Analysing The Way Forward



We dive into how Video Analytics stands of as much importance as the video itself, to leverage content effectively

By Anisha Gakhar

Any technology that helps engage an audience or monetise content, gains attention swiftly. Regardless of how the content is produced or consumed, there is always a need to gain valuable feedback on delivery and consumption. Ongoing experimentation in the production and delivery of content and advertising, has led to the conception of new technologies that help fine-tune the entire process of analysing and leveraging video content.
This is where Video Analytics comes in as an important tool, enabled by Machine Learning (ML), Artificial Intelligence (AI), the Internet of Things (IoT), Big Data, and the Cloud. The trend is gravitating towards actionable ‘People Data’ viewed holistically across each segment of the value chain, instead of the historic, generalised, and averaged statistical data which is no longer sufficiently effective nor insightful.

At Qligent, their focus on Video Analytics is closely knit with other trending technologies such as the Cloud and AI. They specialise in the continuous monitoring and analysis of Quality of Service (QoS), Quality of Experience (QoE), compliance and content verification.
Ted Korte, COO, Qligent, explained, “Broadcasters, service providers and other content distributors have a good amount of data already. The key is to fill in the gaps, aggregate it together, and analyse it as close to real-time as possible. That is the whole idea of a Big Data strategy.”
Most of the new technologies Qligent uses are virtualisable, and leverage various tools that already exist in the Cloud. Their main aim is to deliver the missing delivery analytics pieces by collecting and analysing last-mile, consumption and behavior data, combining Quality of Experience (QoE) data with business impact metrics to form useful, actionable insights.
Since most of the components of their solution are Cloud-based, it is easy for them to start small, and grow out in any direction. IoT and other technologies are making it more cost-effective to gain the missing last-mile and end-user data. With such an approach, companies can afford to test small pieces before investing much. It spells convenience, agility and cost-effectiveness, which aids rapid technology adoption. The benefits of Qligent’s Analysis solution can be reaped in entirety by deploying it across the entire value chain, from content origination to its consumption.
Advances in ML, AI, IoT, Big Data, and the Cloud are key components of Qligent’s solution and approach; from enabling flexible and cost-effective virtual probes, to generating deeper, forward-looking insights from the collected data.

Video Analytics helps traditional media companies compete with IT-rooted technology giants having a grasp on consumer feedback, and now investing into content creation. “We are far past ‘content is king’ and need to follow the interests of individual consumers for both, content and advertising. Large companies can only do this with Big Data – and importantly, reliable data – since consumption and behavior data will not make any sense without a solid understanding of the quality of the service delivered,” added Korte.
For instance, if one imagines producing an OTT service where the highest profile is 4K, it would incur high costs along with time. In a situation like this, it would indeed be of use to learn that the format received by most viewers, oscillates back and forth between 480p and 720p. Not only do they not receive the 4K, but their experience is further degraded from buffering or switching between formats. Video Analytics leverages this information and helps the provider to be able to optimally overcome such issues and deliver a better experience.
Qligent has executed several projects where probes were deployed in thousands, globally, without breaking the budget. It usually deploys a mix of bare metal computing platforms, virtual machines, and Cloud deployments as per the specifics of the client. Currently, it is actively involved in leading a Big Data deployment with a quad-play provider who wishes to understand customer ‘churn,’ as it is one of the major challenges faced by delivery services.
“We have found a way to eradicate the ‘silent suffers’ phenomenon, by collecting data pertaining to who was online and what they were watching when a problem occurred with their service, all within seconds – allowing the provider to reach out to the customer before they had a chance to complain or drop their service,” affirmed Korte.

The tomorrow of media is expected to need a data-driven feedback loop to gain analytics from any type of technology deployed – such as 4K, AR, etc. – irrespective of the type of service offering (OTT, IPTV, OTA, satellite, cable, etc.). Data analytics will cite as a necessity whilst validating the importance and ROI of any add-on implemented.
For example, by tracking the where, when, how, and how long, subscribers are enabled to engage with content and associated targeted advertising in as close to real-time as possible. Wading beyond how traditional ratings systems drove advertising pricing for broadcast television, a blend of QoS/QoE data with viewer-centric information will likely be at the heart of future content monetisation and valuation. “It will take time and experimentation for customers, as the situation and need will be different for each individual media organisation to retain competition,” added Korte
Unless a company has a captive hold on both: their audience and their revenue stream, Video Analytics can prove of utmost essence in the collection and analysis of end-user consumption and behavior data.

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