Global Examples of Telecom Companies Using Big Data Analytics

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Big data technology gives telecommunications companies access to qualitatively new information and opportunities that give them an advantage on the market and help develop the industry and unlock its hidden potential. Let’s look at the telecom industry’s barriers to overcome today.

The telecom industry is a leader in Big Data strategy because of the vast amount of data it gathers during normal business operations. An operator that serves 8 million prepaid subscribers can generate around 30 million Call Data Records per day, which equals 11 billion records annually. The same operator may also offer post-paid or fixed-line services. This means that there is more data available.

The Role of Big Data Analytics in Telecom Industry

Like any other industry, the telecom industry is faced with many business challenges. Data analytics is a tool that helps companies identify and extract valuable information from data sets and allows them to make crucial business decisions.

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Let’s take a look at some use cases for big data development in the telecom industry:

Network Optimization

Communication service providers must monitor and manage the network capacity to prioritize and plan network expansion strategies.

Analyzing network congestion, service consumption, usage, and other issues can improve network management.

Telecom service providers can access real-time data analytics to determine the network traffic value. This allows them to target specific investments, create good services, or optimize commercial bandwidth value.

Predictive Churn Analysis

The telecom industry can use detailed predictive analytics to analyze data from different devices to forecast traffic patterns and make better investment decisions. This will enable smooth network operation.

These operations can be improved by real-time data insight to monitor and manage service performance drops, predict future demand, and model network behavior.

This helps customers understand their preferences and spot issues such as churn risk. It analyzes millions of network usage patterns and hundreds upon thousands of data points. Mckinsey & Company claims that advanced data analytics can help the telecom sector predict customer churn and reduce it by 15%.

Attracting New Subscriber

Telecom companies can use big data to retain customers and draw new subscribers by providing new content and services. How do they find out what their customers want? Telecom companies can use big data analytics to create a customer persona and predict the needs and interests of their customers.

Flexible offerings and the right content will retain customers and attract new ones. This will increase operator revenues.

Enhance Network Security

The telecom industry must ensure that networks are authentic and confidential to maintain user trust, as it has access to sensitive data.

A Deloitte survey found that security concerns are the primary reason people don’t use mobile payments.

Telecom service providers can identify patterns that could indicate an attack, detect abnormalities, find security threats, and discover vulnerabilities using real-time analysis and customer behavior.

Price Optimization

Telecommunication companies must establish optimal pricing for their products and services due to the increasing competition for subscribers and users.

Data analytics allows the industry to gain precise data insights and create optimal pricing strategies by analyzing customers’ reactions and purchasing history.

How Telecom Industry is Benefitting from Big Data Analytics?

Telecom companies can use Big Data to offer them major benefits and to generate many solutions.

Improve Customer Experience

Customer satisfaction is key to generating loyal customers. Big Data can provide categorized information across users, further assisting in personalizing the customer experience.

Customer loyalty is based on providing excellent services and prompt help when they have questions. Many telecom service provider apps include an automated chatbot that can resolve issues immediately and take the necessary actions.

Targeted Marketing

Companies can use customer data to identify customer behavior, billing, and problem resolution patterns. This allows them to not only resolve customer issues and keep loyal customers but also help target them for the best services.

Companies can provide customers with the best offer by providing real-time information about the expiry date of their pack and data exhaustion before the renewable time in the current day.

Real-Time Operational Analysis

Companies can use big data visualization solutions modify operations when necessary. They can use heat maps to monitor network traffic and respond accordingly. Increase or decrease the range or bandwidth of cell towers in peak hours or off-hours within a particular area.

Analyses can also be used for monitoring telecom’s use of resources, thus preventing waste. This leads to both savings and time.

Operational analysis in real-time helps set the timeline for data updates and determine other parameters (such as preferred file formats) so that a company can best adapt the data analysis system to its business needs.

Reducing Fraud

International revenue share fraud (IRSF) is another highly dangerous fraud for telecoms. According to the Communications Fraud Control Association (CFCA), approximately $4B was lost by the telecom industry to international revenue-sharing fraud (IRSF). The artificial inflation of traffic, or traffic pumping to premium-rate numbers worldwide, causes IRSF. Hackers and fraudsters create traffic and PRN (Premium rate Number) aggregators, which obtain fraudulent premium-rate numbers.

Telecom fraud is the main reason for lost revenue within the telecom industry. The annual cost of subscription fraud in telecommunications is estimated at more than $12B. Others estimate it to be 3 to 10 percent of gross revenue. Telecoms employ fraud detection systems that use data mining algorithms to detect fraudulent customers and suspicious behavior in real time.

Data Monetization

Telecom companies can collect many data about the subscriber, such as demographics and location, network usage, device details and currency, preferences, and so on.

These data can provide insight into useful inferential statistical analysis that telecom companies may not use directly. However, they could be very useful for other businesses.

The service providers set the terms and conditions for such information aggregation.

Telecom companies are not violating these guidelines. They provide data analysis services to various business categories such as retail, advertising, healthcare, and public services. This helps them in their campaigns, retargeting, and personalization, which will help their business thrive.

Top Global Companies That Use Big Data Analytics

These are real-life examples of telecom companies that have successfully used big data strategies.

Vodafone

Many telecom companies decide to collect big data for their own business and share it with third parties using business intelligence (BI). Vodafone is one of these companies. Vodafone Analytics is a platform that provides insights and extracts value from the gathered data. This service optimizes business operations and increases efficiency in retail, real estate, or insurance sectors.

Vodafone Analytics: Reasons to Use

  • Improved understanding of customers
  • Informed decision-making
  • You can save money and use it elsewhere
  • Propositions tailored to the audience
  • Future-proofing is a way to reduce business stress and shocks

AT&T

AT&T is the largest telecommunications company in the world and invests millions in developing AI-based network technology. They need to keep up with the latest trends in big data and AI, and they are working to prepare the company’s hardware and software for the inevitable adoption (5G) of network technology.

AT&T is currently developing an advanced AI-enabled network that will use big data from all sources, including:

  • IoT devices require edge computing solutions
  • Software-defined networking solutions that help with network configuration, management, and troubleshooting.

Reliance Jio

Jio acquired 130 million customers just one year after its launch, thanks to big data. Jio, unlike other companies that underestimate the power of big-data analytics, used it to its full potential and established a dominance in the telecom industry. Jio uses big data analytics to gain a real-time, location-based view of users. Jio has also been able to use data analytics to gather data about consumer habits which will ultimately help them improve customer experience.

Deloitte

Deloitte assisted a large wireless telecom company in implementing a platform. The platform stores, analyze, and stores data from millions of customers and billions of transactions. This allows you to use real-time marketing effectively.

Telecommunication companies must generate insights from the data. These insights help companies better understand their customers and open up new markets. They are also interested in exploring new revenue streams and capturing a larger market share.

The Key Takeaway

The global big data market value was USD 138.9 Billion in 2020. It is projected to rise to USD 229.4 Billion by 2025. There are great opportunities for all industries, including telecoms, thanks to big data solutions. They enable telecom providers to understand better and build trusting relationships with their customers by providing the content and services they most demand. Carriers can also use big data to track equipment and detect fraud. Finding the right software or a vendor who will create a powerful big-data instrument is easy.

Although Big Data is a huge opportunity for the telecom IT solutions, it can also be challenging. However, companies can certainly benefit from it. Big Data analytics allows telecom companies to forecast peak network usage and take

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