Projects / Case studies

What we actually build for clients

Examples based on real implementations (some anonymised). Each follows: problem → solution → tools → result.

Featured case study

Price & margin monitoring dashboard

Problem: Purchase and sales prices were scattered across files and systems. Margins were calculated manually, late and with errors.
Solution: I built a VPS-based system that periodically pulls data from CSV files and APIs, processes it in Python (pandas) and shows margins on a live Streamlit dashboard.
Result: A live view of margins in one place, instead of occasional manual spreadsheets.

Python pandas Streamlit VPS API

Problem: Product data had to be manually copied between Allegro and internal systems.
Solution: Allegro API integration to automatically retrieve and sync listing data.
Result: Less manual work and consistent data across channels.

Allegro API Python n8n

Problem: Supplier data in inconsistent formats: mismatched categories, brands, missing EANs.
Solution: Scripts that clean and map data into a single, consistent, sale-ready format.
Result: Faster product onboarding and fewer offer errors.

Python CSV/XML EAN

Problem: Tracking was in place, but the data did not match actual sales.
Solution: Audit and re-implementation of GA4, GTM, pixels and Consent Mode v2 with a CMP.
Result: Reliable data for marketing decisions and GDPR compliance.

GA4 GTM Consent Mode v2 CMP

Problem: Sales and marketing reports prepared manually every week.
Solution: An automated process that collects data and generates the report on schedule.
Result: Hours saved weekly and reports always on time.

n8n Python API

Problem: The marketplace required different product data than the store and supplier.
Solution: Transforming and enriching data into feeds compliant with each channel's requirements.
Result: Smooth listing in new sales channels.

CSV/XML Feeds Baselinker

Tell me what you are trying to solve. I will review the case and suggest a practical solution.