Hello and welcome to my GitHub repository for the "Subway Customer Satisfaction Analysis" project. As a data enthusiast, I embarked on this fascinating journey to explore customer satisfaction across various sub sandwich chain restaurants in the USA, with a special focus on Subway.
Project Name: Subway Customer Satisfaction Analysis
Objective: The main goal of this project is to identify key drivers that can potentially boost customer satisfaction and sales for Subway. By analyzing a comprehensive dataset encompassing various American sub sandwich chains, I aimed to uncover insights specifically beneficial for Subway.
The dataset used in this project is a rich compilation of customer satisfaction metrics from various USA-based sub sandwich chain restaurants. It includes a variety of key drivers for every restaurant, providing a holistic view of what influences customer satisfaction in this sector.
In my analysis, I employed a range of data analytics techniques to dissect and understand the dataset thoroughly. The key steps in my approach included:
Data Cleaning and Preprocessing: Ensuring the data is accurate and formatted correctly for analysis.
Exploratory Data Analysis (EDA): Gaining insights and identifying trends and patterns within the dataset.
Key Driver Analysis: Pinpointing the factors that most significantly impact customer satisfaction.
A significant part of my analysis involved using XGBoost, an efficient and powerful machine learning technique. By applying XGBoost, I was able to:
Identify the most influential factors impacting customer satisfaction.
Predict areas where Subway can improve to enhance customer experiences and boost sales.
Through my analysis, I uncovered several key drivers that Subway can adopt to elevate customer satisfaction levels. These findings are detailed in the notebook and accompanied by data-driven recommendations tailored for Subway.
Analysis.ipynb: This Jupyter Notebook contains the complete analysis process, including data cleaning, EDA, XGBoost modeling, and interpretation of results. Sanwiches.csv :the dataset used for the analysis.
This project was an incredible learning experience, allowing me to deepen my understanding of data analytics in the context of the fast-food industry. By sharing my findings, I hope to contribute valuable insights to Subway and other similar businesses looking to enhance customer satisfaction.
Feel free to explore the notebook and use my analysis as a stepping stone for your own projects!