With the acquisition of large volumes of data from online sources and in-store visits, our client wanted to build a data management platform to track user behavior of their customers and use the insights to personalize their offerings.
The client was processing terabytes of data with multiple siloed data stores which led to a broken reporting with no coordinated master data management approach. There was a clear lack of an agile mechanism to deliver the on-demand analytics using modern tools and emerging technologies.
We started with modernizing their current data warehouse by incorporating a modern data lake with emerging technologies and real-time capabilities to deliver insights. In the re-engineered data lake, we merged over 300 data sources into a single data lake to deliver the actionable insights by analyzing over 50 million transactions across multiple customer channels.
In addition, we implement the following capabilities for real-time analytics:
- Eye Tracking using sensors to capture attention and measure customer interest
- Radio-Frequency Identification Implants
- Loyalty Programs based on analytics
- Customer Heat Maps analysis to improve store merchandising
Traditional data warehouses have served well (and still do), but most of them lack the scalability, agility and cost profile of a data lake. Data lake is a powerful architectural approach to finding insights from untapped data which our client delivers it to their customer. We delivered many business benefits including:
- Streamlined data acquisition process to address data gaps and monitor customer behavior data for transactional insights
- Machine Learning techniques to predict the outage and customer buying patterns on the data lake
- Customer loyalty program campaigns tailored for each customer
- Algorithms based tracking for attributes like people counts, location and stay time in the store
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