 rows of 100, the representative on 76.

Why is isSponsored null on some rows? Whether a slot is sponsored is a property of a search result. Offers read from an offer address or an offer number were not found through a search, so the field is null for them.

Does it work for allegro.cz, allegro.sk or allegro.hu? Yes. Set country to cz, sk or hu, or paste an address from one of those domains. Titles, parameters and delivery terms come in that country's language, prices in CZK, EUR or HUF, and url points to the offer on that domain. In our tests the same keyword returned 40 offers from allegro.cz in 6 seconds, 20 from allegro.sk and 12 from allegro.hu in 2 seconds each.

Can I scrape a seller's whole storefront? Not directly. Search the seller's products by keyword, or collect their offer numbers and paste them.

Is it legal to scrape Allegro? The scraper reads public offer pages, the same data any visitor sees without logging in. Check the Legal compliance section below and Allegro's terms for your use case.

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• Europages - Europages Scraper | Suppliers and B2B Companies
• Eventim - Eventim Scraper | Events, Ticket Prices and Venues
• GasBuddy - GasBuddy Scraper | Gas Prices by Station
• Google Hotels - Google Hotels Scraper | Prices, Offers and Ratings
• Homedepot - Homedepot Reviews Scraper | Customer Reviews and Ratings
• Leboncoin - Leboncoin Details Scraper | Full Ad Data and Sellers
• Mercari - Mercari Scraper | Listings, Sold Prices and Sellers
• Vinted Marketplace - Vinted Marketplace Scraper
• Walmart - Walmart Product Scraper
• Alibaba - Alibaba Scraper | Products, Prices and Suppliers
• Amazon - Amazon Product Scraper
• Amazon Marketplace - Amazon Marketplace Scraper
• AutoScout24 - AutoScout24 Scraper
• eBay Listings - eBay Listings Scraper
• Europages Deep Dive Extractor - Europages Deep Dive Extractor | VAT, Decision Makers, ISO Certs
• Pinterest - Pinterest Scraper
• Trip - Trip Scraper | Hotels, Prices and Reviews
• Vinted - Vinted Scraper
• Walmart - Walmart Scraper | Prices, Reviews, Sellers, Availability

💼 Jobs

• ZipRecruiter - ZipRecruiter Jobs Scraper | Salary, Company & Location Filters
• Indeed - Indeed Company Reviews Scraper
• Multi Board - Multi Board Job Scraper
• Glassdoor Job Listings - Glassdoor Job Listings Scraper
• 🔥 Glassdoor - 🔥 Glassdoor Scraper
• LinkedIn Job Search - LinkedIn Job Search Scraper | Salaries & Seniority
• ATS - ATS Jobs Scraper | Greenhouse, Lever and Ashby
• Dice Tech - Dice Tech Jobs Scraper
• iimjobs - iimjobs Scraper | Jobs, Companies and Recruiters
• Jora - Jora Jobs Scraper
• Malt Freelancer - Malt Freelancer Scraper
• Malt - Malt Scraper | Freelance Profiles
• Welcome to the Jungle - Welcome to the Jungle Job Scraper
• All - All Jobs Scraper
• Arbeitsagentur - Arbeitsagentur Jobs Scraper
• Cutshort - Cutshort Jobs Scraper | Salaries, Skills and Companies
• Dice - Dice Jobs Scraper | US Tech Jobs, Salaries, Skills
• Glassdoor - Glassdoor Jobs Scraper
• Indeed - Indeed Jobs Scraper | Job Listings in 73 Countries
• Jora - Jora Scraper | Jobs in Australia, New Zealand, Singapore
• StepStone - StepStone Scraper
• YCombinator - YCombinator Jobs Scraper | Startup Jobs, Salaries and Founders
• Arbeitsagentur - Arbeitsagentur Scraper | German and Austrian Job Board
• Indeed - Indeed Companies Scraper | Reviews, Salaries, Interviews
• Indeed - Indeed Jobs Scraper | NLP Skills
• LinkedIn - LinkedIn Jobs Scraper
• Naukri & NaukriGulf - Naukri & NaukriGulf Jobs Scraper
• Seek - Seek Job Scraper
• Welcome to the Jungle - Welcome to the Jungle Scraper | Jobs and Company Data
• Ziprecruiter - Ziprecruiter Scraper

🏠 Real estate

• SeLoger - SeLoger Scraper | Real Estate Listings
• Anjuke - Anjuke Scraper | Rental Listings, Prices and Agents
• Realtor Rental Listings - Realtor Rental Listings Scraper
• Airbnb Pro Host Contact & - Airbnb Pro Host Contact & Email Scraper
• Bien'ici - Bien'ici Scraper | Property Listings
• Rightmove - Rightmove Scraper
• Trulia Rental Listings - Trulia Rental Listings Scraper
• Airbnb Professional Host - Airbnb Professional Host Scraper | Emails, Phones, SIRET
• Airbnb Search - Airbnb Search Scraper
• Bienici - Bienici Scraper
• Idealista - Idealista Scraper
• Realestate.com.au - Realestate.com.au Scraper
• SeLoger - SeLoger Scraper | French Property Listings and Agencies
• Zillow - Zillow Scraper
• Airbnb Search - Airbnb Search Scraper | Prices, Fees, Amenities, Hosts
• Idealista - Idealista Scraper
• Realtor Rental - Realtor Rental Scraper
• Trulia Rental - Trulia Rental Scraper | US Rentals, Prices, Pet Policy

📣 Social media

• LinkedIn Post Search - LinkedIn Post Search Scraper | Keywords, Hashtags & Profiles
• Facebook Search - Facebook Search Scraper
• Instagram - Instagram Story Scraper | Stories & Highlights
• LinkedIn Leads - LinkedIn Leads Scraper | Sales Navigator Export
• TikTok - TikTok Scraper
• YouTube - YouTube Channel Scraper | Videos, Shorts and Views
• Instagram Engagement - Instagram Engagement Scraper
• Facebook Search - Facebook Search Profiles Scraper | People by Name or Keyword
• Meta Ad Library - Meta Ad Library Scraper
• OnlyFans - OnlyFans Profile Scraper
• TikTok Trend - TikTok Trend Scraper | Trending Hashtags and Videos
• OnlyFans - OnlyFans Creator Scraper
• Skool Community - Skool Community Scraper
• Bilibili - Bilibili Scraper
• Facebook Thread - Facebook Thread Profiles Scraper | Followers, Bios & Engagement
• Kuaishou - Kuaishou Scraper | Videos, Comments and Creator Stats
• LinkedIn Event - LinkedIn Event Scraper
• Reddit - Reddit Scraper | Posts, Comments and Subreddits
• Reddit - Reddit Scraper | Comments, Posts and Users
• Snapchat - Snapchat Contacts Scraper | Phones, Emails and Websites
• Weibo - Weibo Scraper | Posts, Profiles and Engagement
• Xigua - Xigua Scraper | Videos, Creators and Downloads
• Discord - Discord Scraper | Servers, Member Counts and Invites
• Facebook - Facebook Company Scraper | Emails, Phones, Ratings
• Facebook Business Page - Facebook Business Page Scraper
• Kwai - Kwai Scraper | Videos, Creators and Hashtags
• LinkedIn Ads Library - No Cookies - LinkedIn Ads Library Scraper - No Cookies
• LinkedIn Hashtag & - LinkedIn Hashtag & Post Scraper | No Cookies
• Skool Group - Skool Group Scraper
• Snapchat - Snapchat Ads Scraper | Ad Library, Impressions & Targeting
• YouTube - YouTube Transcript Scraper

🏢 Business data

• Tencent - Tencent Scraper | Maps Places, Phones and Ratings
• LinkedIn People Search - LinkedIn People Search Scraper | Profiles & Companies
• LinkedIn Company Search - LinkedIn Company Search Scraper | Profiles & Firmographics
• Company Data - Company Data Scraper | Emails, Phones and Tech Stack
• FanDuel - FanDuel Scraper | Odds, Spreads and Player Props
• ForexFactory - ForexFactory Scraper | Economic Calendar and Forecasts
• Justdial - Justdial Companies Scraper | Business Leads, Phones and Emails
• Kakao - Kakao Scraper | Map Places, Reviews and Phones
• OpenTable - OpenTable Reviews Scraper | Restaurant Reviews and Ratings
• SoftwareAdvice - SoftwareAdvice Scraper | Reviews, Ratings and Pros & Cons
• Teachable Course - Teachable Course Scraper
• Zomato - Zomato Reviews Scraper | Restaurant Ratings and Replies
• 2GIS - 2GIS Reviews Scraper | Ratings, Photos and Owner Replies
• LinkedIn Sales Navigator - LinkedIn Sales Navigator Scraper
• Teachable - Courses, Prices & Instructors - Teachable Scraper - Courses, Prices & Instructors
• Trustpilot - Trustpilot Scraper | Reviews, Ratings and Company Contacts
• Website Tech Stack - Website Tech Stack Scraper

✈️ Travel

• Google Maps - Google Maps Scraper
• Booking.com Hotel - Booking.com Hotel Scraper
• Flight Price - Flight Price Scraper
• Trip - Trip Reviews Scraper | Hotel Reviews and Ratings
• Booking - Booking Scraper | Hotel Prices, Photos, Availability

🎯 Lead generation

• Northdata - Northdata Company Scraper
• ZocDoc - ZocDoc Scraper | Doctors, Reviews and Availability
• UK Companies House - UK Companies House Enricher
• Dealroom - Dealroom Scraper | Companies and Investors
• CNPJ Brazilian - CNPJ Brazilian Company Enricher
• Google Ads Transparency - Google Ads Transparency Scraper
• SIRET - SIRET Company Enricher
• BuiltWith - BuiltWith Scraper | Tech Stacks and Top Sites
• Domain - Domain Enricher
• French Company Prospector - French Company Prospector
• SEC - SEC Scraper | EDGAR Filings and Company Data
• USPTO - USPTO Scraper | Trademark Search and Status
• ZocDoc - ZocDoc Scraper
• Clutch - Clutch Scraper | Agencies, Reviews, Ratings, Services
• Clutch Agency - Clutch Agency Scraper
• Dealroom Startup Data - Dealroom Startup Data Scraper
• G2 - G2 Reviews Scraper
• PagesJaunes - PagesJaunes Scraper | French Business Emails and SIRET
• PagesJaunes - PagesJaunes Business Scraper
• SIRET French - SIRET French Company Enricher
• ThomasNet Suppliers - ThomasNet Suppliers Scraper

🔎 SEO

• Similarweb - Similarweb Scraper | Website Traffic, Rankings and Competitors
• Google News - Google News Scraper
• Apple - Apple Scraper | App Store Apps, Ratings and Charts

📈 Marketing

• Pexels - Pexels Scraper | Photos, Videos and Download Stats

🧰 More tools

• PrizePicks - PrizePicks Scraper | Player Props, Lines and Projections
• Apple - Apple Reviews Scraper | App Store Reviews and Ratings

Support

Need something this scraper doesn't do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations and high-volume plans
• Pricing questions? Check the Monetization tab on the actor page

Response time: usually under 24 hours.

Legal compliance

This Actor extracts publicly available data from Allegro.pl, Allegro.cz, Allegro.sk and Allegro.hu. It does not bypass any login, paywall or CAPTCHA, and it never asks for your Allegro account. Users are responsible for complying with Allegro's terms of service and with the data protection laws that apply to them (GDPR in the European Union, CCPA in California, PIPL in China). Rows can contain personal data: a sole trader's company name is often the owner's name, sellerRepresentative names a person, and the address, tax ID, REGON and KRS identify the business. Handle such rows accordingly, keep only what your purpose needs, and do not use them for unsolicited marketing where the law forbids it. The data returned is informational; verify it before any regulated use.

Built for pricing teams, brand managers and analysts who need Allegro offers as data, not tabs.