Qligent announces Foresight, a cloud-based service that uses AI, machine learning, and big data to mitigate content distribution issues. Designed to help broadcasters, MVPDs, and OTT service providers understand and correlate factors that contribute to higher audience engagement, Foresight is intended to provide real-time 24/7 data analytics based on system performance and user behavior.
"Foresight uses the data you already have in your plant, plus some new data that you can gather from end user devices, for predictive analysis," said Lang Cooksey, product manager, Qligent. "It's vital to understand how network outages and other technical issues cause problems all the way through to the customer, for example. We're trying to help stop silent sufferers from leaving your service, and predict and prevent customer churn."
Qligent Foresight aggregates data points from end user equipment - including set-top boxes, smart TVs, and iOS and Android devices - as well as CDN logs, stream monitoring data, CRMs, support ticketing systems, network monitoring systems, and other hardware monitoring systems. Using scalable cloud processing, its integrated AI and machine learning provide automated data collection, while its learning technology mines data from hundreds or thousands of layers of data. Big data technology then correlates and aggregates the data for real-time, cloud-based quality assurance.
With its deployment of networked and virtual probes, Foresight is intended to create a controlled data mining environment that is not compromised by operator error, viewer disinterest, user hardware malfunction, or other variables. It is a prevention-oriented toolset designed to predict conditions negatively impacting audience engagement.
Customizable reports summarize key performance indicators (KPIs), key quality indicators (KQIs), and other criteria for multiplatform content distribution. All findings are presented on Qligent's dashboard, accessible from a computer or mobile device.
Foresight is intended to produce revenue protection by helping maintain customer satisfaction and long-term subscriptions by monitoring end user equipment and without including data from receiving devices to help build internal technical support databases.
"We can look into IT asset management systems and say, 'We noticed that the last time a product like this exceeded its warranty, these specific technical problems were resolved through replacement,'" Cooksey said. "This added level of business intelligence can pay dividends for the content or service provider."