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Product Management Root Cause Analysis Question: Investigating sudden increase in late delivery support tickets for online grocery platform

What's causing the sudden 30% increase in customer support tickets related to late deliveries on BigBasket in the past week?

Data Analysis Problem Solving Operational Insight E-commerce Grocery Delivery Logistics
E-Commerce Data Analysis Root Cause Analysis Customer Support Delivery Optimization

Introduction

The sudden 30% increase in customer support tickets related to late deliveries on BigBasket in the past week is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term and long-term implications for our delivery service.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into our product ecosystem, metrics, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and develop a comprehensive plan to resolve the issue and prevent future occurrences.

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 this could be related to a recent system update. Have there been any significant changes to our delivery management system in the past two weeks?

Why it matters: System changes often have unintended consequences on delivery performance. Expected answer: Yes, there was a minor update to route optimization. Impact on approach: If confirmed, we'd focus on technical issues related to the update.

  • Considering user segments, I'm curious if this increase is uniform across all customer types. Are we seeing a disproportionate increase in tickets from any particular user segment, such as first-time customers or those in specific geographic areas?

Why it matters: This helps us narrow down whether it's a systemic issue or related to specific user groups or regions. Expected answer: The increase is more pronounced in urban areas. Impact on approach: We'd investigate urban-specific factors like traffic patterns or local events.

  • Given the sudden nature of the increase, I'm wondering about our delivery partner network. Has there been any significant change in our delivery workforce or partner relationships recently?

Why it matters: Changes in our delivery network could directly impact our ability to meet delivery promises. Expected answer: No major changes, but there's been some turnover in delivery partners. Impact on approach: We'd look into training and onboarding processes for new delivery partners.

  • Considering potential changes in customer behavior, have we recently run any major marketing campaigns or promotions that could have led to an unexpected surge in orders?

Why it matters: A sudden increase in order volume could strain our delivery capacity. Expected answer: There was a flash sale last week. Impact on approach: We'd analyze our capacity planning and demand forecasting processes.

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