5G and IoT platforms are gradually growing complex, because of which the service providers are moving to cognitive technologies like AI and robotic process automation (RPA) in their telecom network operations.
FREMONT, CA: Operating the telecom network operations are becoming more and more complicated than before. It represents an entire catalog of challenges such as legacy, multi-vendor, multi-RAN, multi-technology, along with different billing and proprietary hardware-based solutions.
The operations can extend throughout different organizational segments, for example, technical, marketing, customer care, product planning and strategy, and billing. With 5G and the innovations of IoT devices unfolding, content security policies (CSPs) are challenged with having to take care of an ever-growing number of use cases, as well as new service needs. Meanwhile, it presents an opportunity to alter network operations so that they are independent, proactive, and carry minimal human intervention.
The rising significance of operations provides a great customer experience. Operations are considered to be cost-efficient and also a significant part of customer experience, making telecom network operations a critical aspect to modernize in every way.
As network complications increase with 5G and IoT, it will get challenging to manage telecom network operations without the involvement of cognitive technologies.
Telecom network operations comprise a considerable amount of data processing and analysis and are often categorized by highly manual, cyclic, time-consuming, and alarm-based actions. The implementati
ons of cognitive technologies in telecom network operations offer plenty of direct as well as indirect advantages to the CSP.
Monetization of content based on the usage behavior of the customer and the most accessed media content in the network can be possible. Cognitive network operations can make better decisions in real-time, relying on the popularity of the content along with its access rates, instead of any humans. Additionally, the concept of identifying privileged customer preferences, their usage and behaviors, continuously learning and updating the previously recorded preferences, and providing them customized packages can unleash a plethora of opportunities for the CSP. There is no second thought that the combination of cognitive automation and AI can bring much better network insights.
Cognitive intelligence can be extended similarly; the automated chatbots and customer care agents revert to the customer complaints. It can be used in real-time, learning in super quick time from millions of other similar claims, data points, billing plans, customer’s history of communication along with customer care. According to the analysis of multiple data points, opportunities for upsell can also be easily derived.
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