Premium Airline Case: Diagnosing and Reversing a Decline in Business Bookings
Company: Publicis Sapient
Role: Product Manager
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Other
A premium airline is getting fewer bookings in its business category. How would you work out what is driving the decline and help the airline turn it around?
```hint Locate the drop first
Before proposing fixes, find out how large the decline is, when it started, and whether it is concentrated in particular routes, channels or customer types.
```
### Clarifying Questions
- Does "business category" mean the business-class cabin, or trips booked by business travelers in any cabin?
- How large is the decline and over what period, and is it measured in bookings, revenue or seats filled?
- Are competitors on the same routes seeing the same decline, or only this airline?
- Should my recommendations focus on the airline's digital products, such as booking and customer service, or on its commercial strategy as a whole?
### What a Strong Answer Covers
- A diagnosis that rules out data and capacity explanations, then separates market-wide shifts from causes within the airline's control, in a sensible order
- Segmentation of the decline by route, customer type, sales channel and booking-funnel stage
- Specific data to check each hypothesis, such as funnel conversion, fare comparisons with competitors and customer feedback
- Prioritized recommendations that match the diagnosed cause, with a realistic view of what can be won back
- Metrics to track the recovery, with guardrails such as average fare and cannibalization of other cabins
### Follow-up Questions
- The data shows corporate travel on your routes is down for every airline. What do you recommend now?
- You propose selling discounted upgrades to leisure travelers. How do you stop that from eating into full-fare business revenue?
- Which single metric would you show the executive team to judge whether the turnaround is working?
Overview: An analytical case about a premium airline whose bookings in the business category are falling. It tests structured metric-drop diagnosis, separating market-wide shifts from causes the airline controls, segmenting the decline by route, customer type and channel, and recommending prioritized fixes with metrics that protect fares.