The FT wrote its AI position into the one file every crawler reads first. A licence for research does not quietly extend to training a model.
Plans from €169 a month · Free project assessment · Reply within 1 business day
CSV · Excel · JSON · XML · FTP · SFTP · Amazon S3 · Google Cloud
API, JSON feed or CSV, XLSX and JSON files
ScheduleOne-time, monthly, weekly, daily or 3 times a day
Financial Times pages, filters, fields and a schedule
Built, monitored and repaired by our team
API, JSON feed or CSV, XLSX and JSON files
ScrapeIt runs the work as a managed service. You name the sections, topics or companies; we build the collector, record headline, standfirst, byline, section and timestamps on every row, and hand back CSV, JSON, Excel or a push into your warehouse.
Anti-bot handling, proxy rotation and rendering are part of the service, and we never log in or go behind the paywall.
Article records carry the headline, standfirst, byline where the page shows it, section, publication and update timestamps and the article identifier, as the public pages display them.
Citation records are a separate table built without the FT site: where other outlets cite or quote FT reporting, showing which FT stories shaped wider coverage.
Every row carries the collection timestamp and its source type.
Citation analysis is the strongest product: which FT reports are cited, by whom, how quickly and in what context, joined to the headline, section and publication time the FT gave each story.
Headline tracking follows the public pages over time: each run records headline, standfirst, section and update timestamp, so a retitled story or a revised standfirst shows up as a dated change.
The Financial Times is one of the most influential business newspapers in the world, published behind a subscription and read closely by finance, policy and corporate audiences.
Part of it is still public. Front and section pages list each story with its headline, standfirst, section and timestamp, and every article page opens with its headline and standfirst before the paywall starts.
We collect only publicly available data - everything a visitor can see on the Financial Times - and we collect it legally. We do not log in and do not go behind the paywall.
Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan detailsThe FT is read closely by finance, policy and corporate audiences, so what it puts in front of them is itself a signal. A dated series of headlines, standfirsts and sections shows which companies, markets and policy themes the paper covers and how that mix shifts over time.
Most FT data briefs are really about influence: which FT stories moved markets or set agendas. That question is answered from two sides: what the FT put on its front and section pages and when, and how other outlets cite the FT afterwards.
Learn how to use web scraping to solve data problems for your organization
Data scraping is the wide term that includes documents, scans and old screens; web scraping is the part that works on websites. We compare sources, daily work, output and cost drivers, give a briefing checklist and walk through two of our projects.
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.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team builds the pipeline, keeps it running and repairs collection when formats change.
You see a sample first, in your format. The sample covers the sections or companies you track, so you can judge the value before committing.
Still unsure? Write to info@scrapeit.io
Yes, the public layer: front and section pages and the part of each article page shown before the paywall, with headline, standfirst, byline where shown, section, timestamps and article identifier. Anti-bot handling is part of the service, and delivery is CSV, JSON, Excel or a push into your warehouse.
Yes. The ScrapeIt Financial Times API returns headline, standfirst, byline, section, timestamps and article identifier 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. We collect headlines, standfirsts, bylines, sections, timestamps and article identifiers from the public pages, plus citations of FT reporting in other outlets. We collect only publicly available data - everything a visitor can see on the Financial Times - and we collect it legally, without logging in or going behind the paywall.
Yes. Each run records headline, standfirst and update timestamp, so a retitled story or a revised standfirst appears as a new row with its collection time, and the versions stay side by side.
Yes. Citations of FT reporting in other outlets show which stories shaped coverage, how fast and where. That answers most influence questions without touching ft.com.
You share your needs, expectations, and desired timeframe. We'll suggest the best solution based on your request and budget.
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
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.
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.
Tell us which sites, which fields and how often. A couple of lines is enough to start.
Financial Times data from €169/month. Free project assessment, reply within 1 business day.