Subway Customer Satisfaction Analysis

Executed by: Mlsolutions Team

Project Overview:

The Mlsolutions team embarked on an insightful journey to elevate customer satisfaction for Subway, a leading sub sandwich chain in the USA. By meticulously analyzing customer satisfaction data across various American sub sandwich chains, our objective was to distill actionable insights specifically for Subway, aiming to enhance their customer experiences and drive sales.

Project Highlights:

Objective:

Identify and leverage key drivers to significantly boost customer satisfaction and sales for Subway.

Dataset:

Utilized a comprehensive dataset featuring customer satisfaction metrics from numerous USA-based sub sandwich chains, including a diverse range of key drivers influencing customer satisfaction within the industry.

Analysis Approach:

• Data Cleaning and Preprocessing: Initial steps involved ensuring the accuracy and proper formatting of the dataset for nuanced analysis.
• Exploratory Data Analysis (EDA): Conducted a thorough exploration of the data to identify trends, patterns, and insights within the customer satisfaction metrics.
• Key Driver Analysis: Employed statistical methods to pinpoint the factors most significantly impacting customer satisfaction.
• Leveraging Advanced AI Models: A pivotal aspect of our analysis, utilizing cutting-edge AI models to:
  • Determine the most influential factors affecting customer satisfaction.
  • Predict improvement areas for Subway to bolster customer experiences and sales.

Findings and Recommendations:

The Mlsolutions team's analysis revealed several critical drivers that, if adopted, could substantially improve customer satisfaction levels for Subway. These insights, detailed within our analytical notebook, are paired with specific, data-driven recommendations designed to strategically position Subway to excel in customer satisfaction and sales growth.