Introduction:

In the fast-paced digital commerce industry, having real-time visibility into customer journeys is essential for boosting conversions and making informed business decisions. To meet this need, an OBT (One Big Table) Data Warehouse platform was developed for a client. This solution consolidated data from various sources into a unified view, leveraging the AWS tech stack. The platform enabled near-real-time analytics, improved underwriting processes, and provided data-driven insights, enhancing customer engagement, mitigating risks, and improving operational efficiency.

Business Challenge:

The client, operating in digital commerce, faced difficulties in tracking customer journeys from lead generation to conversion in near real-time. They required a comprehensive view of customer interactions across multiple platforms to improve segmentation, underwriting, and risk management. However, their existing data processes were not agile enough to consolidate information quickly, causing delays in identifying sales bottlenecks, missed personalized marketing opportunities, and slower decision-making. These issues negatively impacted conversion rates, operational efficiency, and customer satisfaction.

Solution:

The OBT Data Warehouse was implemented to consolidate data from multiple sources—including web traffic, CRM systems, underwriting platforms, payment gateways, and customer interaction tools—into one holistic table. The platform was built using the AWS tech stack, which enabled real-time data integration, processing, and analysis.

The key AWS components used were:

• Amazon S3 for scalable storage of raw and processed data.
• AWS Glue for data cataloguing and ETL processes.
• Amazon Redshift as the data warehouse, optimized for large-scale queries.
• Amazon Kinesis Data Streams for real-time streaming data handling.
• Amazon QuickSight for data visualization and business intelligence dashboards.
• AWS Lambda for event-driven data processing and automation.

These services allowed seamless data integration from multiple sources, improving the client’s ability to act on real-time insights.

Impact:

The OBT Data Warehouse had a substantial positive impact across the organization, particularly in tracking digital platform performance and customer behaviour. By creating a real-time, mirror view of customer buying behaviour, teams were able to monitor fluctuations in lead volume and funnel performance, enabling timely interventions by various departments, including sales, underwriting, analytics, and tech.

Key Outcomes:

• Lead to Customer Conversion: A 15% increase in conversion rates was achieved by identifying bottlenecks in the sales funnel and optimizing customer engagement strategies.
• Underwriting Efficiency: Approval times were reduced by 20% due to real-time access to enriched customer data.
• Risk Mitigation: A 10% reduction in high-risk loans was realized by using historical data to identify potential credit defaults.
• Sales and Marketing Insights: A 12% increase in repeat customers was achieved through personalized marketing strategies.
• Operational Efficiency: Time spent on manual data handling and query optimization was reduced by 25% thanks to the consolidated data structure.

This implementation of the OBT Data Warehouse not only streamlined data management but also empowered departments to make smarter, faster decisions, driving overall business performance and reducing risks.