Monitor and Improve Streaming QoE KPIs
Conviva Videoprovides a robust set of features to help you establish and monitor the streaming QoE KPIs most critical to your video ecosystem.
Use this list of procedures to benchmark QoE and audience performance and explore the most commonly recommended features for QoE monitoring and issue resolution.
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Use the Experience Insight's Executive email to provide key stakeholders with insights into on-going streaming quality, comparative QoE performance, and engagement trends. Based on Conviva's industry-leading streaming intelligence, you can configure customized emails that showcase visual summaries of KPIs and performance metrics to empower data-driven operational best practices and KPI-based decision making.
Conviva formulates a unified streaming performance KPI based on the percentage of streaming sessions with good or great viewing experience. This KPI represents the Conviva Streaming Performance Index, and is based on the percentage of streams with:
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No errors (VSF-T or VPF-T)
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No or very low Rebuffering (using CIRR)
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Acceptable picture quality based on average peak bitrate for different screen sizes (sessions with playing time over 1 minute)
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Acceptable Video Start Time
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No EBVS if the viewer was waiting a long time before exiting.
For more details, see Executive Emails.
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The AI Alerts feature offers proactive anomaly detection and instant alerts to help shorten time to resolution. This advanced feature eliminates the need to determine the thresholds, identify the relevant dimensions that you need to monitor, and set alerts to notify related individuals and groups.
The Conviva AI Alerting system is continuously checking for anomalies and computes a baseline along with a range of variation for the metric(s) based on the mean and standard deviation derived from historical data. This range of variation is then used to evaluate the traffic in the past few minutes. If the range is exceeded, an anomaly is detected, which then triggers the diagnosis process to determine if an alert should be fired based on the sensitivity control settings and the root cause of the event.
For each generated alert, the system provides the sessions that attributed to the dimensions (or set of dimensions) associated with the root cause of the alerts and the views that were impacted due to the alert.
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Dimensions (Root-cause) |
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For more details, see AI Alerts.
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Use the Trends page to quickly set up one-click and combinatorial filtering to drill-down to specific dimensional entity impacts and perform cross-dimensional root cause analysis.
With one-click filtering, apply logical AND filter rules by clicking a dimension value (for example, Roku AND Houston, Texas). For more advanced filtering, build combinatorial filters, using logical OR and logical AND filter rules, such as (Apple iPhone AND iOS 6.1.0) OR (Apple iPhone AND iOS 6.1.3).
For more details, see Trends Dashboard.
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Video enables easy access to granular QoE metric time series across custom audience segments for detailed diagnostics. On the Diagnostics page, the metric time series provides minute-level granularity; for example the Rebuffering Ratio time series shows data points that represent the average rebuffering ratio value for each minute in the selected time period.
With distributions, Conviva Videousers can also easily uncover a deeper understanding of the per session breakdown of the significance of each metric. The session breakdowns or distributions illustrate the significance of streaming session impacts on the overall metric value to help you determine if the metric value reflects consistent session behavior or session variance caused by outliers. You can also click individual data buckets in the distributions to expand the data range for more detailed analysis and granularity.
Distribution metrics are available for custom time periods, so your analysis of metric distributions can focus on an entire video streaming event, such as a live football match, or specific video stream intervals that contained metric anomalies.
For more details, see Diagnostics and Distributions.
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Once you establish which KPIs are most impacting to your streaming ecosystem, use the Real-Time dashboard to monitor the performance of your most critical streaming KPIs and set visual threshold crossing indicators to quickly identify and correlate changes in QoE metrics.
The Real-Time dashboard supports up to 20 filters and 200 monitored dimension values so you can customize the dashboard settings to focus on the most critical performance, such as Live traffic across channels for tent pole events or All Traffic across assets for on-going operations.
For more details, see Real-Time dashboard.
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