Bloomberg is a data company that also publishes news. Asking to scrape its website for market data is asking the shop window for the warehouse.
Plans from €169/month · Free project assessment · Reply within 1 business day
ScrapeIt runs the work as a managed service. We split your brief into its parts, map instruments to their identifiers, collect primary-source market data from exchanges and regulators, add Bloomberg's public reporting where coverage matters, and hand back CSV, JSON, Excel or a push into your warehouse.
Handling anti-bot protection - pacing, proxy rotation and rendering - is part of the service.
We collect only publicly available data - everything a visitor can see on Bloomberg - and we collect it legally.
Identifier records carry the financial instrument identifier, the ticker, exchange code, security type, market sector and the instrument name as published. The identifier exists precisely so that instruments can be matched across systems.
Market data records come from the primary sources the market itself publishes: exchanges, regulators and central banks. We record the source on every row, because a price from an exchange notice and a price from a vendor feed are different claims.
News coverage records, where a client wants to measure Bloomberg reporting, come from bloomberg.com itself and from citations and pickups in other outlets.
Every row carries the collection timestamp and its source type.
Identifier mapping is the most immediately useful output here, and it is the one clients least expect: reconciling tickers, exchange codes and instrument types across internal systems through the financial instrument identifier.
Primary-source market data from exchanges and regulators covers much of what people ask Bloomberg for, and it has the advantage of being the original publication rather than a redistribution.
Coverage measurement of Bloomberg reporting runs on the site itself and on citations in other outlets, and shows which stories shaped the market conversation.
Limits: we never log in and never go behind a paywall, so terminal data and subscriber-only pages stay out of scope.
Bloomberg is first a financial data company. Its core business is the terminal and the data products around it: prices, reference data, fundamentals and analytics for financial institutions. The news operation is large and respected, and it is one product inside that business.
The public website is the news front end: what Bloomberg reported and when.
Next to the news sits instrument identification: the financial instrument identifier with its ticker, exchange code, security type and market sector, which answers a real and common data problem - matching securities across systems.
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Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan details →Almost every brief that names Bloomberg is really three different requests, and each has a different honest answer.
The first is market data: prices, fundamentals, reference data. We collect it from the primary publications of exchanges, regulators and central banks, which are the original source anyway, and record the source on every row.
The second is instrument identification: matching securities across a client's systems. We deliver the financial instrument identifier with its ticker, exchange code, security type and market sector, mapped against the instruments you hold.
The third is news: what Bloomberg reported and when, and which of its stories other outlets cited and followed.
Splitting the brief almost always produces a better dataset than a single crawl would, with each part collected from the source that answers it.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team maps instruments to their identifiers, maintains collection from primary sources as their formats change, and keeps provenance on every row.
You see a sample first, in your format, over the instruments you actually hold, so you can check the identifier mapping against your own systems before anything else.
Yes, from the sources that publish it first. We collect prices, fundamentals and reference data from the primary publications of exchanges, regulators and central banks, pair them with instrument identifiers and record the source on every row.
Yes. The ScrapeIt Bloomberg API returns the financial instrument identifier, ticker, exchange code, security type, market sector and instrument name as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files or straight into your database.
Yes. What Bloomberg reported and when is publicly available data - everything a visitor can see on Bloomberg - and we collect it legally. We never log in, so terminal data and subscriber-only pages stay out of scope.
Yes, from the site itself and through citations and pickups in other outlets. That shows which stories shaped coverage and when.
Through the financial instrument identifier. Each record carries it with the ticker, exchange code, security type, market sector and instrument name as published, so tickers and exchange codes reconcile across your internal systems. You check the mapping on a sample over the instruments you hold before anything else.
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.
Bloomberg data from €169/month. Free project assessment, reply within 1 business day.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582
