Six Ways Data Analytics is Transforming the Global Telecom Industry

Data Analytics has taken the world by storm. Every industry across the globe is leveraging its data to make the most of it and unlock new opportunities for growth. The telecom industry is no exception. With the rollout of 5G networks combined with edge computing, the telecom industry has been making headlines.

Many telecom players today use data analytics to optimize their network utilization and services, thereby enhancing their customer experience and security and increasing their revenue. Earlier this year, Oracle and Vodafone, formed a strategic alliance in Europe to support and extend the operator’s OSS(Operations Support Systems) and BSS (Business Support Systems) services, such as CRM and Order Management, on a dedicated cloud platform. Moreover, global data analytics in the telecom market is expected to register a rapid revenue CAGR of 32.75% between 2022 and 2027, according to a recent report by Mordor Intelligence.

Here’s a closer look at some of the top data analytics applications in the telecom industry today:

Network Management and Optimization 

The telecom industry has begun to implement data analytics in order to efficiently monitor and manage networks and plan network growth strategies. Telecom service providers employ real-time data analytics to identify severely congested areas where network traffic is nearing capacity thresholds and to prioritize the rollout of extra capacity. Using real-time data, they may also develop ways for forecasting and preparing for additional capacity in the event of outages.

Suggested read: Enhancing Network Bandwidth with Big Data

Price optimization

The telecom sector is very competitive, and as a result, telecom service providers must determine appropriate prices for their products and services. Using data analytics, telecom operators can get reliable data insights and develop optimal pricing plans based on customers’ responses to various pricing methods, purchasing history, and competitor pricing.

Predictive Analytics

Data analytics supports telecom companies in better understanding their customers’ preferences and demands by appropriately analyzing hundreds of data points and network usage trends. This enables them to address consumer concerns and offer discounts or incentives to retain consumers.

Customer Segmentation

Data analytics enables telecom service providers to classify their consumers according to their behavior, preferences, purchase history, feedback, and more. Customer segmentation enables network providers to offer customized products and services to the right customers at the right time.

Suggested read: Big Data: The Key to Efficient Decision Making

Product Development and Innovation 

Using data analytics, telecom service providers can create new products and services that are personalized to their consumers’ demands. Real-time data gathered from multiple sources can be used to enhance existing products or create new ones.

Preventing Fraud

The global telecom industry loses billions of dollars annually due to frauds involving illegal access, fraudulent profiles, and abuse of credit/debit card information, among others. As a result, telecom service providers deploy various data analytics and machine learning algorithms to detect and prevent fraudulent user behavior. Using data analysis techniques, these systems discover anomalies, report them to analysts as alerts, and enable real-time response to suspicious activities.

There are various advantages to using data analytics in the telecom industry. By offering clear insights into organizational statistics, implementing data analytics can improve overall competency and contribute to enhanced consumer experiences. Data analytics solutions facilitate the transformation of unstructured data into useful insights, enabling data-driven decision-making and enabling the business to maintain a competitive advantage. To learn more about how we can assist you with using data analytics capabilities, contact our experts at contact@vsplc.com