Case Study: a leading retail establishment improves sales forecasting with Zymr's Azure-based AI solution

a leading retail establishment improves sales forecasting accuracy with Zymr

The client, a leading retail establishment, faced significant challenges in sales forecasting due to noisy and inconsistent data. They struggled to accurately assess the impact of promotions, capture seasonality trends, and integrate external factors like holidays and local events. Zymr was engaged to provide a robust solution to overcome these data quality issues and improve prediction accuracy.

Zymr implemented an Azure-based solution that utilized advanced data preprocessing, classification, and feature engineering. The solution was built using Azure Databricks, MLflow, and Azure Data Factory to create a seamless and scalable pipeline. This empowered the client to accurately discern seasonality, trends, and promotion dynamics, leading to a better understanding of consumer behavior. The solution provided by Zymr delivered unparalleled accuracy and a strategic edge in retail demand prediction.