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Product Management Root Cause Analysis Question: Investigating Amazon Ads metrics update failure across campaigns

Why are Amazon Ads metrics not updating for 30% of campaigns?

Problem Solving Data Analysis Technical Understanding E-commerce Advertising Big Data
Amazon Metrics Root Cause Analysis Ad Tech Data Pipeline

Introduction

Amazon Ads metrics not updating for 30% of campaigns is a critical issue that demands immediate attention. This problem directly impacts advertisers' ability to optimize their campaigns and could lead to significant revenue loss for both advertisers and Amazon. I'll approach this issue systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term 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 scope, I'm thinking this might be a systemic issue. Is this problem affecting all types of ad campaigns or specific ones (e.g., Sponsored Products, Sponsored Brands)?

Why it matters: Identifying the scope helps narrow down potential causes. Expected answer: It's affecting all campaign types. Impact on approach: If it's all types, we'd focus on shared systems; if specific, we'd investigate those campaign types.

  • Considering timing, I'm wondering if this coincides with any recent updates. Has there been any significant change to the ad platform or reporting systems in the last 7-14 days?

Why it matters: Recent changes often correlate with new issues. Expected answer: A backend update was rolled out last week. Impact on approach: If there's a correlation, we'd prioritize investigating that update.

  • Thinking about data flow, I'm curious about the update frequency. Are these real-time metrics or do they have a standard delay?

Why it matters: Understanding the expected behavior helps identify deviations. Expected answer: Metrics typically update hourly. Impact on approach: This would guide our investigation into data processing pipelines.

  • Considering user impact, I'm wondering about the consistency of the issue. Is it always the same 30% of campaigns affected, or does it vary?

Why it matters: This helps determine if it's a data or campaign-specific issue. Expected answer: It varies, affecting different campaigns at different times. Impact on approach: If consistent, we'd focus on campaign attributes; if varying, we'd look at system-wide issues.

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