ObjectiveΒΆ

Authors:

Cao Tri DO <cao-tri.do@keyrus.com>

Version:

2025-04

Objectives

This article is intended to provide a comprehensive overview of the business objectives in which the project is being developed.

source: https://www.kaggle.com/datasets/ahsan81/hotel-reservations-classification-dataset/data

In this context, the central question of the use case is: Can we predict whether a customer will honor their reservation or cancel it?

The goal is to develop a predictive model capable of estimating, based on booking-related features (such as reservation date, stay duration, booking channel, cancellation policy, and customer profile), the probability that a reservation will be canceled or result in a no-show.

Such a solution would enable hotels to:

  • better anticipate cancellations and adjust their sales strategy accordingly;

  • optimize occupancy rates and revenue management;

  • implement dynamic pricing policies or targeted offers based on cancellation risk;

  • improve operational planning (staff scheduling, supply management, maintenance).

Ultimately, predicting booking behavior supports a data-driven decision-making approach that balances customer satisfaction with hotel profitability and efficiency.