Federal job listings contain more structured data than most people realize. USAJobs surfaces job titles, hiring organizations, salary ranges, employment types, application deadlines, and eligibility paths all on a single search results page. The challenge is getting that data out in a usable format without copying rows manually. This guide walks through how to extract that data using the Minexa.ai Chrome extension, a no-code tool that turns any structured web page into a down

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dozens of pages, copying prices, addresses, and specs one by one, and ending up with a spreadsheet that is already outdated by the time you finish.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

Ryanair publishes a public flight listing page that shows available routes, departure dates, origin and destination cities, IATA airport codes, one-way fares, and direct booking links. All of it is visible in the browser. None of it is easy to collect at scale without a tool built for the job. This guide covers how to extract that data using Minexa.ai, a Chrome extension that detects page structure automatically and exports results to Excel, Google Sheets, or JSON without any

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

Here is what the data looks like before you read a single instruction. [ { "course_title": "Level 2 Certificate in Awareness of Mental Health Problems", "provider_name": "Learning Curve Group", "enquiry_count": "8,704 enquiries", "course_description": "Complete online for FREE when it suits you, with study materials and tutor support.", "course_features": "Tutor support", "list_item_description": "Regulated qualification", "link_href": "/courses/level-2-certificate-in-awarene

Built In is a tech-focused jobs and company directory that covers a wide range of industries, including agriculture and food production. Its company listings page at builtin.com/companies/type/agriculture-companies surfaces company names, employee counts, office locations, benefits counts, industry tags, and hiring status all in one place. That makes it a useful starting point for agri-food market research, competitive benchmarking, or building a targeted outreach list. The c

The T-Bank invest portal lists dozens of ETFs and investment funds on a single paginated page. Each card carries a fund name, a logo, a performance chart rendered in SVG, and a link to the fund detail page. Visually, it reads cleanly. Programmatically, it is a different story: the chart data is embedded in SVG polyline attributes, gradient identifiers are scattered across path elements, and performance direction is encoded in CSS variable names rather than plain text values.

Michael Page publishes hundreds of active job listings across London every day. If you want that data in a spreadsheet, structured and ready to analyse, the Minexa.ai Chrome extension gets you there without writing a single line of code. This walkthrough covers the full extraction process from the michaelpage.co.uk/jobs/london page, showing exactly what you see at each step and what to do. Watch the full tutorial first The video below covers the complete workflow from install

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

Government procurement portals publish some of the most consistently structured public data available online. OregonBuys, Oregon's centralized public purchasing system at oregonbuys.gov, lists open bids from state agencies, counties, school districts, tribal organizations, and public utilities all in one place. The data is public, updated regularly, and genuinely useful for vendors tracking opportunities, researchers monitoring public spending, and analysts building procureme

Fleet procurement teams and logistics analysts working in Brazil regularly need structured vehicle specification data to compare configurations, validate supplier quotes, and build internal reference datasets. Mercado Livre publishes detailed catalogue pages for commercial vehicles, including full technical comparison tables per trim, but that data sits inside a web page rather than a spreadsheet. Getting it out manually, row by row, is slow and error-prone at any meaningful

Most people who need web data for a work project assume the task is either trivially easy or completely out of reach. Neither assumption tends to be accurate, and both lead to the same outcome: hours spent doing manually what a tool could handle in minutes. Here are ten things that commonly trip people up before they even get started. 1. Multi-level navigation means the site cannot be scraped Some sites require you to click through several layers before reaching the actual da

Website traffic data is one of the most useful signals for competitive research, SEO benchmarking, and market sizing. SE Ranking publishes traffic estimates for domains directly on its website traffic checker page, and with the Minexa.ai Chrome extension, you can pull that data into a structured spreadsheet without writing a single line of code. This walkthrough shows you exactly how to do it, step by step, with screenshots at each stage so you know what to expect. Watch the

Credit card benefit data buried inside accordion-based FAQ pages is some of the hardest structured content to extract reliably. Capital One's rental car insurance help page is a good example: each question expands into a body containing card eligibility lists, benefit administrator contacts, and coverage exclusions, all encoded inside Angular components with dynamic display states. This guide shows how to pull that content into a clean, repeatable data pipeline using the Mine

Indonetwork is one of Indonesia's largest B2B directories, listing thousands of verified companies across industries including cargo, freight forwarding, customs brokerage, and domestic logistics. The cargo and logistics section alone contains hundreds of active company profiles, each with addresses, service descriptions, contact data, and membership tier information. If you are building a supplier database, researching logistics partners across Indonesian cities, or monitori

FRED publishes hundreds of commodity price series, all publicly accessible, all updated regularly. The problem is that the data sits inside a category listing page that was built for browsing, not for export. Getting it into a spreadsheet means either copying rows one by one or building something custom. Neither option scales. This guide shows how to extract structured commodity price data from fred.stlouisfed.org using the Minexa.ai Chrome extension, no code required. Watch

A Greenhouse job board page looks clean in a browser. Open the raw source and it is a different story: nested divs, dynamic class names, carousel wrappers, and image paths buried inside attributes. Getting that into a spreadsheet manually takes far longer than it should. This guide shows how to go from that raw page to a structured, exportable dataset using Minexa.ai, a Chrome extension that detects and extracts data from any web page without requiring any code. What the page

SEC filings are public, structured, and updated regularly. But pulling them into a usable dataset from Eli Lilly's investor portal manually is slow work. This walkthrough shows how to build a repeatable extraction pipeline using the Minexa API. The scenario: monitoring Eli Lilly SEC filings at scale Imagine you need to track every new filing that appears on the Eli Lilly SEC filings page and feed that data into a downstream system automatically. You need filing types, dates,

Kleinanzeigen is Germany's largest classifieds platform, and its land and garden listings category contains thousands of active property ads updated daily. Getting that data into a structured format manually is not practical at any meaningful scale. This guide shows how to do it programmatically using the Minexa API. The workflow has two tracks. You run track one once in the browser to train the scraper. You run track two as many times as you need via the API. Once track one