What Minexa actually detects when you open a page (and why that matters for your data)

Most people assume that to extract data from a website, you need to tell the tool exactly what to look for. Point at a price, click a title, highlight a date. Minexa.ai works differently, and understanding how changes what you can do with it.

Detection comes first, selection comes second

When you open a page with Minexa active, it does not wait for you to click anything. It scans the page structure and identifies repeating patterns automatically. From those patterns, it builds a picture of every data point present in each result on the page: names, prices, dates, ratings, image links, and attributes that sit inside the page code but are not directly visible to someone reading the page normally.

This matters because data hidden in HTML attributes is often the most useful kind. Image source URLs, product identifiers, category tags, and structured metadata are all things a human would miss when copying data manually. Minexa surfaces them as part of its standard detection pass.

You do not need to know what fields exist

One of the less obvious features is automatic field discovery. If you are not sure what data is available on a page, you do not have to guess or explore manually. Minexa detects all relevant data points it finds and ranks them by relevance. You can let it show you what is there before deciding what to keep.

This is useful when you are working with an unfamiliar site or when you want to see the full picture before narrowing your output. It removes the need to inspect page source or run test extractions to find out what fields are available.

List pages and detail pages are both covered

A standard search results page gives you a summary of each result: a title, a price, maybe a location. The full information lives one click deeper, on each individual result's page. Minexa handles both layers in a single run.

After confirming what it found on the list page, you have the option to instruct Minexa to follow each result's link and extract the detail data from each individual page as well. A list of 400 property listings becomes a dataset that includes the full description, floor plan details, agent contact, and listed date from every one of those pages, without any manual clicking involved.

The detection logic applies to detail pages the same way it applies to list pages. Minexa reads the structure, identifies the data points, and extracts them consistently across every page in the run.

Install the Minexa extension and run your first extraction today.

The structure is remembered after the first run

Detection takes a few seconds to a few minutes the first time, depending on the complexity of the page. Once complete, that structure is saved as a scraper. Every subsequent run on a page with the same structure skips the detection phase entirely and goes straight to extraction. This means the setup cost is a one-time investment, not a recurring one.

Ten rows or ten thousand rows from the same page type take the same amount of setup time. The extraction itself runs in milliseconds per page once the structure has been learned.

Pagination is handled without any configuration

Minexa detects the pagination method used by the site during its initial scan. Whether the site uses a next page button, infinite scroll, or a load more button, Minexa identifies it and follows it automatically across however many pages the site has. There is no setting to configure and no pagination type to select from a menu.

What happens when a site changes its layout

If a website significantly redesigns its structure, the saved scraper will no longer match the page. When this happens, Minexa returns an empty result rather than extracting incorrect data from the wrong sections of the page. The scraper can be retrained using the same process as the initial setup, which typically takes a few minutes.

One practical detail worth knowing: after retraining, column names may differ slightly from the original. A field previously labelled 'price_total' might come out as 'price_full' after retraining. If you have any downstream process that references specific column names, it is worth reviewing those after a retrain to make sure nothing breaks silently.

Scheduling keeps your data current without manual effort

Once a scraping job is configured, you can schedule it to run automatically on a recurring basis. Daily, weekly, or at whatever interval fits your use case. Each run captures the current state of the page at that moment, which means you can build a historical record of how prices, listings, or rankings change over time without triggering anything manually after the initial setup.

This is particularly relevant for use cases like price monitoring, job market tracking, or competitor research, where the value of the data comes from watching it change rather than capturing it once.

JavaScript and geo-targeted pages are handled automatically

Some pages only display their content after JavaScript has run. Others show different results depending on where the request appears to come from. Minexa manages both of these behind the scenes without requiring any configuration from the user. You do not need to select a rendering mode or set up proxy routing. It is part of how Minexa processes pages by default.

The output reflects exactly what is on the page

Minexa does not interpret or reformat the data it finds. Each extracted value comes directly from the position in the page structure it was trained on. If a field is not present on a given page, the output for that field is empty. Nothing is invented, inferred, or substituted. The result is a dataset where every value can be traced back to a specific location on the source page.

For anyone who has dealt with inconsistent output from interpretation-based tools, this is a meaningful difference. The data you get is the data that was on the page, structured and ready to use.

Learn more about how Minexa works at minexa.ai.