Black Friday data analysis

Black-Friday-Sales-Prediction

 Black Friday marks the beginning of the Christmas shopping festival across the US. On Black

Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and

deals on different product categories. The product categories range from electronic items,

Clothing, kitchen appliances Research has been carried out to predict sales by various

researchers. The analysis of this data serves as a basis to provide discounts on various product

items. With the purpose of analyzing and predicting the sales, we have used three models. The

dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and

prediction purposes. The models used for prediction are linear regression, lasso regression,

ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared

Error (MSE) is used as a performance evaluation measure. Random Forest Regressor

outperforms the other models with the least MSE score.

Introduction

● Black Friday is an informal name for the Friday following Thanksgiving Day in the United

States, which is celebrated on the fourth Thursday of November. The day after

Thanksgiving has been regarded as the beginning of the United States Christmas

shopping season since 1952, although the term "Black Friday" did not become widely

used until more recent decades. Many stores offer highly promoted sales on Black

Friday and open very early, such as at midnight, or may even start their sales at some

time on Thanksgiving. The major challenge for a Retail store or eCommerce business is

to choose product price such that they get maximum profit at the end of the sales. Our

project deals with determining the product prices based on the historical retail store

sales data. After generating the predictions, our model will help the retail store to

decide the price of the products to earn more profits.