Scrape full article text, author profiles, publication metadata, tag taxonomies, engagement signals, and internal link structures from WordPress, Medium, Substack, Ghost, Blogger, and any custom CMS — deduplicated, cleaned, and structured for content research, SEO intelligence, or AI training pipelines.
Blog content scraping is the automated extraction of structured data from blog posts across any publishing platform. This includes the full article body, headline, author details, publication and last-updated dates, category and tag taxonomy, estimated read time, social share counts, comment counts, internal and external links, canonical URLs, and SEO metadata. Collected at scale, blog content becomes a rich dataset for understanding industry discourse, content performance patterns, and knowledge distribution across the web.
Blogs are where original thinking, domain expertise, and emerging trends first appear in written form — often months before they reach mainstream media or formal research. For SEO professionals analysing competitor content strategies, data scientists building NLP training corpora, content teams benchmarking their output, and market researchers tracking industry sentiment, systematically collected blog data provides signal that no other source can match.
The technical challenge is diversity: there is no universal blog API. WordPress, Medium, Substack, Ghost, Blogger, and thousands of custom CMSes each expose content differently. DataFlirt handles this platform diversity with a library of platform-specific parsers and a fallback general-purpose extractor — ensuring full content capture regardless of the CMS, without relying on RSS feeds alone.
Comprehensive extraction built for reliability, accuracy, and scale.
Complete article body text including headings, paragraphs, blockquotes, lists, code blocks, and embedded content — not just summaries.
Author name, bio, social links, post history, domain authority, and follower/subscriber count where available.
Comment counts, social share counts, estimated read time, and reaction/clap data from platforms that expose these metrics.
Full tag lists, category hierarchies, topic clusters, and SEO metadata including meta title, description, and canonical URL.
Original publish date, last-updated date, and posting frequency patterns — essential for content freshness and cadence analysis.
Internal link anchors and targets, external link domains, and outbound link counts — the backbone of content topology analysis.
Every field you need, structured and ready to use downstream.
A proven process that turns any source into clean structured data — reliably.
{ "url": "https://techcrunch.com/2025/06/08/ai-agents-enterprise/", "platform": "wordpress", "title": "AI Agents Are Reshaping Enterprise Software", "author": "Kyle Wiggers", "published": "2025-06-08T14:22:00Z", "word_count": 1847, "tags": ["AI", "Enterprise", "Automation"], "category": "Artificial Intelligence", "body_text": "Enterprise software is undergoing…", "internal_links": 7, "external_links": 12, "language": "en" }
Built on proven open-source tools and cloud infrastructure — no vendor lock-in.
Dedicated parsers for WordPress (REST API + HTML), Medium, Substack, Ghost, Blogger, and Tumblr — avoiding fragile CSS selectors where APIs exist.
Trafilatura-based content extraction strips navigation, sidebars, ads, and footer boilerplate — only article content extracted.
Locality-sensitive hashing detects near-duplicate and syndicated content across sources before delivery.
Language detection on every article, with separate pipelines for Latin-script and non-Latin languages for optimal extraction.
Publication volume tracking per topic, author, and tag over time — delivered alongside content for trend detection use cases.
Internal and external link relationships stored as a graph — enabling content topology, authority analysis, and link opportunity research.
From solo analysts to enterprise data teams — here's how organizations use this data.
The world's most valuable domain knowledge is scattered across millions of blogs, published daily by practitioners, researchers, and specialists. It appears there before it reaches reports, papers, or mainstream media. DataFlirt aggregates, cleans, and structures this content stream at any scale — giving your SEO, AI, and research teams a continuously updated dataset of the web's most authentic expert output.
Start free and scale as your data needs grow.
For small teams and projects getting started with data.
For growing teams with serious data requirements.
For large organizations with custom requirements.
Everything you need to know before getting started.
Join data teams worldwide using DataFlirt to power products, research, and operations with reliable, structured web data.
