AI in "Telecommunication"
The Telecom industry is no longer limited to providing internet service, they are the heart of technological growth.
Business Challenges
Telecommunications as an industry has changed along with people's need to connect—faster, more reliable and free from physical constraints. This resilient industry has progressed from landline telephones and dial-up internet connections to delivering mobile-first connectivity to customers constantly on the go. Today's communications serive providers face increasing demands for higher quality services and better customer experience. In order to gain a competitive edge, they need to focus on providing customized solutions to their customers and focus on developing long-term relationships with them.
How can AI help?
Telcoms are investing on gaining opportunities by leveraging the vast amounts of data collected over the years from their massive customer bases. This data is culled from devices, networks, mobile applications, geolocation, detailed customer profiles, service usage and billing data. Telecom industries are harnessing the power of AI to process and analyze these huge volumes of Big Data in order to extract actionable insights and provide better customer experience, improve operations, and increase revenue through new products and services.
Use cases
Network Management, Automation and Optimization: Network management and optimization gives an opportunity to define the score points in operations to identify the root causes of these complications. AI is essential in helping communication providers build self-optimizing networks, which give them the ability to automatically optimize network quality based on traffic information by region and time zone. Looking into historical data and predicting possible future problems or, on the contrary, beneficial scenarios is a great benefit for the telecom providers.
Preventive Maintenance: AI-driven predictive analytics are helping provide better services by utilizing data, sophisticated algorithms and machine learning techniques to predict future results based on historical data. Here operators can use data-driven insights to can monitor the state of equipment, anticipate failure based on patterns, and proactively fix problems with communications hardware, such as cell towers, power lines, data center servers, etc.
Fraud Detection: Telecommunication industry has significant number of users every day who are attracted for fraudulent activity. By applying unsupervised machine learning algorithms to an immense amount of customer and operator data to spot the characteristics of normal traffic you can prevent fraud. The algorithms define the anomalies and with the help of data visualization techniques present them as alerts to the analysts in real time.
Recommendations: The recommendation engine is a set of smart algorithms depicting customers behavior and making a prediction about possible future needs of the product or service. They rely on the analysis of data on user's behavior and predict what they will like by their similarity to others. It also attributes concerning relations between the customer profile and the items the customer chooses.
Real Time Analytics: Due to rapid development of the internet and the evolving of 3G, 4G, and even 5G connections, telecommunication companies face the challenge of the constantly changing customer requirements and Real-time streaming analytics can deal with this task. Real-time analytics combines the data related to customer profiles, network, location, traffic, and usage to create a user-centric view of the product or service. It also captures and analyzes the interaction and communication between the customers.
Why choose us?
The telecommunications industry is at the beginning of an artificial intelligence (AI)-driven shift and soon there will be no looking back.
We at RadomeTech believe AI is crucial for every business entity. Thus we have a developed a tool which lets the user have the power of Artificial Intelligence and Machine Learning !
