A popular Mexican credit card comparison portal needed a price comparison data feed pulling offers directly from bank websites, refreshed weekly and ready to use without any technical work on its own side.
Client Overview
A popular credit card comparison portal in Mexico needed a reliable price comparison data feed pulling credit card offers and promotional details directly from bank websites, the raw material its entire comparison engine depended on. Without that feed staying current, the portal would be showing customers offers that banks had already changed or withdrawn.
The portal had no in-house technical capability to build this itself, and the target bank sites were built with dynamic, complex coding that was never going to yield to a simple script. Getting a price comparison data feed this specific meant the portal needed a fully managed partner willing to take end-to-end ownership of the extraction, not just a tool it would have to operate itself.
Client Requirements
The portal’s brief to PromptCloud was clear about ownership and cadence:
- Credit card offers and promotional details extracted from bank websites
- A fully managed service, since the portal had no in-house technical capability
- Weekly extraction frequency to keep the comparison engine current
- Delivery in a clean, ready-to-use format requiring no further processing
- JSON format, delivered directly to the portal’s Dropbox account
Challenges
Bank websites are not built for easy scraping. Dynamic, complex coding elements meant a crawler had to handle pages that behaved more like applications than static content, and doing that reliably across multiple bank sites at once demanded real infrastructure rather than a handful of scripts.
The portal’s lack of in-house technical capability raised the stakes further. Since the portal could not maintain or troubleshoot a crawling setup itself, PromptCloud needed to own not just the initial build but the ongoing reliability of the whole pipeline, catching site changes before they turned into missing or outdated offers on the comparison engine itself, a bigger risk for a comparison business than for almost any other kind of data user.
Solutions
PromptCloud treated this as a site specific crawl, taking full ownership of the extraction, monitoring, and delivery so the portal never had to touch the technical side directly.
Crawlers Built for Dynamic Bank Sites
Handling bank websites with complex, dynamic coding meant building crawlers capable of interpreting pages the way a browser would rather than relying on simple static extraction. This is the kind of infrastructure difference worth weighing when comparing PromptCloud’s approach to other web scraping platforms, since a data feed built on unreliable extraction logic will eventually show customers offers that no longer exist.
Weekly Delivery, Ready to Use Immediately
Data moved on a weekly cycle, delivered in JSON format straight to the portal’s Dropbox account in a clean, ready-to-use state. That meant the comparison engine could pull new credit card offers directly into its own systems without an extra processing step standing between delivery and actually showing updated offers to the portal’s own customers.
Monitoring on Two Layers, Not Just One
PromptCloud set up both automated and manual layers of monitoring on the target bank sites, catching structural changes that could otherwise break a crawler silently. Running both layers together meant a change was far less likely to slip through unnoticed, which matters more for a comparison portal than most other use cases, since a missed change means showing a customer an offer that is no longer real.
Live in Three Days
The crawler setup for the target bank sites was completed in just three days, and the first crawl alone delivered about 10,000 records to the portal. That speed meant the portal could start powering its comparison engine with real data almost immediately, rather than waiting weeks for a custom scraping project to reach production.
Credit Card Comparison Data Feed, Before and After PromptCloud
| Area | Before | After |
| Technical ownership | No in-house capability to build or run this | Fully managed, end-to-end ownership by PromptCloud |
| Site monitoring | None in place | Automated and manual layers, both active |
| Data readiness | Would need further processing before use | Clean, ready-to-use JSON delivered to Dropbox |
| Time to value | No existing pipeline | Live in 3 days, 10,000 records on the first crawl |
Benefits to the Client
The portal got a comparison engine running on real bank offer data within three days of starting the project, with about 10,000 records landing in the very first crawl. None of the technical complexity, from handling dynamic bank site coding to monitoring for changes, ever touched the portal’s own team.
Weekly delivery kept offers current enough for a comparison business to trust, and clean, ready-to-use JSON data meant the portal could load new offers straight into its engine without extra processing. On cost, the source material cites two different figures for savings against an in-house crawling team, 60 percent in one place and 78 percent in another, so that number needs verification before it goes on the page rather than being stated as fact here.
A Price Comparison Data Feed That Banks Cannot Quietly Break
A comparison portal is only as trustworthy as the offers it shows, and a price comparison data feed pulling from bank websites has to catch every change those banks make, not just the ones that happen to be obvious.
That is what two layers of monitoring, weekly delivery, and full managed ownership actually solve, a feed that keeps showing real offers even as the banks behind them keep changing their own sites. That is what turned a portal with no technical team of its own into one running on data it never had to touch directly.
