Objective Business problem Approach Key findings Recommendations
Summary
- The dataset contains information about sample airline bookings, including the number of passengers, sales channel, trip type, purchase lead time, length of stay, flight hour, flight day, route, booking origin, and various flags indicating if the customer wanted extra baggage, preferred seat, or in-flight meals. The dataset also includes the total flight duration and a flag indicating if the booking was completed. This information can be used for various analyses, such as predicting demand, identifying popular routes, and understanding customer preferences.
Purpose
- This report provides a comprehensive analysis of airline booking data using various customer and flight-related metrics. Key insights include the performance of different sales channels based on booking completion rates, popular routes and trip types, and customer preferences for add-on services like extra baggage, preferred seating, and in-flight meals. The analysis also explores how factors such as purchase lead time, flight duration, and travel day impact booking behavior. Geographic trends reveal which countries have the highest conversion rates and demand for premium services. Temporal patterns, such as flight hour and day-of-week trends, help identify peak booking periods. Correlations between trip types, number of passengers, and service requests provide further segmentation opportunities. Overall, the queries aim to support data-driven decisions in route planning, marketing, and customer experience enhancement by identifying areas of high demand, customer behavior trends, and potential operational optimizations across different segments of the airline’s booking ecosystem.
Data dictionnary
| Column | Type | Description |
|---|---|---|
| num_passengers | INT | number of passengers travelling |
| sales_channel | INT | sales channel booking was made on |
| trip_type | DATE | trip Type (Round Trip, One Way, Circle Trip) |
| purchase_lead | DECIMAL | number of days between travel date and booking date |
| length_of_stay | DECIMAL | number of days spent at destination |
| flight_hour | DECIMAL | hour of flight departure |
| route | DECIMAL | origin -> destination flight route |
| wants_extra_baggage | DECIMAL | if the customer wanted extra baggage in the booking |
| wants_preferred_seat | DECIMAL | if the customer wanted a preferred seat in the booking |
| wants_in_flight_meals | DECIMAL | if the customer wanted in-flight meals in the booking |
| flight_duration | DECIMAL | total duration of flight (in hours) |
| booking_complete | DECIMAL | flag indicating if the customer completed the booking |
| flight_day | DECIMAL | day of week of flight departure |
| booking_origin | INT | country from where booking was made |
(1) Booking Behavior Analysis
What is the average number of passengers per booking across all routes?
Which sales channel has the highest booking completion rate?
What are the top 5 trip types by volume of completed bookings?
How does the number of days between booking and travel (purchase_lead) impact booking completion?
(2) Flight and Route Analysis
What are the top 10 most popular routes by booking volume?
What is the average flight duration per route?
Which days of the week have the highest booking completions?
(3) Add-On Services Demand
What percentage of customers opt for extra baggage?
What is the overlap between customers who want all 3 services (baggage, meals, preferred seat)?
How does add-on preference vary by booking origin (country)?
(4) Temporal Patterns
What is the distribution of flights by hour of the day?
Is there a correlation between length of stay and trip type?
(5) Geographic Trends
Which booking origins have the highest completion rate?
Top 5 countries with customers requesting preferred seats the most?
(6) Conversion & Optimization
What is the average purchase lead for completed bookings vs. incomplete?
Which flight routes have the lowest booking completion rate?
Is there a difference in add-on requests between One Way and Round Trips?
What is the relationship between number of passengers and add-on service requests?
Which combinations of trip_type and flight_day are most successful (by completion rate)?
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