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Orasi Retail Analytics: A Case Study of a
Fortune 50 US Retailer

"At Orasi, we firmly believe that all data holds vital information that can be converted into actionable insights that are significant in transforming the businesses."

Meet the Fortune 50 Retail Giant

The esteemed client has over 2000 stores across the US. The client faces the unique challenges of synergizing the uniformity of operations of stores that are present in multiple geographies. This is required to ensure that each of its stores continues to offer consistent service along with products that are locally in demand.

Some of the specific challenges are

  • To understand and localize customer sales patterns across multiple locations
  • Go beyond the “region focus”: add variations of products across retail locations on a localized level
  • Understand how their stores’ demographics affect their sales and use the data to offer more location-based products

To meet these challenges, it was important to restructure and revisualize the data in non-conventional ways. Orasi’s retail analytics solution helped the client visualize the data in ways that can help them take location-based, demography-based decisions down to the level of the store and even SKUs. 

The Orasi Solution

  • Changed the client from a regional assortment strategy to clusters that are localized by product attributes and customer demographics
  • Analyzed 750 product categories and clustered their sales by customer buying patterns within each category and across multiple categories using a proprietary algorithm
  • Created a “Decision Tree" in each category, applied it to its clusters, and adjusted them by their stores’ demographics
  • Applied new visual analytics to advise which SKUs were to  rationalize by store, which SKUs needed price changes, and which were to fill gaps in each category’s assortments

Orasi retail analytics opened up critical insights into the sales of these 2000 stores. This helped the retailer achieve increased productivity in the area of demand planning, inventory management and sales. And also furthered the culture of making data-driven decisions.

The key benefits to the retailer

  • Increased $3 Billion in sales while increasing gross margin by 17%
  • Improved faster completion time by 97% (manual two-week process down to an automated thirty-minute process)
  • Time saved in analysis and execution = Expanded analytics capabilities
  • Optimized assortments improved demand planning, inventory turns, and stock-out- rates
  • Improved decision making of category managers for products, as insights from every category directly influenced changes in all the associated categories

Key takeaways

  • Understand the business problem
  • Identify the right data sources to pull from
  • Identify the right tools to be used to build a solution that meets goals and objectives
  • Providing continuous insights into the business

For more details on how you can use Orasi analytics to transform your retail business, get in touch with:

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