Retail Analytics Transformation for Global Fashion Brand
Transformed disparate data sources into a unified analytics platform, enabling real-time insights and data-driven decision making across 500+ stores.
The Challenge
A leading fashion retailer with 500+ stores across 20 countries struggled with fragmented data systems. Sales data, inventory data, and customer data resided in separate systems, making it impossible to get a unified view of business performance. Decision-making was slow, based on outdated reports, and the company was losing market share to more agile competitors.
Key Pain Points:
- Data scattered across 15+ different systems
- Reports took 2-3 weeks to generate
- No real-time visibility into inventory or sales
- Unable to personalize customer experiences
- Missing revenue opportunities due to stockouts and overstock
Our Solution
We designed and implemented a modern data platform that unified all data sources, enabling real-time analytics and machine learning-driven insights.
Our Approach
- 1Conducted comprehensive data audit across all systems
- 2Designed cloud-based data warehouse on Snowflake
- 3Built real-time data pipelines using Apache Kafka and dbt
- 4Implemented Power BI dashboards for different business units
- 5Developed ML models for demand forecasting and inventory optimization
- 6Created self-service analytics capabilities for business users
Technologies Used
The Results
The new analytics platform delivered transformational business impact within the first year of implementation.
"This transformation changed how we operate. We now make decisions based on real-time data, not gut feelings. The ROI exceeded our expectations."
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Let's discuss how we can help you achieve transformational outcomes with your data.