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Qligent to Showcase New Big Data Analytics Platform for Cloud-Based Monitoring at IBC2018

Qligent will demonstrate a big data deployment of its new Vision Service Quality Management platform with real-time processing that offers actionable insights into viewer Quality of Experience

In an effort to communicate the value proposition of real-time analytics in a cloud-based monitoring workflow, Qligent will demonstrate a real-world MVPD deployment of its Vision SQM platform that leverages its second-generation, big data processing engine for viewer satisfaction.

The project verifies the overall Quality of Experience (QoE) that subscribers have while live streaming sports, recording a show, watching video on demand, browsing the program guide, or accessing any other content or service.

With this unprecedented level of real-time delivery analytics to understand each individual subscriber, which Qligent officially launches at IBC (September 14-18, Amsterdam RAI), MVPDs and other service providers can easily identify network performance issues sooner and take swift, decisive action to ensure consistently higher customer satisfaction. Qligent exhibits at Stand 8.E47.

Uncovering Silent Sufferers

As a specialist in cloud-based, enterprise-level content monitoring and analysis, Qligent developed this big data analytics solution as a special engineering project requested through a European MVPD that sought a more detailed understanding of the user experience for its Quad-Play (TV, broadband, mobile and IP phone) services.

“In this highly competitive media environment, people have nearly unlimited options to access rich media content, and once they’re gone, it’s hard to get them back,” said Qligent COO Ted Korte. “Recognizing that ‘churn’ is a big problem that hurts their growth and bottom line, MVPDs want to get out in front of network service issues before their customers become disgruntled, post damaging reviews online, and potentially abandon their service altogether.”

Qligent’s second-generation big data processing solution is especially powerful as it looks beyond the obvious pain points to uncover “Silent Sufferers.” These are the subscribers who experience service difficulties, but never complain to customer service. They just decide to drop the service.

“By proactively reaching out to these suffering users—whether it’s one person or tens of millions—and telling them, ‘We see you had a problem and we’re going to make it right for you,’ MVPDs can show their commitment to delivering that optimal user experience that keeps customers happy, engaged and on-board.”

Automated End-to-End

Qligent will demonstrate the real-world benefits that this special project accomplished, and discuss how other media and entertainment companies can achieve a better understanding of their own end-users’ QoE.

“This fully automated, cloud-based deployment of Vision is designed to handle the ‘three V’s’—volume, variety, and velocity—of big data pouring in from several databases and live systems across the enterprise, as well as data relayed by IOT and virtual probes monitoring the downstream distribution channels out to the last mile,” said Korte. The probes can even double-check and verify that any trouble an end-user is having is indeed being caused by poor network performance, and not false data like “operator error” that can throw off the big picture analysis.”

SQM_Vision_Dashboard

“Vision was deployed for high scalability and throughput using common big data technologies such as Docker Containers, Microservices, and Kubernetes to fit seamlessly within the client’s unique operational ecosystem,” Korte added. “This means tapping into the MVPD’s customer relationship management (CRM), Business and Operations Support Systems (BSS/OSS), media asset management (MAM), and other business systems, as well as Vision’s own QC monitoring database.”

For example, this big data deployment of Vision reaches into the customer’s CRM profile and can open a trouble ticket, send out customer service alerts, and close the ticket once the issue is resolved—all in an automated, real-time manner. The data mining process follows a logical path, sifting through, augmenting, and evaluating multiple layers of voluminous data in real-time to promptly determine how, where, and for how long network performance fell short of customer expectations. With this workflow, Vision’s big data processing capabilities answer the “How is my QoE?” question by first evaluating video and audio quality, whether the right program and ad content aired, and if the set-top box and router is working in the home.

SQM_Charts_VisionBigData

“This big data deployment of Vision is the most comprehensive way that service providers can gain valuable insights into what’s going on across their networks, out to the viewer, so they can take steps to ensure a high QoE for their customers and completely eliminate silent sufferers,” concluded Korte.

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