Created date

February 15, 2018

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An Imperative Journey – Navigating Analytics to Enhance QoE and Open New Revenue Streams

Video analytics has become indispensable for video service providers (VSPs) in improving operational efficiency and customer satisfaction with the ultimate allure of new revenue streams. And although many VSPs have already deployed some form of analytics to help ensure quality of service (QoS) for their service offerings or analyze audience behavior at least at a crude level, most focus only on a narrow subset of data.

Most analytics have tended to be implemented in silos, compromising the ability to integrate them across multiple data sets. As a result, most VSPs have lagged behind the major “digital first” companies like Amazon, Facebook, Google and especially Netflix in the video space.  This is more than a pity because analytics can work strongly to the advantage of VSPs by exploiting their premium assets to the fullest and taking their customers towards new levels of service and quality. Furthermore, there is scope for VSPs to harness their data for new revenue streams by making it available to third parties for marketing or other purposes, subject to rigorous anonymization to protect the identity of the customers involved.

Verimatrix has been at the forefront of analytic development for VSPs and has just sponsored a white paper from ABI Research setting out the benefits of a coherent analytics strategy. The Data Imperative: Maximizing Analytics to Gain an Edge  makes clear that analytics represents a journey for VSPs that will deepen and have an ever-greater impact across all departments, including marketing, operations, products and content development. By migrating away from that siloed approach towards one that pools data in a common repository, VSPs lay the foundation for many of the emerging applications that rely on the integration of different data sets.

The paper identifies four key business drivers for analytics:

  1. Increased Content Consumption – achieved by collecting multiple metrics (minutes viewed, number of channels watched, rental history, etc.) to better identify service issues and understand the risk of churn for individual customers
  2. Increased Monetization – achieved by creating greater personalization through effective targeting, recommendations and promotion of higher service tiers
  3. Improved Service Quality and Efficiency –achieved by optimizing the balance between costs and customer experience by analyzing metrics such as start time, buffering and average bit rate
  4. Continuous Service and Content Improvement – achieved by leveraging the most advanced aspects of analytics relating to improvement of the service and content it delivers, with higher degrees of personalization aimed at boosting the experience even further

Verimatrix has aligned its analytics strategy and portfolio around these drivers to construct a matching four-stage journey with the ultimate goal of achieving results beyond what has been previously considered possible.

The first stage is descriptive analytics, which is essential in providing a foundation for a deeper exploitation of analytic data. At this point, valuable feedback and insights are used to determine consumption trends and factors influencing the customer experience.

At the second stage of predictive analytics, VSPs start being able to forecast trends and ask “what if” questions to assess possible outcomes or customer reactions to service enhancements. One challenge here is to work out which questions are the best to ask; Verimatrix helps VSPs tackle this by automatically creating filters designed to shoulder the burden.

The third stage, prescriptive analytics, adds another layer of sophistication by automating tasks and setting alerts to trigger actions in response to anomalous data values. This can take VSPs into the realm of threat monitoring—anticipating problems or attacks before they occur (or at least nipping them in the bud before any serious business damage has been caused.)

Then the final stage brings in AI and machine learning for deeper exploitation of the integrated analytics data, enabling service self-optimization. Verimatrix has been working to apply AI and machine learning to analytics for some time, and we can demonstrate how this can optimize quality against cost in various ways. For example, metrics can be combined from a variety of sources including the device, access network, Wi-Fi domain and the ISP to develop a surrogate measure of human visual perception. This can then be applied to maintain quality of experience while exploring opportunities to minimize use of network resources. This can all be accomplished automatically without human intervention.

Naturally not all VSPs are ready to exploit these more advanced capabilities but it is important that they at least embark on the journey before they get left behind by their competitors. Our real-time data analytics solution Verspective RT provides the underlying capability through rich data collection from all relevant IP-connected components across managed and unmanaged networks. This includes QoE diagnostics and optimization dashboards which few other tools support. Verspective RT builds an essential foundation for Verspective Intelligence which enables comprehensive business intelligence reporting to drive viewer engagement It is worth emphasizing that security is critical for the successful deployment of analytics because data cannot be made available without customer trust and consent. Given Verimatrix’s background in revenue security, we have the tools and expertise to help companies manage their data in a changing data security landscape, including preparation and readiness for regulations such as the European Union’s General Data Protection Regulation (GDPR), which comes into force on May 25th 2018.

Whether a VSP wants to build out the analytics already in use for QoE monitoring or is starting from a clean slate, Verimatrix has the ideal products and expertise to support that journey.