About

Steven will present how a major UK last-mile logistics company leveraged identity resolution technology to create a unified single customer view from 150 million fragmented records with real-time performance and a 99.5% accuracy rate.

The case study demonstrates how an enterprise-grade identity resolution solution can handle real-world data challenges including inconsistent data formats, complex addresses, masked emails, and external marketplace integrations from the likes of Amazon and eBay. The resulting 38.1 million golden customer profiles enable critical last mile improvements: enhanced delivery accuracy, reduced failed deliveries, household-level preference identification, and automated fraud detection.

This data infrastructure investment also lays down the foundationals for AI-driven applications.

The presentation will show how modern identity resolution transforms fragmented customer data from an operational liability into a strategic asset, enabling logistics companies to deliver superior customer experiences while reducing operational costs and unlocking new revenue opportunities through data-driven personalisation and analytics.

Takeaways

• Enterprise-scale identity resolution can be deployed rapidly on big data without sacrificing accuracy
• Single customer view enables household-level insights and personalized delivery preferences
• Advanced matching handles messy real-world data including eCommerce marketplace integrations and incomplete records
• Unified customer profiles reduce failed deliveries while creating foundation for AI-driven analytics and fraud detection