Tracking every press release, product announcement, and leadership update from a fast-moving digital bank like Starling Bank by hand is the kind of task that sounds manageable until you actually try it at scale. Starling Bank's news page at starlingbank.com/news/ publishes a steady stream of articles covering everything from AI feature launches and bond issuances to SME research and leadership appointments. If you need that data in a structured format for competitive monitori

Zerodha publishes sector-level stock listings that are genuinely useful for anyone tracking Indian equity markets by industry. The agriculture sector page, for example, lists every company in that category with its market capitalization and current trading price. The data is public, it updates regularly, and it covers dozens of companies per sector. The challenge is that it sits inside a web page with no export button and no API. Getting it into a spreadsheet the manual way m

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,

Collecting bike specification and pricing data from BikeDekho manually means opening dozens of pages, copying values one by one, and still ending up with a spreadsheet that goes stale the moment prices update. This walkthrough shows how to extract that data automatically using the Minexa.ai Chrome extension, no code required. Watch the full video tutorial first, then follow the steps below. Step 1: Open Minexa.ai and navigate to BikeDekho Install the Minexa.ai Chrome extensio

Trading Economics publishes a live stream of commodity prices, currency rates, and market indicators across hundreds of instruments. The data is public, structured, and updates continuously. Getting it into a pipeline programmatically is a different story. This guide walks through how to extract structured alternative data from tradingeconomics.com/stream using the Minexa API. The workflow has two phases: train a scraper once using the Minexa Chrome extension, then call the A

Legal and compliance data scattered across dozens of pages is genuinely difficult to work with. LegalDesk publishes a wide catalogue of contract templates, agreement guides, and compliance documents, and getting that content into a structured format manually takes far longer than it should. This walkthrough shows how to extract that data using the Minexa.ai Chrome extension in a few minutes, no code required. Watch the full tutorial first Outcome: a confirmed starting point o

Commercial property data sitting inside a browser tab is not useful to a pipeline. Structured rows in a dataset are. This guide shows how to extract commercial real estate listings from OnTheMarket using the Minexa API, covering every step from scraper training to a working Python request. Watch the full walkthrough first The video below covers the complete extraction workflow on OnTheMarket's commercial listings page for Kent. Watch it before going through the screenshots so

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

The London Metal Exchange publishes a steady stream of market reports, press releases, member notices, and metal price pages. If you are tracking copper warrant stocks, monitoring off-warrant reporting changes, or building a dataset of LME announcements over time, the search interface at lme.com/search?searchTerm=stocks surfaces exactly the kind of structured content you need. The problem is that it is all locked inside a web page, not a spreadsheet. This guide walks through

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,

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

You want to collect job listings. You open a job platform, see hundreds of relevant postings, and immediately hit a wall the moment you try to pull that data into a spreadsheet. This is one of the most common starting points for anyone learning data collection. And it tends to go wrong in the same predictable ways. The platform problem is not what most people think The instinct is to treat all job data as equally accessible. It is not. There is a meaningful difference between

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

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