This project was developed as part of my early data analytics portfolio to demonstrate how data can drive strategic decisions in real-world contexts. Using historical trip data from Cyclistic, a bike-share company in Chicago, I conducted an end-to-end analysis to uncover key behavioral differences between casual and annual riders. The goal: provide actionable insights to support marketing strategies that increase annual memberships.

This project analyzes historical bike-share usage data for Cyclistic, a fictional bike-share company in Chicago. The goal is to uncover actionable insights that will inform the company’s marketing strategy to convert more casual riders into annual members.

Cyclistic’s marketing team wants to understand:

How casual and annual riders behave differently

When and where do rides occur most frequently?

What business insights can help improve conversion rates?

Excel & R – For data cleaning, filtering, and pivot tables

Tableau - Data visualization and interactive dashboards

Descriptive Statistics – To identify trends and usage behavior

Annual members take more weekday trips, especially during commuting hours

Casual riders favor weekends and tourist-heavy routes

Significant opportunity to market membership to casual users via weekday promotions and loyalty rewards

Launch a targeted email campaign promoting discounted weekday membership

Partner with hotels and tourism boards for casual-to-member trials

Create in-app popups encouraging casual riders to upgrade.

The Tableau dashboard PDF is included in this repository. You can view the detailed visualizations by opening the Cyclistic_Dashboard.pdf file.

Cyclistic_Analysis_Report.docx: Detailed report of the analysis and findings.

Cyclistic_Dashboard.pdf: PDF of the Tableau dashboard containing visualizations of the analysis.