Introduction
The recent 20% decrease in conversion rate for first-time visitors to the BigBasket app following the latest update is a critical issue that demands immediate attention. This analysis will systematically investigate potential root causes, generate data-driven hypotheses, and propose a strategic plan to address the problem. We'll examine both internal and external factors, considering technical, user experience, and market-related aspects to develop a comprehensive understanding of the situation.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Establishes a clear timeline for the issue. Expected answer: The update was released on [date] and the drop was noticed within [timeframe]. Impact on approach: Helps narrow down potential causes related to the update.
Why it matters: Identifies if the issue is universal or specific to certain user groups. Expected answer: The impact varies across [specific demographics or device types]. Impact on approach: Guides us to focus on particular user segments or technical issues.
Why it matters: Pinpoints specific problematic areas in the user experience. Expected answer: The most significant drop-off occurs at [specific step in the funnel]. Impact on approach: Allows us to focus our investigation on critical parts of the user journey.
Why it matters: Helps identify if technical issues are contributing to the conversion rate drop. Expected answer: We've seen [number/percentage] increase in reported technical issues. Impact on approach: Directs our attention to potential technical root causes.
Why it matters: Provides qualitative insights into user perception and potential issues. Expected answer: We've observed [specific changes] in user feedback and ratings. Impact on approach: Guides us to investigate specific features or changes that users are responding to negatively.
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