INDUSTRY 05

Retail & Consumer Goods.

In retail, the difference between a good quarter and a bad one is a few percentage points of sell-through. Data is what tells you which percentage points to chase.

Sub-sectors
Warehouse management · Demand forecasting · Pricing analytics · E-commerce integration
Engagements
2+
Specializations
DACH
Status
Actively serving
— Common challenges

What retail leaders bring to us.

Recurring patterns across engagements. Each is solvable. None is solved by a slide deck alone.

— Case studies

Selected work in Retail & Consumer Goods.

Engagement details below. Specific clients, financials and architecture diagrams shared under NDA.

Consumer Goods · 2023–2024

Marketing analytics and pricing intelligence

Power BI · Python · Pandas · Azure SQL · MS Fabric

Developed marketing analytics reports for campaigns. Defined campaign KPIs and analyzed performance. Built pricing dashboards using data from price comparison websites. Conducted web scraping for campaign data from Amazon, MediaMarkt and Otto. Integrated third-party pricing data using Python.

Pricing decisions moved from reactive to data-led. Campaign attribution closed.
Retail · 2021–2022

BI integration for DACH sales

Python · Power BI · Qlik Sense · MS SQL Server

Integrated customer data inputs into the existing BI system. Built and automated custom data integration pipelines. Developed data marts for the DACH Sales Department. Migrated legacy reports.

DACH sales analytics centralized. Legacy reporting decommissioned.
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