Geox is one of the best-known Italian brands internationally in the fashion landscape.
Innovation and technology have always been hallmarks of the brand, revolutionizing the footwear world with its patented breathable technology.
Present in more than 100 countries, this multinational company—combining retail, digital, and B2B distribution—sees data as a strategic asset for managing lifestyle and urban comfort.
In an increasingly dynamic retail context, Geox identified two priorities to strengthen its competitive intelligence:
The e-commerce and wholesale team needed to monitor on a daily basis how 3P platforms (such as Amazon and Zalando) and B2B partners were presenting Geox products in terms of pricing, discounting, and assortment.
A critical activity to ensure consistency and defend brand perception, but made complex by the sheer volume of data to manage: hundreds of thousands of references spread across dozens of markets and digital channels.
Teams needed reliable and up-to-date strategic insights to answer key questions:
What products do competitors offer? At what price points? When are new collections coming in?
But the traditional method – based on manual research – was time-consuming, poorly scalable, and often flawed.
In the world of footwear and fashion, the importance of data lies in the ability to continuously improve our collections and offer products tailored to consumer tastes and customs across the countries we operate in.
Geox adopted an advanced price & market intelligence platform, specialized in the fashion and retail sector, building a scalable, intuitive, and personalized infrastructure.
The activated functionalities included:
- Brand Plan
Daily monitoring of price trends and seller presence on marketplaces and retail platforms, with automated alerts on violations of brand policies. - Benchmark Plan
Daily analysis of competitors’ assortment strategies and pricing in major markets: new arrivals, seasonality, discounts, and best sellers by product category. - Intelligent Product Matching
Matching of catalog items through shared data networks, thanks to deep learning algorithms via semantic analysis. - Advanced KPIs
Such as the Global Price Index (GPI) to analyze price trends across countries and segments, and track pricing deviations from expected ranges. - Dashboards and Dynamic Reports
Views and insights tailored to each team, updated on a daily basis. - Ad-hoc Customizations for Geox
From automatic classification of products to the detection of specific attributes in line with the internal taxonomy.
The Results
Automated and scalable control of pricing across international channels
Improved partner management and protection of brand perception
Significantly reduced time and analytical effort for Marketing and Style
Faster and better-informed decisions for evolving collections
