Use Case Scenario Example: Cancel a Hotel Reservation

Cancellation policies create many scenarios: cancellation within the free-cancellation window (full refund), cancellation outside the window (fee charged), non-refundable bookings, and cancellations processed by hotel staff vs. the customer online.

Provide the Use Case Description

First, we feed the AI a detailed use case description. For the best results, include preconditions, main flows, and alternative flows. This rich context helps the AI deliver a more accurate and comprehensive analysis. You can also generate a high-quality description using our AI Use Case Description Generator.

Initiate the Analysis

With the description in place, simply click the “Identify Use Case Scenarios & Core Test Cases” button. Our AI engine will then parse the text to understand its logical structure.

Review the AI-Generated Results

In moments, the AI produces a complete analysis. It automatically extracts all relevant Conditions and Actions, presenting them as clear, easy-to-read lists. The most powerful output is the Decision Matrix, which maps every scenario to its specific conditions and outcomes.

Export and Share

Finally, click Export to HTML to save a standalone copy of the analysis. This makes it easy to share with your team, attach to project documentation, or use as a basis for writing formal test cases.

What’s Next?

With this detailed analysis, you have a solid foundation for the next phases of your project. You can now:

• ☑️Automate Cancellation Logic: Implement business rules to automatically apply cancellation policies and calculate refunds based on timing and booking type.
• ☑️Optimize User Interface: Design a clear and transparent UI that informs the customer of potential fees or non-refundable status before they confirm the cancellation.
• ☑️Integrate with Payment Gateway: Connect the system to a payment gateway to process refunds or charge fees seamlessly.
• ☑️Enhance Customer Communication: Use these scenarios to develop a robust notification system for both the customer and the hotel staff.