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Product Management Root Cause Analysis Question: Investigating sudden drop in Xendit's XenInvoice transactions
Image of author vinay

Vinay

Updated Dec 1, 2024

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What caused the sudden 20% drop in successful transactions for Xendit's XenInvoice last week?

Problem-Solving Data Analysis Technical Understanding Fintech Payment Processing SaaS
Data Analysis Fintech Root Cause Analysis Troubleshooting Transaction Processing

Introduction

A sudden 20% drop in successful transactions for Xendit's XenInvoice last week is a critical issue that demands immediate attention and thorough analysis. This significant decline in a core product metric could have far-reaching implications for user satisfaction, revenue, and overall business performance. To address this problem, I'll employ a systematic approach to identify, validate, and resolve the root cause while considering both short-term fixes and long-term strategic implications.

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 product update. Has there been any significant change to XenInvoice in the past two weeks?

Why it matters: Recent changes often correlate with performance shifts. Expected answer: Yes, a new feature was rolled out. Impact on approach: If true, I'd focus on the new feature's implementation and potential bugs.

  • Considering the scale of the drop, I'm wondering about system-wide issues. Have we observed similar declines in other Xendit products or services?

Why it matters: Helps distinguish between product-specific and platform-wide problems. Expected answer: No, other products are performing normally. Impact on approach: If true, I'd narrow my focus to XenInvoice-specific factors.

  • Given the nature of invoicing, I'm curious about seasonality. Is this 20% drop unusual compared to historical weekly fluctuations?

Why it matters: Distinguishes between normal variations and anomalies. Expected answer: Yes, this drop is significantly larger than typical fluctuations. Impact on approach: If confirmed, I'd rule out seasonal factors and focus on recent changes or external events.

  • Thinking about user segments, I'm wondering if this affects all users equally. Do we see any patterns in terms of user types, geographies, or transaction sizes affected?

Why it matters: Helps narrow down potential causes and affected user groups. Expected answer: The drop is more pronounced among SMB users in Southeast Asia. Impact on approach: If true, I'd investigate factors specific to this user segment and region.

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