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Product Management Root Cause Analysis Question: Investigating grocery average order value decline for an e-commerce platform

Asked at Souq

15 mins

Why has the average order value for grocery items on Souq Now declined by 20% compared to last month?

Data Analysis Problem-Solving Strategic Thinking E-commerce Grocery Delivery Online Retail
E-Commerce Data Analysis Root Cause Analysis User Behavior AOV Optimization

Introduction

The 20% decline in average order value (AOV) for grocery items on Souq Now compared to last month is a significant issue that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our product and business.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into our product, user journey, and relevant metrics. From there, I'll form data-driven hypotheses, conduct root cause analysis, and propose validation methods and solutions.

Framework overview

This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.

Step 1

Clarifying Questions (3 minutes)

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

Why it matters: Seasonal trends can significantly impact grocery shopping behavior. Expected answer: No significant seasonal changes noted. Impact on approach: If seasonal, we'd focus on year-over-year comparisons instead of month-to-month.

  • Considering user segments, I'm curious if this decline is uniform across all user groups. Have we seen any particular user segment more affected than others?

Why it matters: Different segments may have different reasons for changing behavior. Expected answer: The decline is relatively uniform across segments. Impact on approach: If segment-specific, we'd tailor our solutions to those particular groups.

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

Why it matters: Internal changes could directly impact user behavior and AOV. Expected answer: No major changes implemented recently. Impact on approach: If recent changes occurred, we'd focus on analyzing their specific impact.

  • Regarding competitive landscape, have there been any notable moves from our competitors or new entrants in the market recently?

Why it matters: External market forces could be driving users to alternatives. Expected answer: No significant competitive shifts noted. Impact on approach: If competitive factors are at play, we'd need to consider market positioning and differentiation strategies.

  • Considering data integrity, can we confirm that there haven't been any changes to how AOV is calculated or tracked in our systems?

Why it matters: Ensures we're dealing with a real issue, not a data anomaly. Expected answer: No changes to AOV calculation or tracking. Impact on approach: If data issues are present, we'd need to address those before diving into user behavior analysis.

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