Website Scraping

What the service includes

We collect data from the sites you need and turn it into a structured spreadsheet or database. The work covers gathering product catalogs with prices and specifications, company contacts, listings, reviews and any other public information from pages. We tune the collection to your goal: filling your catalog, building a base for cold sales, analyzing competitors' assortments, aggregating offers from different sources. We export the results to a spreadsheet, a database, a file or directly into your system, and when needed we put the collection on a schedule for regular updates. We work with publicly available data and respect the sites' limits. The outcome: you get a ready structured dataset instead of manually copying hundreds of pages, and it can be updated automatically.

How it actually works

Collection is built on collector actors that visit the site's pages, find the needed elements by their structure and pull the values into dataset fields. We describe to the actor what to collect: which product fields, where the price is, where the specifications are, how to navigate through catalog pages and product cards. The collector works through the site with paginated navigation, carefully spacing requests over time so as not to create load, and returns a table where each row is a product, a company or a listing. The data is then normalized: prices and units are standardized, texts cleaned, duplicates removed, categories reconciled. The finished dataset is exported to the format you need or into your database, and a repeat scheduled run keeps the data current.

Where website data collection came from

Automated data collection from websites is as old as the web itself: the first web robot was the World Wide Web Wanderer, which Matthew Gray deployed at the Massachusetts Institute of Technology in June 1993 to crawl and measure the web. As early as 1995, BargainFinder appeared — created at Andersen Consulting under Bruce Krulwich — the first price-comparison agent that crawled online stores itself and gathered their offers. That was the start of an entire industry of collecting commercial data from websites. Apify, the cloud collection platform we work on, appeared in 2015 and moved scraping out of fragile scripts into a managed, industrial process with ready-made actors and storage. We use precisely this mature toolkit, not home-grown parsers that break at the first change in markup.

Why accuracy and legality are critical

Collected data is only useful when it's accurate and gathered cleanly. A careless parser mixes up prices, loses some product cards or duplicates records — and a catalog filled with it will have to be redone by hand. That's why the core engineering work isn't the page visit itself but normalization: reconciling fields, standardizing prices and units, deduplication, mapping to categories. The legal side matters just as much: we collect publicly available data, space requests over time so as not to create load, and don't bypass authentication or protections — that's what separates data collection from harming someone else's site. We're upfront about what's publicly available and what requires clearance. As a result, you get a reliable, ready-to-use dataset, not a set of random rows carrying legal risk.

What stack we work on

The foundation is the Apify platform and its collector actors, which visit sites, pull the needed fields and store them in a structured dataset, running in the cloud. For complex sites with dynamic loading we use collectors on a managed browser that see the page like a real user. Orchestration and scheduling run on n8n, tying collection, cleaning and export into a single flow. We store the result in a spreadsheet, a database, a file or directly in your system. For regularly changing data we set up an automated run with updates. The stack is manageable and portable: the collection logic is explicit and stays with you, and it can be changed for new sites without depending on a single home-grown script.

When the key tools appeared

Website data collection tools took shape across three milestones. The World Wide Web Wanderer web robot appeared in June 1993 and set the very idea of automatically crawling pages. The first price-comparison agent, BargainFinder, went live in 1995, showing the commercial value of collecting data from other people's sites. The Apify cloud scraping platform was founded in 2015 by Jan Curn and Jakub Balada and turned scattered parsers into a managed platform with ready-made actors. The n8n orchestrator launched as an open project in 2019 and made it possible to tie collection and processing together without manual code. We use the current generation of these tools, so collection is resilient to change and scales.

Why you can trust us with this

Our team's combined IT experience exceeds 45 years, and we treat website data collection as an engineering task on an ongoing basis. We take a systematic approach: we fix what to collect and from where, configure the actors, always clean and normalize the data and check it for completeness and duplicates before handover. We keep the legal framing honest — public data, careful load on the site, no bypassing protections. The data and the pipeline stay yours: you get both the result and a configured process you can repeat without us. We'll tell you plainly where collection pays off and where a source is unreliable or carries risk. In the end, you get a ready structured dataset for a specific task, not a mountain of raw rows.