Work / Analytics & Risk Modeling
IndoCabs Cancellation Analytics
A diagnostic of booking cancellations by channel, travel type, and lead time, followed by recommendations for pricing, driver supply, and customer experience.
- Role
- Data analyst and presenter
- Context
- Academic case
- Team
- Project team
- Deliverable
- Analytics case + workbook
Summary
The question
IndoCabs needed to understand why confirmed bookings were canceled and where intervention would matter most across a two-sided transportation marketplace.
What I did
- Profiled the full booking dataset and established a reliable cancellation baseline before comparing segments.
- Tested cancellation patterns across booking channels, trip types, and booking windows to locate concentrations of risk.
- Connected the findings to pricing visibility, driver availability, and targeted operational follow-up rather than treating every cancellation the same.
What it showed
Averages hid the action. Segmenting the cancellation problem revealed which combinations of channel, trip, and timing deserved a different operating response.
From the work
The vast majority of bookings and the highest proportion of cancellations occur within one day of an intended ride. I would advise the company to raise prices on bookings made less than one day in the future, to encourage customers to book in advance, and thus decrease cancellations.
IndoCabs case report, executive summary
Charts and slides
In my words
Like PhillyCycle, this was a case project from my business analytics coursework. I analyzed booking behavior and cancellations, then turned the findings into practical recommendations. These projects helped build the analytics foundation I later drew on as a tutor for the same course sequence.
Documents
- IndoCabs case reportPDF · 12 pages · Excel analysis available