DomCop is a domain research platform that surfaces domain authority metrics, open pagerank scores, and web asset statistics across millions of indexed domains. The stats page at domcop.com/stats aggregates this data into a structured listing format, making it a useful source for SEO analysts, domain investors, and data teams building competitive intelligence pipelines. This guide walks through extracting that data programmatically using the Minexa API, a deterministic AI web

Franchise and business opportunity data changes constantly. Listings appear, prices shift, categories expand. If your pipeline depends on that data being current and structured, manually checking Seek Business page by page is not a sustainable approach. This guide walks through how to extract franchise and business listing data from Seek Business (seekbusiness.com.au) using the Minexa API — a two-phase workflow where you train a scraper once using the Minexa Chrome extension,

Immigration research involves tracking hundreds of forum threads across country-specific portals, and doing that manually does not scale. This walkthrough shows how to extract structured data from Visa Journey (visajourney.com) using the Minexa API, covering every step from scraper creation to a production-ready Python script. Step 1: Open the target page Navigate to the Visa Journey country portal, for example the Brazil-specific thread listing at visajourney.com/portals/ind

Flight price data sitting behind a search interface is genuinely difficult to collect at scale. Kayak surfaces destination tiles with prices, stop counts, and editorial tags, but none of that is available via an official API. This walkthrough shows how to extract it using the Minexa API, a data extraction platform that combines a browser-based training step with a programmatic extraction endpoint. The workflow has two phases: train a scraper once using the Minexa Chrome exten

Financial product pages like Kotak Mahindra Bank's credit card listings are structured, publicly accessible, and updated regularly. That makes them a practical data source for fintech developers, competitive analysts, and financial researchers who need card features, eligibility criteria, and product metadata in a structured format. This guide covers how to extract that data programmatically using the Minexa API, a deterministic web extraction platform that handles JavaScript

Event data sitting behind a paginated listing page is useful only when it is structured, repeatable, and accessible without manual copying. Live Nation Asia publishes a full event directory at livenation.asia/event/allevents, and the Minexa API gives developers a direct path from that page to a clean JSON dataset they can query, store, or pipe into any downstream system. This guide walks through the complete workflow: training a scraper once using the Minexa Chrome extension,

Manually copying flight data from Cheapflights row by row is the kind of task that looks simple until you are three pages in and the prices have already changed. This guide shows how to connect the Minexa API to Cheapflights and pull structured flight data programmatically, starting from a single trained scraper. What the data looks like before and after Without automation, flight data from Cheapflights lives in a rendered page that updates dynamically. You can see the prices

If you track Indian startup funding rounds, monitor sector trends, or build datasets for VC research, Inc42 is one of the most consistently updated sources available. The challenge is that the data sits inside article cards spread across paginated listing pages, and there is no official API to pull it programmatically. This guide shows how to extract structured startup and investment data from Inc42 using the Minexa API. The workflow has two phases: train a scraper once using

Logistics data sits on public-facing pages in plain sight, but getting it into a structured format for analysis is rarely straightforward. Shiprocket, one of India's widely used shipping and logistics platforms, publishes a range of supply chain-relevant content across its site. Extracting that content consistently, at scale, and without writing custom scraper code is exactly the kind of problem the Minexa API is built to solve. This guide walks through the full workflow: tra

The OSPI Online Learning Course Catalog lists every state-approved online course available to Washington K-12 students, including provider names, grade eligibility, course levels, and direct links to provider PDFs. Pulling that data manually means clicking through paginated tables and copying rows one by one. The Minexa API removes that entirely. Watch the full extraction walkthrough before diving into the steps below. What the extracted data looks like Here is a sample of wh

Every job listing on Freshersworld contains more structured data than it appears to hold at first glance. Behind each card sits a salary range, a relative posting timestamp, a numeric job ID embedded in a CSS class, and a full list of eligible qualifications packed into a single traversable array. Getting all of that out cleanly, at scale, without writing selectors or maintaining parsing logic, is exactly what the Minexa API is built for. This guide walks through the complete

Air quality data is publicly available on AQICN, but getting it into a structured format that a pipeline can actually use is a different problem. The page renders pollutant readings dynamically, attribution strings span multiple lines, and each row carries embedded chart images encoded as Base64. None of that is accessible through a simple HTTP request. This guide walks through how to extract that data programmatically using the Minexa API, covering the full workflow from scr

Collecting property listing data from Dom.ria.com manually means opening dozens of pages, copying prices, addresses, and specs one by one, and ending up with a spreadsheet that is already outdated by the time you finish. This post shows how to replace that process with a single API call using Minexa, a web data extraction platform that turns any structured listing page into clean JSON without writing selectors or parsing HTML by hand. Before: what you are dealing with on Dom.

Clinical trials data is one of the most structurally rich and time-sensitive categories of public research information available on the web. Fred Hutch Cancer Center publishes a continuously updated directory of active trials at fredhutch.org, covering oncology, hematology, behavioral interventions, and surgical comparisons across phase I through phase III studies. Extracting that data programmatically opens up a range of research intelligence workflows that are difficult to

Queensland.com lists hundreds of tours, activities, and experiences across the state. Each listing card carries a company name, a full activity description, a cover image, booking links, and a unique product identifier. Getting all of that into a structured dataset manually is not realistic at any meaningful scale. This walkthrough shows how to extract that data using the Minexa API. You train a scraper once through the Minexa Chrome extension, then call the API programmatica

Metacritic's game browse page is one of the most complete public sources of critic-scored game data on the web. Every listing carries a Metascore, an ESRB rating, a release date, a full description, and a direct link to the game's detail page. If you are building a game analytics pipeline, a content recommendation engine, or a media intelligence feed, this is a dataset worth having in structured form. This guide walks through how to extract that data at scale using the Minexa

Kavak is one of Latin America's largest used car marketplaces, and its Brazilian listings page at kavak.com/br/seminovos contains hundreds of vehicle cards updated regularly with price, mileage, model year, location, and direct links to individual detail pages. Extracting that data at scale without writing custom scraper code is exactly what the Minexa API is built for. This walkthrough covers the full workflow: training a scraper once using the Minexa Chrome extension, then

Alternative.to lists software alternatives organized by category, platform, and language. Every listing card contains a product name, description, external website link, feature count, social profiles, and platform metadata. Pulling that data manually across dozens of pages is slow. The Minexa API makes it programmable. The workflow has two phases: train a scraper once using the Minexa Chrome extension, then call the API to extract data at scale from any number of Alternative

GitHub Explore surfaces what the developer community is actually building right now. Trending repositories, active topics, star counts, programming languages, and full card-level metadata are all sitting on a single public page. The challenge is getting that data into a structured format you can query, filter, and feed into a pipeline. This guide walks through how to extract that data programmatically using the Minexa API. The workflow has two phases: train a scraper once usi

The IMO's GISIS portal is one of the most comprehensive public sources of maritime regulatory data on the internet. Ship particulars, maritime security records, casualty reports, treaty statuses, port reception facilities, ballast water management data, and more than twenty other module categories are all publicly accessible from a single index page. The challenge is not finding the data. It is getting it out in a form you can actually use programmatically. This guide covers