You set the scope - a category subtree, a reference list, a set of stores, one country or several - and the cadence. We build the crawler, run it on our own infrastructure, monitor it, and repair it when Leroy Merlin changes a template. Output arrives as CSV, JSON, XLSX or through an API, on a schedule, with the same column names every run.
Every row keeps the raw reference, the seller name and the capture timestamp, so price history and offer changes stay reconstructable later. We work within the rules the site publishes and at a request rate that does not add load, and we collect no personal data.
A product resolves from a URL shaped as /produits/(slug)-(number).html, and the trailing number is the reference the rest of the site keys on. On the quarter-round moulding page ending -72593906.html, that value turns up three times: as sku in the JSON-LD Product block, in the analytics payload, and as the hidden reflm field on the add-to-cart form. The slug ahead of it is decorative. These are the fields we normally extract.
The store comes first. Leroy Merlin price and availability are contextual: the site carries a chosen store as a numeric storeId, and the same reference can read differently depending on which store is set. Store pages live at /magasins/(city).html and are listed in sitemap-store1.xml. The published robots.txt disallows the in-store availability endpoint and any URL carrying a storeid parameter, so store-level scope is something we agree up front rather than sweep blindly.
Listing navigation comes second. A category page prints its total as a count of "résultats" and offers sorts named "Meilleures ventes", "Prix croissant" and "Prix décroissant", but pagination is a select control labelled "Choisir un numéro de page" whose options read "1 sur 2". There is no next-page link to follow, so the crawler drives the page parameter itself. robots.txt separately disallows the filters, sort and limit parameters and the search paths.
Delivery comes third. Leroy Merlin publishes four delivery modes keyed to the weight and volume of the order, and eligibility is carried on the product as a badge such as "Livraison dès demain à domicile" (home delivery from tomorrow). For heavy goods, kerbside drop and the paid room-of-choice option are separate lines. If bulky logistics is your subject, that belongs in a column.
Leroy Merlin is the DIY, home improvement and garden chain of the French group Adeo. It trades in France, Spain, Italy, Poland, Portugal, Romania, Greece, Ukraine, Brazil and South Africa, and each country runs a separate site on its own domain: leroymerlin.fr, leroymerlin.es, leroymerlin.it, leroymerlin.pl, leroymerlin.pt, leroymerlin.ro, leroymerlin.com.br and leroymerlin.co.za. The path segment is translated with the country, so a French product sits under /produits/ while the Spanish equivalent sits under /productos/, and the sitemap filenames follow the same habit: sitemap-product1.xml in France, sitemap-productos1.xml in Spain, sitemap-produkty1.xml in Poland.
The group layer shows through in the markup. Product images resolve to media.adeo.com rather than a Leroy Merlin host, and the label for a declaration of performance reads ADEO Declaration of performance (DoP) even on a French page. Adeo also runs Weldom, Bricoman, Bricocenter, Obramat, Tecnomat and Obramax, which matters if you are comparing assortments across fascias rather than across borders.
Two catalogues share the same shelf. Leroy Merlin sells its own range, and a Mirakl marketplace layer, live in France since December 2020, puts third-party merchants beside it. Both appear in the same category trees and the same result lists, so a usable Leroy Merlin data set has to record which of the two an offer came from and which merchant holds it.
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DIY pricing in France is fought inside a narrow band, and Leroy Merlin sets a lot of it. Suppliers and brands scrape Leroy Merlin to see how their own references are listed, priced and described next to a marketplace merchant selling the same item a few euros lower on the same page. Competing retailers watch the Leroy Merlin price on the lines that drive footfall - paint, insulation, tiling, decking, power tools - and they want the movement rather than a single snapshot.
Marketplace sellers use it differently. They need to know where their listing sits inside the "autres offres" (other offers) stack, whether Leroy Merlin itself holds the lead position, and how that gap moves week to week. That is a per-reference, per-seller question, and it cannot be answered from a feed the seller pushed in.
Assortment work is the third case. Category teams want the attribute table, because a section in millimetres and a pack quantity are what let you match a French listing to a line in your own PIM. Range planners want to know what appeared and what disappeared between two runs, and only a repeated crawl answers that. Store-level teams add a fourth question on top: whether a reference that reads as available nationally is actually sitting in the stores they care about.
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Learn MoreLearn how to use web scraping to solve data problems for your organization
If you sell online, run a marketplace, or advise e-commerce clients, you already know why eBay matters: it’s one of the few places where big retailers compete side by side with thousands of small merchants and private sellers.
E-commerce teams do not just need “some” competitor data anymore. They need a continuous stream of real prices, discounts, stock levels, reviews, and seller behavior from the platforms that actually shape their markets.
Amazon provides valuable information gathered in one place: products, reviews, ratings, exclusive offers, news, etc. So scraping data from Amazon will help solve the problems of the time-consuming process of extracting data from e-commerce.
ScrapeIt is a managed web scraping agency. We do not sell a library, a proxy pool or a browser plugin. We take the requirement, build the crawler, keep it running as the target site changes, and deliver clean, deduplicated data in the format your team already works in. You get a named contact, an agreed schedule, and a file or endpoint that still works months after the first delivery, because someone here is watching it when the site changes.
Not for the public catalogue. Leroy Merlin Brazil runs a developer portal at developers.leroymerlin.com.br listing authentication, store locator, product catalogue, stock, marketplace and purchase order APIs, and a French developer portal exists at developer.leroymerlin.fr. Both sit behind a developer account and an issued key, and both are aimed at partners and sellers integrating into Leroy Merlin. The Mirakl feed tooling sold around the marketplace runs the same direction: it pushes a seller's own listings in, it does not read the catalogue out. If you need leroymerlin.fr prices, offers and store availability as a dataset, scraping the site is the practical route.
Store context is a real dimension on this site, not a display detail. The chosen store is carried as a numeric storeId, and availability wording changes with it. We scope store-level work explicitly: you give us the store list, we agree the volume and the rate, and we run it within the constraints the site publishes. Where a store-level figure is not exposed to a normal visitor, we say so rather than guess it.
By the seller string on the offer. The site prints "Vendu par" (sold by) and "Vendu et expédié par" (sold and shipped by) with a vendor name that is either LEROY MERLIN or a third-party merchant, and a merchant name links through to that seller's own page. Where several sellers list the same reference, the page shows an other-offers counter. We output a seller column and an is-marketplace flag on every row, so first-party and third-party lines never get averaged together.
Yes. Each country is a separate site with its own domain, its own catalogue and localised paths, so leroymerlin.es uses /productos/ where leroymerlin.fr uses /produits/. We treat each domain as its own dataset and match products across countries on GTIN and attributes rather than assuming a reference carries over. Tell us which markets you need and we scope them together, with one schema across all of them.
Unevenly, which is why cadence is a decision rather than a default. Price, promotions and store-level availability move fastest, and the marketplace layer moves with them as merchants come and go on a reference. Descriptions, attribute tables and document attachments are comparatively stable. The garden and heating ranges swing hard by season, so category coverage is worth re-running even when individual records look quiet. Most clients run daily on a price panel and weekly or monthly on a full catalogue sweep.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
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