Case Study

Retail and CPG

Retail Chain Unlocks Insights by Analyzing Billions of Transactions on Azure

The grocery chain wanted to align its merchandise mix and store inventory to match its customer’s specific needs and offer a unique shopping experience. With a massive network of stores and daily visitors, they were tracking every purchase and logging almost 140,000 transactions per day. However, their current BI environment was unable to support complex analysis of massive data.

This case study highlights how Kyvos’ OLAP on Azure solution delivers interactive analytics on 12 billion rows, along with the flexibility to scale limitlessly in the future. Download to learn how Kyvos helps them:

In this case study, you will learn how they use Kyvos to:

  • Map buying patterns with customer profile data to offer better experiences
  • Analyze buying patterns over two years to improve forecast accuracy
  • Perform year-over-year analysis historical data to cater to seasonal demand fluctuations