Objective Business problem Approach Key findings Recommendations
Summary
The goal is to perform KYC ( know your customer) and derive customer and usage insights from the data.
Data dictionnary
| Column name | Type | Description |
|---|---|---|
| Duration | INT | Duration of trip |
| Start Date | INT | Includes start date and time |
| End Date | DATE | Date of transaction |
| Start Station | DECIMAL | Includes starting station name and number |
| End Station | DECIMAL | Includes ending station name and number |
| Bike Number | DECIMAL | Includes ID number of bike used for the trip |
| Member Type | DECIMAL | Indicates whether user was a “registered” member (Annual Member, 30-Day Member or Day Key Member) or a “casual” rider (Single Trip, 24-Hour Pass, 3-Day Pass or 5-Day Pass) |
Exploratory Data Analysis EDA
1. Customer Segmentation & Profiles (KYC)
- What is the average trip duration by member type (Subscriber vs Customer)?
- Which start stations are most popular among Subscribers vs Customers?
- What is the average number of trips per unique user by member type?
- What time of day do Subscribers vs Customers typically ride (e.g., hour of start time)?
- Which bike numbers are used most frequently by each member type?
- What percentage of trips are by Subscribers vs Customers?
- What is the distribution of trip durations (short, medium, long) for each member type?
- What are the top 10 most used routes by Subscribers and by Customers?
2. Temporal Analysis (Time Trends)
- How has the number of trips changed month over month?
- What days of the week have the highest and lowest ridership?
- What is the average duration of trips per month — does it vary seasonally?
- What are the peak hours for trip starts on weekdays vs weekends?
- Are there seasonal trends in usage (e.g., higher trips in summer)?
- How do Subscribers and Customers differ in trip volume over the course of the year?
4. Operational Metrics & Anomalies
- Are there any bikes that were used an unusually high or low number of times (potential theft or disuse)?
- What is the average turnaround time for bikes (time between end of one trip and start of the next)?
3. Geographic Insights (Station Usage)
- Which stations are most frequently used as starting vs ending stations?
- Which station pairs (start → end) are most commonly traveled?
- Are there stations with high one-way traffic (used mostly as start or end only)?
- What are the most common inbound and outbound stations for commuters?
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