MAVEN UK RAILWAYS

Project Excerpt: UK Train Data Analysis

Project Overview

This project involves the comprehensive analysis of UK train data to identify key performance metrics, passenger trends, and operational efficiencies. The objective is to derive actionable insights that can inform decision-making processes, enhance service delivery, and improve overall customer satisfaction.

Key Objectives

1. Identify Most Used Routes:

   • Determine the top 5 most frequented train routes to understand high-demand travel corridors.

2. Analyze Customer Demographics:

   • Categorize railcard holders and non-holders to tailor marketing strategies and improve customer loyalty programs.

3. Evaluate Journey Status and Delays:

   • Investigate the primary reasons for journey delays, such as signal failures and staffing issues, to develop mitigation strategies.

4. Determine Peak Travel Hours:

   • Identify peak travel times to optimize scheduling and resource allocation during high-demand periods.

5. Assess Average Pricing Trends:

   • Analyze weekly ticket pricing to understand price elasticity and revenue generation.

6. Financial Performance Review:

   • Assess total sales, tickets sold, and refund amounts to gauge financial health and areas for revenue improvement.

Key Findings

• Most Used Routes: Identified Manchester Piccadilly to Liverpool Lime Street and London Euston to Birmingham New Street as the top routes.
• Customer Demographics: Found a significant number of travelers without railcards, highlighting potential for marketing opportunities.
• Journey Delays: Recognized signal failure and staffing issues as leading causes of delays.
• Peak Travel Hours: Morning and evening rush hours were the busiest, with the highest peak at 5 PM.
• Average Pricing: Weekly ticket prices varied, with an average price of approximately £23.29.
• Financial Metrics: Total sales amounted to £741,921 with 31,653 tickets sold and £38,702 in refunds.

Conclusion

The analysis of UK train data provides valuable insights into operational performance and customer behavior. By addressing key delay causes, optimizing peak hour resources, and leveraging demographic data for targeted marketing, train services can be significantly enhanced. This project underscores the importance of data-driven decision-making in improving efficiency, profitability, and customer satisfaction in the rail industry.