Demand Forecasting For a Retail Store

o Data Exploration:

I started by exploring the sales data, visualizing sales trends over time to understand patterns and seasonality.

o Decomposition Analysis:

Utilized seasonal decomposition to break down the data into trend, seasonality, and residual components, gaining deeper insights into sales patterns.

o Model Building:

Employed Exponential Smoothing with seasonal components to build a robust forecasting model, leveraging historical sales data.

o Results:

The model accurately predicted future sales trends, enabling better decision-making and resource allocation for inventory management and business planning.

o Impact:

By implementing data-driven demand forecasting, businesses can optimize inventory levels, reduce stockouts, and enhance customer satisfaction.

GITHUB - https://github.com/13Anush/Demand-Forecasting-for-a-Retail-Store