Understand the metric in detail: Are there specific routes, airlines, or customer segments that are experiencing a higher cancellation rate? A granular understanding can guide further investigation and potentially lead to more targeted solutions.

Evaluate the trend: Is this a sudden increase or a gradual one? A sudden increase may indicate a specific event or change leading to this outcome, while a gradual increase might suggest more systemic issues or evolving market conditions.

Investigate internal factors: Have there been recent changes in our platform that could have led to this increase in cancellation? This could include changes in UI/UX, pricing, ticketing policy, or even glitches and bugs in the cancellation process.

• For example, if there's been a recent change in the refund policy that is less favorable to customers, this could potentially increase cancellations.
• Alternatively, if a new feature or UI change has made it easier to cancel, this might also inadvertently lead to more cancellations.

Investigate external factors: What external changes might have occurred to cause this? These could include competitive market changes, regulatory shifts, or broader macroeconomic or societal trends.

• For instance, a new competitor's aggressive promotional offers might be causing customers to cancel and rebook.
• Alternatively, new airline or regulatory policies, a public health scare, or economic downturn could be leading to more cancellations.

Analyze related metrics and user behavior: Is there an increase in customer complaints, negative reviews, or a decrease in user engagement? This can provide hints about user sentiment and potential pain points in the customer journey.

Engage with cross-functional teams: Discuss with customer service, operations, data analytics, and engineering teams for their insights and to gather more data points.

Formulate hypotheses and test: Based on the gathered insights, formulate potential hypotheses for the increased cancellation rate.

• For example, if the increase is predominantly for a specific airline, the issue might be with changes in the airline's policies. If it's across all airlines, it could be due to a broader issue like a competitive market change, a platform change, or broader user behavior shift.
• Design tests or data analyses to validate these hypotheses. This could involve A/B tests, user surveys, or deeper dives into user behavior data.

Act based on insights: Once you understand the root cause(s), plan and implement solutions. This could involve improving communication with customers, changing platform features or policies, working with airline partners, or addressing technical issues.