Why has Mews's online check-in feature seen a 30% drop in usage over the past month?

Introduction

Mews's online check-in feature has experienced a significant 30% drop in usage over the past month, raising concerns about user engagement and potential issues with the product. This analysis will systematically investigate the root cause of this decline, considering various factors that could contribute to the decreased usage.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal trend. Has this 30% drop been compared to the same period last year?

Why it matters: Seasonal fluctuations could explain the usage drop without indicating a product issue. Expected answer: No, we haven't compared it to last year's data yet. Impact on approach: If seasonal, we'd focus on strategies to mitigate seasonal dips rather than product changes.

• Considering user segments, I'm curious if this drop is uniform across all user types. Have you noticed any particular user segment more affected than others?

Why it matters: Identifying specific affected segments could point to targeted issues or changes. Expected answer: The drop seems more pronounced among business travelers. Impact on approach: We'd investigate factors specifically affecting business travelers' usage of the feature.

• Thinking about recent changes, has there been any update to the online check-in feature or related systems in the past 1-2 months?

Why it matters: Recent changes could directly correlate with the usage drop. Expected answer: Yes, we implemented a new UI for the check-in process last month. Impact on approach: We'd focus on analyzing the impact of the UI change on user behavior.

• Regarding performance metrics, has there been any change in how we're measuring or defining "usage" of the online check-in feature?

Why it matters: Ensures we're comparing apples to apples in our metrics. Expected answer: No, the definition and measurement method have remained consistent. Impact on approach: We'd rule out measurement issues and focus on actual usage patterns.