Why are Google Assistant custom routines failing for 45% of users?

Introduction

Google Assistant custom routines failing for 45% of users represents a significant product issue that requires immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term implications for the product.

I'll approach this problem by first clarifying the context, then ruling out external factors before diving deep into the product mechanics, user journey, and potential internal causes. We'll generate data-driven hypotheses, conduct root cause analysis, and propose a structured plan for validation and resolution.

Step 1

Clarifying Questions (3 minutes)

• Looking at the failure rate, I'm wondering about the scope. Is this 45% failure rate consistent across all types of custom routines, or are certain types more affected?

Why it matters: This helps us narrow down if it's a global issue or specific to certain routine types. Expected answer: The failure rate varies, with smart home routines having a higher failure rate. Impact on approach: If certain types are more affected, we'd focus our investigation on those specific routines first.

• Considering recent changes, have there been any significant updates to the Google Assistant or related systems in the past month?

Why it matters: Recent changes often correlate with new issues. Expected answer: A backend update was rolled out two weeks ago. Impact on approach: We'd prioritize investigating the impact of this update on custom routines.

• Thinking about user segments, are we seeing any patterns in terms of device types, operating systems, or geographical regions where failures are more prevalent?

Why it matters: This could point to compatibility issues or regional infrastructure problems. Expected answer: Android devices in North America show a higher failure rate. Impact on approach: We'd focus on Android-specific issues and North American infrastructure.

• Regarding the definition of "failure," how exactly are we measuring this? Is it based on user reports, system logs, or a combination?

Why it matters: Understanding the metric is crucial for accurate analysis. Expected answer: Failures are logged when a routine doesn't complete all specified actions. Impact on approach: We'd analyze system logs to identify patterns in incomplete actions.