In luxury retail, customer expectations evolve rapidly and brands must continuously adapt their strategies to remain competitive. For Piquadro Group, managing customer, commerce, and marketing data across multiple brands created an opportunity to rethink how information could support growth and decision making.

Working with BIP xTech, the Group designed a centralized data ecosystem powered by Azure Databricks that connects behavioral, transactional and CRM data into a single intelligence layer. The result is a scalable platform that enables advanced customer analytics, audience discovery, marketing activation and real-time business intelligence across Piquadro, The Bridge and Lancel.

CHALLENGE

Turning Data Complexity into Business Opportunity

As the Group expanded its digital footprint, data was being generated across multiple touchpoints:

• e-commerce platforms
• web analytics
• physical stores
• email marketing tools

While each source contained valuable information, the absence of a shared analytical foundation limited the ability to obtain a complete view of customer behaviour and market performance.

The business needed a solution capable of connecting anonymous browsing activity, customer profiles, purchase history and marketing engagement into a single ecosystem. The objective was not only to improve reporting but also to generate actionable insights that could support commercial, marketing and strategic decisions at a global scale.

OUR SOLUTION

Building a Retail Data Core with Azure Databricks

To address these challenges, BIP xTech designed and implemented a centralized Data Core architecture powered by Azure Databricks.

The platform integrates information from:

• Google Analytics 4 (GA4)
• Shopify
• Dynamics 365 CRM
• Dynamics 365 Customer Insights

Using Azure Databricks as the processing and orchestration layer, data from multiple channels is consolidated into a unified environment where customer interactions can be analysed consistently across brands and geographies. Secure identity resolution mechanisms enable the connection between behavioural signals and known customer profiles, creating a trusted foundation for customer intelligence and analytics.

The architecture supports both business intelligence and customer activation use cases, allowing teams to move seamlessly from insight generation to campaign execution.

RESULTS

From Data Collection to Customer Intelligence

One of the most valuable outcomes of the initiative was the creation of a unified customer intelligence framework.

The platform combines transactional, behavioural and engagement signals to provide a richer understanding of customer interests, preferences and purchase intent.

Through advanced segmentation capabilities, the Group can identify and monitor audiences based on specific behavioural patterns and business objectives based on Web navigation data of Unknow user. Examples include:

• high-value prospects
• non-converting visitors with strong engagement
• product-category enthusiasts
• high-margin customer segments
• dormant audiences requiring reactivation

This approach enables marketing teams to develop more relevant customer journeys in Customer Insights, while giving business stakeholders greater visibility into emerging opportunities and changing consumer behaviours.

Enabling Data-Driven Decisions Across the Business 

Beyond customer segmentation, the initiative introduced a comprehensive performance measurement framework.

A proprietary Engagement Score combines multiple dimensions of customer interaction, including:

• navigation depth
• purchase intent
• conversion activity
• marketing engagement

The scoring model can be configured directly by business users, allowing teams to adapt measurements according to evolving business priorities and strategic objectives.

To support decision makers, BIP xTech developed advanced Power BI dashboards that provide a consolidated view of:

• customer behavior
• product market analysis
• online opportunities
• campaign effectiveness
• audience insights

This empowers leadership teams to identify trends faster, prioritize investments more effectively and make decisions based on evidence rather than assumptions.

Conclusion

The transformation carried out by Piquadro Group demonstrates how luxury retailers can move beyond fragmented data management toward a unified intelligence model that supports both operational excellence and strategic growth.

By combining the consulting and data expertise of BIP xTech with the scalability of Azure Databricks, the Group established a modern data foundation that connects insights, customers and business decisions across its entire portfolio of brands.

As customer expectations continue to evolve, this data-driven approach positions the organization to respond faster, personalize more effectively and unlock new opportunities for sustainable growth.