CDNs are essential to OTT delivery. But in order to maximize their value, platforms need visibility that goes far beyond standard CDN monitoring dashboards. Traditional metrics, such as cache hits, edge latency and throughput, reveal how the CDN is performing, but not how viewers are experiencing the stream. A CDN can look perfectly healthy on paper while in reality, viewers are struggling with buffering, low bitrates, or delayed start-up times. This gap is why modern CDN analytics and real-time, network-aware analytics software, such as Edge Analytics, have become so important. They expose not only player events but the underlying causes, including routing patterns, traffic handoffs between ASNs, the efficiency of packet paths, and last-mile issues through their QoE impact.

In this article, we explore the metrics OTT platforms should really be measuring, why traditional CDN monitoring tends to fall short, and how a deeper analytics software, such as Edge Analytics, can improve both viewer experience and operational performance.

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Why isn’t traditional CDN monitoring enough?

Although most OTT teams rely on CDN monitoring to understand delivery performance, these tools only show what happens at the edge, not across the rest of the delivery chain. Metrics such as cache hit ratios, edge latency, throughput, and server-side errors are key for checking the health of a CDN, but reveal nothing about what viewers are actually experiencing. As noted by Cloudflare, even when the CDN itself appears to be operating normally, delivery problems including inefficient routing, regional congestion, or origin overload can occur. Research also shows how large-scale studies of commercial streaming services demonstrate that CDNs might return chunks and report stable performance, but users still experience long start-up times and buffering events due to network path variability or client-side bottlenecks.

These blind spots exist because CDNs only provide one piece of the puzzle. They do not monitor ISP performance, last-mile instability, device limitations or the congestion that emerges across the open internet. They cannot detect when a viewer’s throughput collapses after the CDN handover, when a route becomes suboptimal or a region experiences micro-congestion that affects QoE but not CDN metrics. CDNs can report misleading information, causing OTT operators to over-provision, misdiagnose problems, or incorrectly blame churn on content instead of delivery. In reality, the problem isn’t the CDN; it's the lack of end-to-end observability that connects CDN behaviour with the actual user experience.

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The metrics that really predict QoE and churn

In order to understand the real experience of viewers, OTT platforms require metrics that go beyond CDN throughput or cache behaviour. The most reliable QoE indicators are delivered bitrate, rebuffering frequency, start-up time and playback stability, signals that directly reflect the performance of the stream on the viewer’s device. Studies of large-scale streaming systems show that these metrics correlate far more closely with viewer satisfaction and intent to cancel than any server-side statistic. Viewers disengage when the bitrate drops, start-up is slow, or buffering spikes even for a few seconds. These issues often stem from network-path congestion, ISP routing inefficiencies, or last-mile instability, none of which are visible on traditional CDN monitoring dashboards.

Operational metrics also matter, particularly those that reflect efficiency and cost exposure. For example, offload percentage shows how much traffic bypasses the CDN during peak load, thereby reducing reliance on saturated edges and lowering delivery costs. Network-path efficiency, or how well traffic is routed across the open internet, offers an early warning of regional congestion or ISP degradation. Device-level analytics software, including rendition switches and error rates, reveal patterns that influence engagement and the volume of customer support required. Together, these metrics provide a far more accurate picture of QoE, giving OTT teams the insight needed to optimize performance, reduce operational expenditure and proactively prevent churn.

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How Edge Analytics provides the metrics OTT platforms should really be measuring

Edge Analytics provides end-to-end visibility, which is something that traditional CDN monitoring cannot offer. Rather than focusing solely on edge performance, it measures delivery across the entire path, from CDN touchpoints through the open internet and ISPs to the viewer’s device. By tracking real QoE indicators such as delivered bitrate, start-up time, segment retrieval speed, congestion patterns, and real-time QoE signals, it reveals the underlying causes of degradation rather than just the symptoms. This network-aware approach allows OTT platforms to detect regional congestion, ISP routing issues, edge overload symptoms, and last-mile instability long before they escalate into buffering or quality drops. 

However, visibility is only half of the equation. When paired with Edge Intelligence, these video analytics inform real-time delivery decisions directly, meaning the system can bypass congestion, offload traffic away from saturated CDNs and maintain the highest possible resolution for viewers, even during unpredictable peaks. This combination has already proven its worth during major live events, maintaining 95% of viewers at the highest possible bitrate while reducing delivery costs by 50–65%. Edge Analytics provides OTT teams with the tools to improve performance, mitigate churn and scale confidently in regions where CDN infrastructure alone cannot meet demand.

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For more information about our analytics software, Edge Analytics, or to book a call with a member of our team, visit system73.com.

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