Paste an Allegro search, category or offer URL and get the products back as rows: the title, the price and its currency, the condition, the seller, the rating and review count, an image and a link to the offer. One row per product. No account, no proxy pool, no parser to keep alive.
The input is whatever Allegro page you are looking at - a search you ran, a category you are browsing, or a single offer.
One row per product, each tagged with the query it came from - so a run across twenty searches still reconciles back to your input list.
A search you already ran, a category you are browsing, or a single offer - paste whichever you have. There is no separate mode to pick and nothing to reformat before the run.
Allegro sits behind DataDome, which is why a hand-rolled script on an office IP comes back with a challenge page instead of products. Residential routing, rate limiting and IP rotation happen on our side; from yours it is a form or an API call.
The price alone does not tell you whether an offer is competitive. Who is selling it, what they are rated and how many reviews that rating rests on all arrive in the same row, so a price comparison keeps its context.
Each row carries the offer as Allegro's results show it: the title, the price and the currency it is quoted in, the condition, the seller, the rating and review count, an image and a permalink to the offer.
Titles come back verbatim, exactly as the seller wrote them, with no cleanup applied - which is what you want if the next step is matching offers to a catalogue. The column list below is the header row of real run exports rather than a specification, and it is worth reading the note under it, because those runs are the reason this page describes the schema and not the value formats.
Taken from the header row of real run exports, identical across them and identical to the column list the platform ships. Read the note underneath before you write a parser: these names are verified, and the value formats are not.
price. Allegro is a Polish marketplace, so złoty is the reasonable expectation - but no run returned a row, so this page does not name a code.One thing to know before you write code against this. Allegro sits behind DataDome, and the free demo pool does not get past its challenge. An export header row still names its columns, which is why the eleven column names above are trustworthy. What we have not seen is the shape of the values, so this page deliberately claims no price format, no rating scale, no currency code and no condition vocabulary, and does not say whether the JSON export carries a rank field the workbook omits. Pull a free run and read the first rows before you assume any of them.
A per-query limit decides what a run costs and how much lands in the file. It is chosen before the job starts, alongside how you hand over the list of URLs.
A few examples of how teams use marketplace product data to answer a question they actually have.
Export a category on a schedule and watch the spread rather than the headline price. Where your offer sits inside that spread is the number that moves conversion, and it changes without anyone telling you.
The seller, rating and review columns turn a price list into a map of the competition. A cheaper offer from an account with nine reviews is a different threat from the same price under an established shop.
Allegro is where a great deal of Polish e-commerce happens, so its listings are a practical proxy for what a category looks like locally. Pull the breadth, the price band and the condition mix before committing to a launch.
No subscription, no minimum, no recurring bill. Your first 500 rows are on us - after that, pay-as-you-go at the same flat rate as every other scraper here.
Every new account, one-time. No credit card required. Per-query limits, file upload and every export format included.
Roughly $2 per 1,000 products. The pre-flight estimator shows the row count and credit cost before a run starts - no surprise bills, no compute units to translate.
Volume pricing, dedicated workers and an SLA for continuous monitoring or very large historical pulls. Tell us your numbers and we will quote.
LIVESCRAPER10 at checkout.The cross-border benchmark. Amazon and Allegro compete for the same Polish basket in a growing number of categories, so the two exports read well against each other.
The same job on a US local marketplace - title, asking price, city and state, and a link to each listing. Useful if you are comparing how a category behaves in two markets.
Short answer: yes for the public offer content - and the only party named in this export is a shop, not a private person.
Offers on Allegro are published to be found. The title, the price, the condition, the seller, the rating and the image are shown to anyone who runs the search, signed in or not. Collecting publicly visible listing data for price research is long-established practice, and nothing here touches a login, a basket or a paywall.
The one field worth thinking about is seller, which carries the shop or account name Allegro displays. On a marketplace that is usually a business rather than an individual, but Allegro hosts private sellers too, so treat it as potentially personal data and handle it accordingly - Poland is in the EU and the GDPR applies to what you do with it downstream, not to the fact that it was public.
Allegro's own terms restrict automated access, so this is a terms question as well as a legal one - if you have a contractual relationship with the site, check it. We run no third-party trackers on the data layer, and your exports auto-delete after 30 days.
The questions we hear most. Anything else? Talk to us - humans, not bots, write the answers.
500 one-time free rows on every new account - no expiry. After that it is $0.002 per row, pay-as-you-go - no card on file until you say so.
Livescraper's Allegro Scraper turns marketplace URLs into product data. You submit allegro.pl listing, category or offer URLs - typed one per line, or uploaded as a CSV, XLSX, TXT or Parquet file - cap the rows per query if you want to, and download the results as a clean CSV, Excel or JSON file.
Each row carries the offer as Allegro's results show it: the title exactly as the seller wrote it, the price and the currency it is quoted in as separate columns, whether the item is new or used, the seller, that seller's rating and the number of reviews behind it, a product image and a permalink to the offer itself.
Pricing teams export a category on a schedule and watch the spread rather than the headline number, because where an offer sits inside that spread is what moves conversion. Strategy teams read the seller, rating and review columns together, since a cheap offer from a nine-review account is a different competitor from the same price under an established shop. Teams weighing a Polish launch use the breadth, price band and condition mix as a practical read on what a category looks like locally.
One practical note up front: Allegro is protected by DataDome, which is why a hand-rolled script tends to return a challenge page rather than data, and why every run export behind this page came back empty. Residential routing, rate limiting and IP rotation are handled on our side, so from your end it is a form or an API call and there is no proxy pool to run. The column names on this page are taken from the surviving export headers; pull a free run to see the values before you build on them. Start free: your first 500 rows cost nothing and need no credit card, and after that it is $0.002 per row, flat.