Data-Driven Omnichannel Customer Centricity
In the luxury sector, delivering a coherent and personalized experience across all touchpoints is critical. This project was designed to create a single, reliable customer view capable of connecting digital and physical channels and supporting data-driven engagement strategies.
The Client
A leading Italian luxury fashion brand with a strong omnichannel presence and the need to orchestrate consistent customer experiences throughout the entire journey.
The Challenge
The client faced several challenges related to data fragmentation and system complexity:
- Building a 360° customer view by unifying data from multiple sources
- Implementing first party identity resolution
- Ensuring data governance, retention, and integration with legacy BI systems
- Enriching online interactions and coherently linking them to customer identity
The Solution
BitBang designed an ML powered omnichannel customer centricity solution built on a Customer Data Lake.
The solution includes:
- Customer data lake setup and data ingestion pipelines
- Mapping and analysis of key omnichannel customer journeys
- Customer based ecommerce recommendation engine powered by predictive models and machine learning
- Custom reporting and KPI calculation on modern BI platforms
- An architecture ready to support future advanced use cases
The Results
- Consistent, non-duplicated communication across all channels
- Activation of new marketing journeys (re-engagement, upselling, cart abandonment)
- Personalized transactional emails
- More relevant, data-driven in store customer experiences
- Highly personalized ecommerce recommendation carousels
- Increased customer engagement and loyalty
- Improved predictability of business outcomes
- Better performance across key KPIs such as ROAS, NSAT, and repeat orders
“Unifying customer data allowed us to move from fragmented communications to a truly omnichannel experience, fully aligned with our brand positioning.”





















































































