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.
ScrapeIt runs the work as a managed service. We split your brief into its parts, use the open identifier standard where it answers the question, collect primary-source market data from exchanges and regulators where it does not, and hand back CSV, JSON, Excel or a push into your warehouse.
If you license Bloomberg data, we build within the licence and keep its reference on every row.
We do not collect the public site and do not engineer around its refusal. Your counsel should see the intended use before the project starts, particularly where data will be redistributed.
Identifier records from the open standard carry the financial instrument identifier, the ticker, exchange code, security type, market sector and the instrument name as published. The standard exists precisely so that instruments can be matched across systems, and it is free to use.
Where a client licenses Bloomberg data, records carry what the licence delivers, with the licence reference and permitted use recorded per row.
For market data without a licence, 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 citations and pickups in outlets that permit collection, not from bloomberg.com.
Every row carries the collection timestamp and its source type.
Identifier mapping through the open standard 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, using the identifiers Bloomberg publishes for that purpose.
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 citations in other outlets and shows which stories shaped the market conversation, without touching the site.
Limits: we do not collect bloomberg.com content, we do not attempt to get past its 403, and we do not reproduce licensed data outside a licence. If a brief needs terminal data, the answer is a licence from Bloomberg, and we say so first.
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 sold to financial institutions under licence. The news operation is large and respected, and it is one product inside that business.
The public website is the news front end, and it is not where the data lives. Requests to it returned 403. Its crawl rules run to several hundred lines, name the major AI crawlers individually for exclusion, and for general crawlers close the search, company search and account areas.
The file opens with a joke: the Three Laws of Robotics, followed by an invitation to anyone reading to apply for a job. It is the only crawl rules file we have seen with a recruitment pitch, and it is also a reminder that the people who wrote it know exactly what crawlers are doing.
The part Bloomberg deliberately publishes for open use sits elsewhere: the Open FIGI identifier standard and its free programmatic interface, which answer a real and common data problem.
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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. That is Bloomberg's core licensed product and it is not on the public website to be collected. The legitimate routes are a Bloomberg licence, or the primary publications of exchanges and regulators, which are often free and are the original source anyway.
The second is instrument identification: matching securities across a client's systems. Bloomberg publishes an open standard for exactly this, with a free interface, and building a scraper instead of using it would be solving a solved problem badly.
The third is news: what Bloomberg reported and when. That is a licensing question for the text, and a measurement question for the coverage, which can be answered from citations elsewhere.
The site's own answer to anonymous requests is 403, and its crawl rules name AI crawlers for exclusion. We do not treat either as an obstacle to engineer around. Splitting the brief almost always produces a better dataset than a crawl would have, and one the client can defend.
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 through the open standard, 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.
No, and the website would not give it to you anyway. Market data is Bloomberg's licensed product, not public page content. The routes are a Bloomberg licence, or the primary publications of exchanges and regulators, which are often free and are the original source.
Yes - the Open FIGI identifier standard, with a free programmatic interface. It exists so that financial instruments can be matched across systems, and it solves one of the most common problems people try to scrape their way around.
We do not try. A refusal to anonymous requests, alongside crawl rules that name AI crawlers for exclusion, is a clear position. Splitting the brief into market data, identifiers and news almost always produces a better and more defensible dataset.
Yes, through citations and pickups in outlets that permit collection. That shows which stories shaped coverage and when, without collecting the site itself. The text of the reporting is a licensing matter.
The file opens with the Three Laws of Robotics and then invites anyone reading it to apply for a job. It is a light touch in a serious file - and a reminder that the people who wrote it know exactly what crawlers do.
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.
Scrapeit Sp. z o.o.
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