Why has the average order value for groceries on Flipkart decreased by 20% this month compared to last month?

Introduction

The recent 20% decrease in average order value (AOV) for groceries on Flipkart is a concerning trend that requires immediate attention. As we dive into this product root cause analysis, we'll systematically explore potential factors contributing to this decline, validate our hypotheses, and develop a comprehensive plan to address the issue.

Our approach will involve a thorough examination of internal and external factors, data analysis, and strategic thinking to uncover the root cause and propose effective solutions. We'll consider both short-term fixes and long-term strategies to ensure sustainable growth in AOV.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a seasonal effect. Has this decrease coincided with any particular season or holiday period?

Why it matters: Seasonal trends can significantly impact grocery shopping behavior. Expected answer: It's not aligned with any major seasonal event. Impact on approach: If seasonal, we'd focus on year-over-year comparisons and seasonal strategies.

• Considering user segments, I'm curious about the distribution of this decrease. Is the 20% drop consistent across all user segments or more pronounced in specific groups?

Why it matters: Understanding affected segments helps target solutions more effectively. Expected answer: The decrease is more significant among high-value customers. Impact on approach: We'd prioritize retention strategies for high-value customers.

• Thinking about recent changes, have there been any significant updates to the product, pricing, or promotion strategies in the past month?

Why it matters: Recent changes could directly impact user behavior and AOV. Expected answer: A new discount structure was implemented last month. Impact on approach: We'd analyze the impact of the new discount structure on purchasing behavior.

• Considering data integrity, has there been any change in how AOV is calculated or any known issues with data collection systems?

Why it matters: Ensures we're working with accurate data and not chasing a non-existent problem. Expected answer: No changes in calculation or known system issues. Impact on approach: We'd focus on actual user behavior changes rather than data anomalies.