Exploring the 4 top telecom analytics use cases

Data analytics plays a crucial role in the telecommunications industry by turning vast amounts of network, customer, and operational data into actionable insights, enhancing service quality and guiding strategic decisions. Telecom companies leverage big data analytics to optimize network performance, personalize offerings, and reduce costs, using techniques like machine learning and data mining across structured and unstructured data. The analytics process is categorized into descriptive, diagnostic, predictive, prescriptive, and advanced analytics, each serving specific functions from analyzing historical data to providing actionable guidance based on insights. Key use cases include optimizing network coverage using geospatial data, coordinating installations, planning network expansions, and monitoring internet speeds to improve user experience and service reliability. Furthermore, telecom analytics aids in predicting customer churn, targeting marketing efforts, optimizing pricing, and developing new products. Tools like Felt enhance these processes by offering intuitive mapping platforms that transform complex data into easily understandable visual outputs, enabling telecom teams to make informed decisions efficiently. Real-time analytics and key performance indicators (KPIs) are also integral, helping providers manage traffic, improve reliability, and assess performance across networks and customer operations.