Merchandise Managers Get Instant Data Access with 10,000 Searches Weekly
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- ThoughtSpot Relational Search Engine
- Tableau
Tech Stack
- Relational Search Engine
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Real Time Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Industries
- Retail
Applicable Functions
- Business Operation
Use Cases
- Demand Planning & Forecasting
- Inventory Management
Services
- Data Science Services
- System Integration
About The Customer
The customer is a Fortune 100 Mass Retailer, a large corporate entity operating in the retail industry. This retailer manages massive transaction volumes across millions of customers and relies heavily on data to maintain a competitive edge. The merchandise planning team is responsible for managing thousands of product SKUs to maximize sales and minimize losses from markdowns and stockouts. The team requires visibility into daily sales, customer, and product data from multiple sources to make informed decisions about product displays and markdowns. The retailer's merchandise managers are tasked with analyzing this data to ensure the right products are available to meet evolving customer preferences.
The Challenge
At a Fortune 100 Mass Retailer, merchandise managers were struggling to analyze critical data due to the limitations of their legacy Business Intelligence (BI) tool, Tableau. The system was unable to handle the volume of data and frequent ad-hoc requests, leading to constant timeouts and a backlog for the BI team. As a result, merchandise managers had to spend hours manually building pivot tables in Excel to understand daily performance across product lines. This manual process limited their ability to manage all products effectively, causing them to miss opportunities to improve product margins and meet customer needs.
The Solution
The BI team implemented ThoughtSpot’s Relational Search Engine to provide merchandise managers with a self-service analytics solution. This tool allows managers to analyze their own data without needing assistance from data experts. ThoughtSpot's capability to handle terabytes of data with sub-second response times eliminated the need for the BI team to maintain complex data structures. The solution enabled merchandise managers to perform ad hoc analysis, gaining insights into daily sales trends, market basket assortment, and product profitability. ThoughtSpot is also used across the company for customer insights, product profitability analysis, and order analysis, providing a comprehensive view of customer preferences, purchase history, and web activity.
Operational Impact
Quantitative Benefit
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