How can we explain the sudden increase in error rates for Highspot's content recommendation engine over the past week?

Introduction

The sudden increase in error rates for Highspot's content recommendation engine over the past week is a critical issue that demands immediate attention. As we delve into this product execution problem, I'll employ a systematic approach to identify, validate, and address the root cause while considering both short-term fixes and long-term implications for our recommendation system.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a recent change in our system. Has there been any deployment or update to the recommendation engine in the past 10 days?

Why it matters: Recent changes often correlate with sudden performance shifts. Expected answer: Yes, there was a minor update to the algorithm. Impact on approach: If confirmed, we'd focus on the changes made in that update.

• Considering user segments, I'm curious about the error distribution. Are we seeing this increase across all user types, or is it concentrated in specific segments?

Why it matters: Helps narrow down if it's a global issue or specific to certain users. Expected answer: The errors are more prevalent among enterprise users. Impact on approach: We'd investigate factors unique to enterprise usage patterns.

• Given the nature of recommendation engines, I'm wondering about content volume. Has there been a significant influx of new content into the system recently?

Why it matters: Sudden content changes can strain recommendation algorithms. Expected answer: Yes, we've onboarded several new enterprise clients with large content libraries. Impact on approach: We'd examine how the system handles large-scale content additions.

• Thinking about system load, I'm curious about usage patterns. Have we seen any unusual spikes in user activity or API calls to the recommendation engine?

Why it matters: Unexpected load can lead to increased error rates. Expected answer: There's been a 20% increase in API calls from a new integration partner. Impact on approach: We'd investigate the impact of increased load and potential optimizations.