Passangers Satisfaction Analysis
This project was created as part of my final assignment in Data Analytics Bootcamp at RevoU
Periode: September 2025
Background Overview
Business Overview :
RevoAirlane is an aviation service company committed to providing safe, reliable, and affordable air transportation. With a vision to become the preferred airline in the regional market, RevoAirlane focuses on operational efficiency, strategic route networks, and enhancing the overall passenger experience.
Business Problem :
Based on dataset (customer satisfaction score) More than half of passengers are dissatisfied.
73,452 out of 12990 passengers gave a dissatisfied rating (56.55%). as a data analyst at revoairlane, the COO asked me to analyze how to increase passenger satisfaction rate by 10% for next month?
Methodology Summary
Problem Analysis : The problem was identified through data reviews, breaking it down to root causes related to increase satisfied rate and passengers dissatisfied.
Data Cleaning & Analysis : The analytical method adopted included descriptive and prediction with predictive model. Google Collab was employed to execute complex Python and extract actionable insights from the cleaned dataset.
Data Visualization : Various visualizations were created, such as bar charts, heatmap to represent trends and relationships within the data, utilizing Tableau for clear and concise presentations of findings.
Insights : Key insights highlighted significant correlations between customer ratings and service factor metrics
Insight and Recommendation:
Based on the findings, actionable recommendations include investing in service factor for high-score rates and implementing a continuous improvement plan to reduce dissatisfied rate for service factors that have highest impact based on prediction .
