We run the crawl on your schedule and return a table. Daily suits ordinary price and stock work. Hourly suits launch weeks and campaign periods, when the campaign flags and the sold-out states move fastest and a Verkkokauppa price change is worth catching the same afternoon.
Output is CSV, JSON, XLSX or a REST endpoint your systems poll. The usual shapes are a full catalogue snapshot keyed by sku and EAN, a delta feed reporting only what moved since the previous run, a per-location stock panel spanning the four stores and the Vantaa pickup point, and a category level assortment file for range tracking. Matching Verkkokauppa products to your own SKUs by EAN-13 or manufacturer part number is part of the setup, not a separate project.
Two layers carry the record in the same document: a JSON-LD Product block and a hydration state. A plain HTTP fetch returns both, so no headless browser is needed for detail pages.
Colour variants share one URL but exist as separate product ids, each with its own price and its own stock. A Verkkokauppa scraper keyed on the URL alone will under-count the range, so we key on the variant id and carry the parent URL beside it.
Behind the Näytä kaikki lisätiedot control, meaning show all details, the page exposes two panels that are rare on a retail site.
Hintapuntari is a price chart. The site's own explanation names two series: Hintakehitys, the product's price history at Verkkokauppa.com, and Markkinahinta, an average of the five cheapest retailers' current prices taken from the Finnish comparison site Hinta.fi. Verkkokauppa.com published a price tracking service in November 2016, so this is a long standing feature rather than a recent addition.
Myyntihistoria, the sales history panel, is the second. Its labels are Lisätty valikoimaan for the date a product entered the range, Viimeksi saapuneet for the last inbound shipment and Viimeksi myyty for the last sale, with quantities in kpl and the same ceiling at yli 25 kpl. Placed beside the stock buckets, it puts arrival dates, sale dates and unit counts on a single row.
This matters for discount verification. Under the Omnibus directive, as applied in Finnish consumer law since 1 January 2023, a seller advertising a reduction must state the lowest price of the preceding 30 days. The price object supplies original next to current with discountAmount and discountPercentage, and the price chart supplies the trajectory those numbers sit on, so a claimed reduction can be checked against the seller's own published record.
Verkkokauppa.com Oyj is a Finnish retailer selling electronics, home appliances, toys, garden goods and general merchandise online and through four stores: Helsinki in the Jätkäsaari district, Pirkkala, Raisio and Oulu, plus a pickup warehouse in Vantaa. It has traded since 1992 and its shares are listed in Helsinki.
The catalogue runs in three locales under /fi/, /en/ and /sv/, and sitemap entries cross-link them with the hreflang values fi-fi, en-fi and sv-fi. Reading the sitemap index declared in robots.txt on 31 August 2026, we counted twelve Finnish product shards, the first holding 5,000 URLs and the last 966, alongside eighteen further shards listing products that have left the range. The same index points at a category file carrying 5,440 category URLs, 1,814 of them Finnish.
Category paths carry two segments: a stable English slug followed by a localised one, so a category keeps the same key in Finnish, Swedish and English. Product paths carry a numeric id followed by a slug, and that id is the same value the page publishes as sku. Both patterns make a Verkkokauppa scraper cheap to keep stable, because the identifier survives a slug rewrite and a language switch. Category grids are drawn in the browser, so a plain fetch of a listing returns placeholders; product pages are server rendered and return the whole record.
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Most retailers publish a boolean. Verkkokauppa.com publishes integers. The hydration state on a product page carries three parallel stock buckets, named shipment, pickup and stores, and each is keyed by a short location code with a unit count against it.
Reading one product page on 31 August 2026, a single colour variant reported 16 units for shipment from the Helsinki warehouse, 0 at the Vantaa pickup point and 25 at the vendor. Pickup showed 16 in Helsinki, 6 in Pirkkala, 6 in Raisio and 2 in Oulu. Shelf stock in the same record was 4 in Helsinki and 2 in Oulu. The codes are terse: js for Helsinki, then pir, rai, oul and pak, with parallel entries for parcel locker collection.
Every figure carries a stockStatus field reading either exact or above. Above is a ceiling, not a number: the interface renders it as yli 25 kpl, over 25 pieces, so larger holdings are reported as a floor. Pickup entries also carry minEstimate and maxEstimate as ISO 8601 durations, which is how the site expresses a collection window in minutes.
Two consecutive reads of the same variant therefore produce a real depletion figure per location. That is what makes Verkkokauppa data unusual against the rest of Nordic retail: sell-through, restock timing and the imbalance between shelf and warehouse are measurable rather than inferred.
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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 builds and operates crawlers as a managed service. You state the fields and the cadence; we write the parsers, run them, monitor them and repair them when the front end changes. Layout churn on a retail site is routine, and absorbing it is our work rather than yours.
Collection covers public product and pricing data only, and no customer data is gathered. Scraping runs at a measured request rate, and delivery is CSV, JSON, XLSX or an API on the schedule you set.
No documented public product API is offered to outside developers. The site's own front end calls internal services on separate service hosts for availability and search, and those are not published as a third party interface. The robots.txt on the main domain disallows /api/ and /resp-api/ for every crawler. We therefore work only from what the site publishes for public consumption: product pages, category pages and the sitemap index named in robots.txt. That is sufficient, because product pages are server rendered and already contain the price block, the identifiers and the per-location stock counts.
Per store, as unit counts. Each product page carries separate shipment, pickup and shelf figures for Helsinki, Pirkkala, Raisio, Oulu and the Vantaa pickup point, each with an integer and a stockStatus value of exact or above. Where the status reads above, the site caps the display at yli 25 kpl, so we record 25 as a floor and flag the row rather than reporting a false precision. Values are recorded with the timestamp of the read, since they change through the trading day.
By gtin13, the EAN-13 barcode, which the product page publishes as a structured field, and by mpn, the manufacturer part number, where the vendor supplies one. Both come out of the same record as the price, so no second lookup is required. The numeric product id doubles as sku and stays constant when the URL slug is rewritten. Colour and capacity variants get their own ids, and we deliver them as separate rows tied to a parent so your matching does not collapse them.
It depends on how many products you follow and how fast you need them. A narrow watchlist of a few hundred products can be refreshed several times a day; a full catalogue sweep is normally a daily job. Prices and campaign flags move on a different rhythm to stock counts, so we often split them: a cheap daily pass over the whole range for price and assortment, and a tighter loop over the products where unit counts actually matter to you.
Yes. Every product and category exists under /fi/, /en/ and /sv/, and the sitemap cross-links the three with hreflang values. Names, descriptions and category titles are translated; identifiers, prices and stock figures are shared. Because the first segment of a category path is a stable English slug, the same category can be joined across languages without a lookup table. Most buyers take Finnish as the primary feed and add English for internal reporting.
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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