The Telegraph shows headline, standfirst, byline and section before its subscription wall. Our Telegraph scraper collects those fields and tracks which stories other outlets follow up.
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
The Telegraph 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. We collect the sections, writers or subjects you name, record the source type on every row, and hand back CSV, JSON, Excel or a push into your warehouse.
Where the brief is about influence, citations from other outlets run in the same pipeline.
We collect only publicly available data - everything a visitor can see on The Telegraph - and we collect it legally.
Article records carry the headline, standfirst, byline, section, publication timestamp and article identifier, as a visitor sees them without a subscription.
Citation records are built without the site: they record where other outlets cite, quote or follow up Telegraph reporting. They show which Telegraph stories drove wider coverage.
Every row carries the collection timestamp and its source type, so article records and citation observations are never mixed.
Citation and follow-up analysis is the strongest product here: which Telegraph stories were picked up, by whom and how quickly.
Section and byline tracking is ordinary structuring and delivery: which desks publish most, which writers cover which subjects, and how that shifts over time.
Limits: we never log in and do not attempt to get past the payment wall, so subscriber-only text is not part of the dataset.
The Telegraph is a major British national newspaper, published online behind a subscription. It covers politics, business, sport and culture for a large UK readership.
Its section fronts and article pages show every visitor the headline, standfirst, byline, section and publication time, while the full text sits behind the subscription. That split sets the shape of every project here: the public layer is collected, the subscriber text is not.
The paper's reach shows up elsewhere too. Other outlets cite, quote and follow up Telegraph reporting, and that trail of citations is a dataset in its own right.
Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan detailsA Telegraph dataset answers two questions. The first is what the paper publishes: which sections, which writers, which subjects and at what pace, built from headlines, standfirsts, bylines and publication times.
The second is the paper's influence: how other outlets cite and follow its reporting. That is a useful dataset in its own right and needs nothing from telegraph.co.uk.
The two answer different briefs. Output tracking suits teams watching what the paper covers and who writes it; influence tracking suits communications teams measuring which Telegraph stories set the agenda elsewhere.
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 the source type attached to the data, and repairs collection when formats change.
You see a sample first, in your format, so you can judge the value before the project starts.
Still unsure? Write to info@scrapeit.io
Yes. Headlines, standfirsts, bylines, sections and publication times are shown to every visitor, and subscriber-only text stays out of the dataset. We collect only publicly available data - everything a visitor can see on The Telegraph - and we collect it legally.
Yes. The ScrapeIt Telegraph API returns headline, standfirst, byline, section, publication timestamp 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.
Citation and follow-up analysis: which Telegraph stories other outlets picked up, when and how. It is built from other outlets and needs nothing from telegraph.co.uk.
No. We never log in and never go behind the paywall. Article records carry what a visitor sees without a subscription: headline, standfirst, byline, section and publication time.
Because article records and citation observations answer different questions. A source type on every row keeps them apart after delivery, when the data is reused by someone who never saw the brief.
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.
The Telegraph data from €169/month. Free project assessment, reply within 1 business day.