With the wide proliferation of smartphones and exponential growth in demand for data traffic, the need for faster and seamless connectivity has increased manifold. As such, telecom operators have to deal with a huge pool of heterogeneous data originating from various web and mobile applications that traces geolocation, consumer profile data, call detail record, service usage and billing data.
The burgeoning customer digital footprint leaves behind a huge data trail, which is time consuming and seemingly impossible to analyze by humans to get any meaningful information. This is where Artificial Intelligence (AI) and Machine Learning (ML) techniques come into play. Telecom enterprises are increasingly deploying these tools to predict and analyze consumer behavior on real-time basis, which can then be tapped by marketing agencies and retailers to fast-track their sales.
AI & ML: Redefining Telecom Industry
AI facilitates telecom enterprises to dig deeper into the customer realm and predict the propensity of a customer to buy a product through holistic profiling. It helps to get a cognitive insight into customer behavior, thus helping to better connect with the customers and customize an offering for higher probability of acceptance. At the same time, data monetization and data mining techniques by leveraging subscriber’s data could help unearth new revenue generating opportunities for the company. In addition, AI enables telecom operators to deploy intelligent networks using automation tools that automate back-end processes to lower costs and deploy additional human capital for other value-added analytical work.
ML tools are based on algorithms and information feed provided to the machine. These tools help the telecom firms to gain valuable insight about why customers tend to leave any service provider, thus minimizing customer churning. It enables the telecom enterprises to keep track of customer behavioral patterns and update their policies to ensure customer retention. At the same time, a trained ML algorithm can ensure faster quality checks by automatically producing a list of records with anomalies. This gives maintenance and reliability teams a more focused approach by specifically targeting the anomalous maintenance records and reducing the amount of time spent on reviewing non-erroneous ones, thus increasing project efficiency through more useful findings and recommendations.
In addition to classification of traffic, anomaly detection and network optimization and utilization, both these technologies conflate to form the basis of numerous intelligent technologies that have redefined our daily lives. A few of these developments that affect the usage of telecom networks substantially are:
• Smart Homes: AI has given shape to the concept of Smart Homes that helps remote monitoring and management of Internet-connected appliances and systems, such as lighting and heating. This provides homeowners security, comfort, convenience and energy efficiency by allowing them to control smart devices through a smartphone app or other networked device.
• Self-Driving Cars: The growing autonomous vehicle fleet is a testament to the fact that driverless vehicles are getting closer to being a common feature on public roads. This requires seamless data connectivity and AI to control vehicle speed according to road traffic and sensitive areas to prevent any road casualties.
• Smart Cities: Improving the quality of life for residents of the city, reducing environmental impact and increasing operational efficiency are three prime factors that have led to the evolution of Smart Cities. The essence of a Smart City is connectivity, where embedded telecom infrastructure works as a mesh in which data flows seamlessly and enables tasks with the least human intervention in the smartest possible way.
Telecom Stocks in Limelight
AT&T T: This Zacks Rank #2 (Buy) stock is focusing on AI and ML techniques to automate operations such as common call center procedures, and to analyze and correct network outages. AT&T is using AI to help make the global network more secure, self-healing and self-resilient. The company is also utilizing AI tools to improve traffic flow and manage the rapid growth of video traffic on mobile networks as it moves toward 5G technology.
Windstream Holdings, Inc. WIN: Since Windstream embraced SD-WAN (software-defined wide-area network), it has been able to dovetail into AI. This Zacks Ranks #2 stock has utilized SD-WAN Concierge to enable customers set their own routing policies, based on what SLAs (service level agreements) are more important to their unique business needs. The company is providing customers unprecedented network visibility and control, such as identifying which applications are using the most bandwidth, and prioritizing how that needs to change to deliver against business and customer experience objectives.
Verizon Communications Inc. VZ: Verizon is reportedly using its predictive analytics and ML algorithms to monitor 3GB of data every second streaming from millions of network interfaces — from customers’ routers to an array of sensors gathering operational data. The strategy has been designed to be customer-focused from the ground up in order to reduce customer dissatisfaction and ensure prompt service. On its home networks, Verizon runs automated testing on a sample of 60,000 in-home routers every two hours in order to ensure optimum speed of data connectivity. The strategy is increasingly important for this Zacks Rank #3 (Hold) stock as it moves toward the goal of deploying the first residential and mobile 5G networks at the end of this year.
CenturyLink, Inc. CTL: CenturyLink has applied AI to automate the work of qualifying sales leads in an effort to make its human sales force more effective. This kind of sales automation is particularly effective in helping CenturyLink cost-effectively reach smaller businesses, where the revenue volumes often do not justify using a lot of human capital. This Zacks Rank #3 stock has also boosted its Security Log Monitoring platform by blending ML and AI tools. CenturyLink has updated its network-based Security Log Monitoring platform with correlated threat intelligence, cloud security monitoring and a new mobile app to detect and respond to security threats.
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