You’ve got great content on your streaming video service, so match that content with great viewing experiences for your customers! Take the hard work out of improving the consumer experience and growing your business!
Streaming businesses require real time anomaly detection and resolution to provide the best QoE
In video streaming, there is constantly new content being streamed that varies widely in genre, content type, target audience and video duration. Added to this, there are a host of other variables in the streaming workflow that can influence the quality of viewer experience. It is almost impossible for a business to identify issues in real time by relying on manual configuration of thresholds and alerts and the constant monitoring quality of experience dashboards in person.
Manual issue detection systems do not automatically adapt to your changing service
Rule based alerting of issues are useful to inform every time a predefined threshold is triggered, however they are not able to automatically adjust to the changes in seasonal patterns, user behavior, or any other changes in the key and contributing metrics.
Manual issue detection systems require analysis effort
Manual detection of issues requires knowledge, time and resources to know what to look for and what and how to act on them. Even then, this approach cannot scale to all the metrics that matter to your business. Anomalies can occur in seemingly insignificant metrics, or metrics that no one is tracking through manual alerts.
Using SmartSight QoE to accelerate issue detection and resolution
The SmartSight QoE Anomaly Detection system takes the hard work out of identifying issues. It uses Machine Learning and continuously monitors key quality of experience, engagement and business metrics to trigger alerts in real-time whenever anomalies are detected in the data points. Customers are notified of anomaly alerts through the SmartSight user interface, as well as interactively over Slack, Email or Webhooks for workflow automation.