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Qligent Fights Audience Erosion and Customer Churn with Big Data Analytics

Vision Analytics preserves video distribution quality, viewer engagement, and brand value through advanced analytics.

With infinite video entertainment options available, media delivery quality assurance innovator Qligent now offers a powerful cloud-based solution to monitor the quality of viewer engagement and protect media brand value across multiple delivery platforms. Vision Analytics harnesses the power of data mining, machine learning, and predictive data analytics to help its customers quickly address quality issues and take corrective action. Vision Analytics makes its North American debut in booth N4215 at the 2019 NAB Show, taking place April 8-11 at the Las Vegas Convention Center.

Vision Analytics samples video content globally across any content distribution channel and monitors the viewer’s quality of experience on any platform, network, channel, or app at any given moment—uniquely out to the last mile. Following the mining and analysis of these massive data sets, Vision Analytics gives broadcasters, MVPDs and other content owners a valuable assessment of the health of their media operations, ranging from broad visibility to granular, in-depth reporting.

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“While content can be king, viewers will quickly grow frustrated and move on to alternative content if they experience problems finding, accessing, or watching a particular show,” said Ted Korte, CTO, Qligent. “Viewers are truly in control today, and if their viewing experience falls short of expectations, there are many other networks, platforms, programs, and services to choose from. Subscriber churn or audience erosion is costly and difficult to rectify.”

Vision Analytics not only monitors network performance in real-time, but leverages machine learning and other predictive data science technologies to provide a heads-up about conditions that, left unchecked, could sour viewers on the broadcaster or service provider’s media brand.

“A broadcaster or MVPD can take corrective action to prevent quality of experience issues when armed with a rich data toolset that delivers insight into real-time performance and trends,” said Korte, “Vision Analytics puts the power back in the hands of our customers. These problems can be prevented from happening in the first place when it’s made clear that trouble is brewing.”

Verifiable Datasets

Vision Analytics is designed to handle the “4 Vs” of big data: velocity, volume, variety and veracity. Its engines leverage scalable cloud processing to manage a nearly limitless number of static, dynamic or event-based datasets. All findings are presented on a user-friendly dashboard and reports that summarizes key performance indicators (KPIs), key quality indicators (KQIs), and other vital criteria pertaining to multiplatform content distribution across creation, delivery, and consumption.

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“In the field, we understand that each situation is unique and will require integration and development,” said Korte. “This is simplified by leveraging Qligent’s scalable cloud-based network, customizable third-party data adaptors, last-mile and virtual end-user probes.”

Qligent’s unique deployment of probes creates an end-to-end, controlled data mining environment to produce trusted and secondary opinion datasets within Vision Analytics. The analytics engines are never thrown off by variables, such as operator error, viewer disinterest, or user hardware malfunction. This assures that the integrity and variety of the data is maintained. With a reliable data set, users can develop a host of analysis results, visualizations, and reports to suit unique business needs.

“Data that shows that some viewers abruptly stopped watching a certain show can be misleading,” Korte said. “Did they suffer technical difficulties, or did they just get interrupted or leave for the grocery store? Vision Analytics works only with clean datasets that are devoid of anomalies or suspicions. That eliminates any possibility of a misleading analysis.”

If required, Vision Analytics can also automatically tap into the MVPD’s existing systems such as customer relationship management (CRM) system or Business and Operations Support Systems (BSS/OSS), among other enterprise solutions. For example, Vision Analytics can automatically open a trouble ticket, append a note in a CRM record, send out customer service alerts, or deposit “predictive tickets” outlining potential faults. Such advanced warnings will empower users to make corrective actions that prevent a poor quality of experience for their customers.

“Vision Analytics demonstrated that a 2-3% service improvement delivers a 6% percent increase in concurrent active users, a 10% percent increase in viewing duration, a 90% decrease in repeat complaint calls,” said Korte. “These are only some of the many statistics that prove the power of big data in addressing the customer churn challenge.”

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