Data-Driven Retail Innovations: Enhancing Customer Experience and Operational Efficiency [Video]

In the ever-evolving retail landscape, the adoption of advanced forecasting techniques has become pivotal in maintaining competitiveness.  Sijo Valayakkad Manikandan, a renowned expert in retail analytics, explores the transformative power of data-driven forecasting models in enhancing both customer experience and operational efficiency.

Revolutionizing Inventory Management through Demand Forecasting

The retail industry has evolved significantly in demand forecasting, transitioning from traditional methods like ARIMA to advanced machine learning models such as Random Forests and Gradient Boosting. These sophisticated algorithms capture complex consumer behavior more accurately, offering retailers numerous benefits, including reducing stockouts by maintaining optimal stock levels and minimizing excess inventory. This evolution not only ensures product availability and higher customer satisfaction but also reduces storage costs and the risk of obsolescence, especially for short-life cycle products.

Personalized Recommendations as Sales Catalysts

Predictive analytics has become a powerful tool for personalizing customer shopping journeys by analyzing individual preferences and behaviors. Retailers use techniques like collaborative and content-based filtering, while deep learning models add …