Case study

Automated daily revenue reporting for Calzedonia and Intimissimi stores

Impact

Even without a direct API integration, automation is possible. We built a solution that parses daily text files, eliminates approximately 730 manual entries per year, and automates monthly closures.

Background & Challenge

It is standard practice for shopping mall tenants to report their daily revenue and receipt count to the mall management. Typically, a modern direct connection (API) is expected for this, but for international retail chains, this isn't always feasible.

Sales data for Sunshine Group's two stores is managed centrally at the group's headquarters in Italy. There was no ready-made API connection for a single specific market, and the only available data stream consisted of unstructured text files (TXT/CSV) generated daily by their retail system. Because a standard integration was missing, local employees entered the required numbers manually every single day.

Solution

This project proved that a complex or legacy data format is no barrier, and a functional integration can be built with any system, regardless of whether a modern API exists or not.

We developed a custom integration for the client that reads and interprets text files directly every morning, extracts the sales figures for the two stores, and forwards gross revenue, net revenue, and transaction counts directly to the shopping mall's system.

Accuracy was paramount, as these numbers form the basis for various financial settlements. Since we were dealing with raw data in text files, strict validation mechanisms were built into the integration: before transmission, the data is checked against independent checksums contained within the files. The figures must match down to the cent, or nothing is sent and the team is immediately alerted.

Once the month comes to an end, the integration automatically submits the confirmation to the shopping mall.

Impact

Store staff no longer enter revenue figures manually, eliminating roughly 730 manual data entries per year. The shopping mall receives verified, accurate figures every day, and monthly closures happen automatically.

This solution clearly demonstrates that you don't need to wait for a "perfect API" to automate. With smart architecture, even seemingly inconvenient text files can be transformed into a completely reliable, automated data pipeline.