Introduction

Introduction#

Retail businesses thrive on understanding their sales patterns. Knowing how much product will sell in the coming weeks allows stores to optimize their marketing efforts and resource allocation. This report dives into the weekly sales data of Walmart’s retail stores to uncover trends and predict future sales. By analyzing factors like holidays, temperature, fuel prices, and economic indicators, I aim to provide insights that can help the retailer make smarter decisions about managing their stores. This analysis uses a dataset from Kaggle

Objectives#

The primary goals of this analysis are to:

  • Explore the historical sales data to identify key factors influencing weekly sales.

  • Develop a predictive model that can accurately forecast sales for each store over the next 12 weeks.

  • Evaluate the performance of different forecasting models to determine the most reliable one for this specific dataset.

  • Provide insights on sales trends and future sales predictions.

Contents