mahalakshmii-s/machine-learning-project

Deciphering how customer's purchasing habits are influenced by wholesale pricing and examining its impact on final retail cost.

MACHINE-LEARNING-PROJECT

Title:

DECIPHERING HOW CUSTOMER’S PURCHASING HABITS ARE INFLUENCED BY WHOLESALE PRICING AND EXAMING ITS IMPACT ON FINAL RETAIL COST

About the dataset which i've used for this project:

Dataset containing five years of customer orders, resulting in thousands of products sold. The records comprise requests from 2017 to 2021. The data was adapted from the JMP Case Study Library.

Scope and objective:

• The project is to develop and implement the Machine Learning models for predicting the retail price with the wholesale price to enhance the total selling and to improve the pricing strategies for the marketing development.

• The main objective is to despite the availability of wholesale pricing, retail businesses struggle to accurately predict and adjust their retail prices to align with changing wholesale costs, leading to potential profit losses and customer dissatisfaction.

Business Problem Statement:

• Retail industries are facing the challenge of effectively understanding and adapting to the procurement patterns of patrons.

• Despite the availability of wholesale price data, there exists a gap in leveraging this information to predict retail prices accurately.

• This project aims to address this gap by developing a comprehensive analysis of patron procurement patterns and their correlation with wholesale prices. By deciphering these patterns, business can optimize their pricing strategies, enhance customer satisfaction and improve competitiveness in the market.

Analytics Tools:

Python & Machine language libraries.

Analytics Approach:

Machine Learning (Linear Regression, SVR, Decision Tree Regressor, Random Forest Regressor, SVR Poly, Gradient Boosting Regressor).

Conclusion:

The best model is SVR Poly.

Retail prices are much higher than wholesale prices.

Predictions considering Linear Regression and SVR Poly are similar.

Clothing is the category that sells the most and Indoor sport is what sells the least.