Paste Lyreco product or category URLs and get the catalogue back as rows: the name, the price and its currency, availability, the brand, the sku, mpn and gtin, the rating and review count, an image, a link and a description. Fifteen columns, one row per product - read from the structured data Lyreco publishes on the page itself.
The input is either a single product page or a category or search page - the same URL you would be looking at in the webshop.
Every request goes out through the shared proxy pool rather than your own address. Lyreco is not one of the retailers the platform flags as needing a residential proxy, so the default pool is what this one runs on.
The input takes a category or search URL as readily as a single product, so a section of the catalogue becomes one file rather than a click-through exercise.
Sku, mpn and gtin each get their own column. Those are the fields that let a line item be matched against an ERP or a rival's catalogue, which a price on its own never can.
Lyreco is one selectable service on a scraper that serves a range of retailers, and every one of them returns the same fifteen columns with a service field naming the source. Comparing suppliers is a concatenation, not a mapping exercise.
The column set is settled. What fills it is decided by Lyreco rather than by us, and that distinction is the whole of what this page can honestly tell you.
Products are read from the structured data on the page. Retailers publish a machine-readable description of each product alongside the human-readable one, and this scraper reads that. It is the reason the export is clean and consistent rather than parsed out of a layout that changes - and it is also the reason no one can promise you a given field. If Lyreco publishes a gtin for a product, the gtin column carries it; if Lyreco does not, nothing downstream can invent one.
So the honest way to size this up is not to read a fill table on a marketing page - it is to run one category you care about on the free tier and look at what comes back. We have the column names on two independent sources and we are confident about them. We have no populated Lyreco export, which is why you will find no example values, no formats and no fill rates below. Where other pages in this catalogue quote a measured shape, this one deliberately does not.
The export's header row, in order, confirmed against the platform's published column list. Descriptions say what each field is for; they claim nothing about its format or how often it arrives filled - see the note above.
currency, not in this column.Read this dictionary as a list of names, not a promise about contents. The fifteen names and their order are solid - the published column list and the header row of every archived run of this scraper agree exactly. What is not settled is what arrives in them for Lyreco, because we hold no populated Lyreco export: the runs we have are either empty or from a different retailer on the same shared tool, and a fashion marketplace's structured data tells you nothing useful about a B2B office-supplies webshop's. That is also why the mechanism matters more here than a format would: the fields are read from the structured data Lyreco publishes on its own pages, so the export is exactly as complete as that is. query and service are the exceptions - the scraper writes those itself, so they are on every row regardless. If gtin or mpn is load-bearing for your work, run one category on the free tier and look before you build.
A list of URLs and a limit. The input accepts a single product or a whole category, and the limit is what decides the size and the cost of a run.
A few examples of how teams use supplier catalogue data to answer a question they actually have.
Export a category, join on mpn or gtin where they are published, and the overlap between what you buy and what is on offer stops being a manual comparison. The sku column is what you quote back when you want a line re-priced.
Because every retailer on this tool returns the same fifteen columns with a service field naming the source, running the same category against several of them produces one file you can group by rather than several you have to reconcile.
Names, brands, identifiers and images in one pass gives a catalogue team a base to diff against what it already holds - and the url column means anything that looks wrong can be checked at source in one click.
No subscription, no minimum, no recurring bill. Your first 500 rows are on us - after that you pay as you go, at the same flat rate as every other scraper here.
On every new account, one-time. No credit card. Per-query limits, file upload and every export format included - and enough to run one category and see exactly which fields Lyreco publishes.
About $2 per 1,000 products, with no proxy bill on top - this retailer runs on the shared pool. The estimator shows the row count and credit cost before a run starts.
Volume pricing, dedicated workers and an SLA for ongoing monitoring or very large historical pulls. Tell us your numbers and we will put together a quote.
LIVESCRAPER10 at checkout.Another service on the same shared tool, returning the same fifteen columns. Running both over a comparable category is how a supplier comparison stays a group-by rather than a mapping project.
The same fifteen-column shape again, on a different catalogue. Useful when you want a second reading of how much structured data a retailer actually publishes before committing to one.
Short answer: yes for the public catalogue - and this one is a cleaner case than most, because the fields come from data the retailer publishes for machines to read.
A Lyreco product page is served to anyone who opens it, and the structured data this scraper reads is published precisely so that machines can consume it - that is what it is for, and it is how search engines build a product listing. Collecting publicly listed catalogue information for price and assortment research is long-settled practice. No login is involved, no account is touched, and no customer-specific pricing is reachable this way.
That last point deserves emphasis for a B2B supplier. Lyreco negotiates contract pricing with its customers, and what a signed-in account sees is not what the public catalogue shows. This scraper reads the public page, so what you get is list pricing - which is the right basis for a market comparison and the wrong basis for auditing your own contract. If those two get conflated in a report, the report is wrong.
Lyreco's own terms of use restrict automated access, so this is a terms question as well as a legal one - and if your organisation is a Lyreco customer, that contractual relationship is the document that governs, not this page. The rows describe products rather than people, so the personal-data question barely arises here. We run no third-party trackers on the data layer, and your exports self-delete after 30 days.
The questions we hear most. Something else? Talk to us - humans write the answers, not bots.
500 one-time free rows on every new account - no expiry date. Enough to run a category and see exactly which fields come back before you commit to anything. After that $0.002 per row, pay as you go.
Livescraper's Lyreco Products Scraper turns webshop URLs into a product table. You paste Lyreco product or category URLs one per line - or upload them as a CSV, XLSX, TXT or Parquet file - cap the rows per query, and download the results as a clean CSV, Excel or JSON file. Requests go out through the shared proxy pool rather than your own address, and this retailer does not need a residential proxy.
Each row carries fifteen columns: the query and the service that produced it, the product name, the price and its currency, availability, brand, the sku, mpn and gtin identifiers, the rating and review count, an image, a link to the product and a description.
Procurement teams export a category and join it against their own item master on mpn or gtin to see where a supplier's range overlaps what they already buy. Pricing teams run the same category against several retailers on this tool - they all return the same fifteen columns with a service field naming the source - so a supplier comparison is a group-by rather than a mapping project. Catalogue teams use it to keep a product master current, with the url column making anything that looks wrong checkable at source.
One thing determines everything else about this export: the products are read from the structured data Lyreco publishes on the page for machines to consume. That is what keeps the output clean and stable rather than parsed out of a layout, and it is also why no page can promise you a particular field. A column carries a value when the retailer publishes it and is empty when it does not, so the way to find out what you will get is to run one category on the free tier and look. Start free: your first 500 rows cost nothing and need no credit card, and after that it is a flat $0.002 per row.