Most data collection slowdowns have nothing to do with the website. They come from the collection process itself. When pages are processed one at a time, every request waits for the previous one to finish before starting. On a fast connection, that might feel fine for ten pages. At a few hundred pages, the wait becomes noticeable. At several thousand, it becomes the bottleneck that defines your entire workflow. The fix is not complicated in concept: process multiple pages at

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dozens of pages, copying prices, addresses, and specs one by one, and ending up with a spreadsheet that is already outdated by the time you finish.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

Travel Wisconsin's food and drink directory lists hundreds of restaurants, bars, breweries, cafes, and distilleries across the state. If you want that data in a spreadsheet rather than clicking through pages one by one, the Minexa.ai Chrome extension handles the full extraction without any code. Here is the complete walkthrough, step by step. Watch the full tutorial first The video below covers the entire workflow from installing the extension to downloading your export. Watc

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

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

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

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

Supply chain data is everywhere on the web, but getting it into a spreadsheet without copying it line by line is a different story. This walkthrough shows how to pull structured article data from SupplyChainBrain, one of the most referenced logistics and supply chain publications, using the Minexa.ai Chrome extension. The starting URL for this tutorial is the logistics service providers directory: https://www.supplychainbrain.com/directories/98-supplier-directory/topic/1254-l

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

Grant funding databases are only useful when you can actually work with the data inside them. The HRSA Find Funding page lists open federal health grant opportunities from bureaus including the Bureau of Health Workforce and the Federal Office of Rural Health Policy, but the data sits inside a paginated web listing with no export button. This guide walks through every step needed to extract that data using the Minexa.ai Chrome extension, no code required. Watch the full tutor

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

MUBI's all-films catalogue is one of the most consistently structured film listing pages on the web, which makes it a reliable source for building media datasets covering curated cinema from dozens of countries and decades. This guide walks through how to extract structured film data from mubi.com/en/films?all_films=true using the Minexa.ai Chrome extension, with no code required. Watch the tutorial first The video below covers the full extraction from start to export. Step 1

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

The data below was extracted from the Visit Fort Wayne restaurant directory in a single API call. Before explaining how the pipeline works, here is what the output looks like. What the extracted data looks like Each row in the response corresponds to one restaurant listing on the Visit Fort Wayne page. Here are three labelled records from the extraction: [ { "restaurant_name": "Wagyu Burger Shack", "listing_url": "/listing/wagyu-burger-shack/55389/", "external_link":...