What factors are contributing to the increased buffering ratio detected by Conviva's Video AI for several OTT platforms in the APAC region this month?

Introduction

The increased buffering ratio detected by Conviva's Video AI for several OTT platforms in the APAC region this month is a critical issue that demands immediate attention. This problem directly impacts user experience and could lead to customer churn if not addressed promptly. I'll approach this analysis systematically, focusing on identifying the root cause, validating hypotheses, and developing both short-term fixes and long-term solutions.

Step 1

Clarifying Questions (3 minutes)

• Given the regional focus, I'm wondering about infrastructure changes. Have there been any recent CDN or server deployments in the APAC region?

Why it matters: Infrastructure changes could directly impact buffering performance. Expected answer: Information about recent deployments or lack thereof. Impact on approach: If changes occurred, we'd focus on rollback or optimization; if not, we'd look elsewhere.

• Considering user behavior, has there been a significant shift in peak viewing times or content preferences in APAC recently?

Why it matters: Changes in viewing patterns could strain the system in unexpected ways. Expected answer: Data on viewing trends over the past few months. Impact on approach: If patterns have shifted, we'd need to adjust our content delivery strategy.

• Thinking about content, have new high-bandwidth formats or 4K streams been introduced recently?

Why it matters: Higher quality streams require more bandwidth and could increase buffering. Expected answer: Information on recent content quality upgrades. Impact on approach: If new formats were introduced, we'd need to optimize our delivery for these formats.

• Regarding system health, have there been any alerts or anomalies in server performance metrics coinciding with the increased buffering?

Why it matters: Server issues could directly cause buffering problems. Expected answer: Recent server performance data and any incident reports. Impact on approach: If server issues are identified, we'd prioritize backend optimizations.