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Data Analytics in Telecom Industry: A Comprehensive Guide


Trinh Nguyen

Oct 26, 2023

The global big data analytics market is set for remarkable growth, projected to surge from $198.08 billion in 2020 to an astounding $684.12 billion by 2030, boasting a CAGR of 13.5%.

This big data revolution extends to the telecom industry, where vast amounts of semi-structured, structured, and unstructured data are shaping a new era of insights. Data analytics has become pivotal in enhancing customer service, streamlining operations, and driving data-driven decisions within the telecom sector.

This comprehensive guide explores data analytics in the telecom industry, delving into its applications and transformative impact. Let’s get started!

What Is Data Analytics in the Telecom Industry?

What Is Data Analytics in the Telecom Industry?

Data analytics is the science of analyzing raw data and turning it into actionable insights.

In the telecom industry, businesses have been producing enormous amounts of data. A few examples of common data points are call volume, call duration, network traffic, customer behavior, etc.

Today, this huge amount of data is referred to as “Big Data,” an umbrella term indicating the explosion of structured, unstructured, and semi-structured data.

Data analytics or big data analytics has grown in significance in this field thanks to its benefits, including enhanced customer service, efficient operations, and better data-driven decision-making.

Top 7 Use Cases of Data Analytics in Telecom Industry

From pricing optimization to customer experience engagement, data analytics are reshaping the telecom industry. Here are seven key applications you shouldn’t miss out on.

Top 7 Use Cases of Data Analytics in Telecom Industry

1. Customer Experience

Big data analytics could help telecommunication companies enhance customer experience. By boosting LTV (Lifetime Value), sustaining an existing client connection is far less expensive than obtaining a new one, ultimately boosting the business’s profitability.

Telecom data analytics also assists in customer experience personalization. For example, a telecom company can gather customer data on different service-related problems and then develop an automated chatbot to help users resolve these problems whenever possible.

Additionally, by grouping customers into different segments, telecom operators may better understand customer preferences, requirements, and value potential. This results in better customer satisfaction and more successful targeted campaigns.

2. Network Optimization

For users of telecom services, efficiency, speed, and security are essential factors. Customers utilize telecommunications services for many aspects of their everyday lives, and they always anticipate quick, trustworthy, and excellent service from telecom providers.

Telecom analytics tools offer an overview of the network’s performance, with important telecom metrics like network latency, packet loss, MOS score, etc. This enables telecom operators to detect bottlenecks, maximize network capacity, guarantee sufficient bandwidth, and prevent congestion.

In addition, because big data analytics can identify network usage patterns, it can help predict future issues and avoid them by reorganizing network management.

3. Real-time Operational Analysis

Telecom businesses can employ big data for both operation analysis and modification. For instance, by using heat maps, they can track network traffic in real-time and properly adjust the network bandwidth or cell tower range in a specific area or location on peak or off-peak times.

Telecom data analytics can also be utilized to monitor how companies are using their resources to avoid wasting money.

Besides, with real-time operational analysis, businesses can establish a timeline for data updates and define additional parameters, such as preferred file formats, thereby tailoring the best data analysis system to meet their specific business requirements.

4. Predictive Customer Churn Analysis

According to McKinsey & Company, big data analytics can support the telecom sector forecast and minimize customer attrition by 15%.

Preventing the loss of clients requires analyzing customer data and making appropriate adjustments. Data analytics here can track and supervise any drop in service performance continually, model network behavior, and predict future needs accordingly.

Telecom analytics allow operators to proactively reach out to valuable clients who have had incidents of poor-quality services or have voiced unfavorable opinions about the product on social media. This not only helps telecom service providers resolve the problems but also prevents clients from switching to other providers through, for example, discounts and service credits.

5. Price Optimization

In the context of the increased competition in the market to draw in new customers, setting the best prices for their products and services has become vital for telecom operators.

A telecom company can use data analytics to obtain precise and actionable insights into consumer behavior and develop winning pricing plans. This requires you to study customer responses to various pricing strategies, past purchases, and other competitor pricing.

In addition, optimizing the pricing plan based on revenue and profit can also increase sales, attract new clients, and, above all, maintain a loyal customer base.

6. Targeted Marketing

Big data solutions examine how customers utilize telecom services to gain a perception of their behavior. Purchase history, service preferences, and customer feedback analytics would result in an ideal customized marketing campaign that targets just the right audience at the right time.

Also, by doing this, telecom companies can come up with personalized offers and advertising packages for customers to keep their competitive advantage and boost conversion rates.

7. Fraud Prevention

Based on Bankai Group, fraud costs the telecommunications industry between $4 and $6.1 billion annually.

Big data analytics can help protect telecom companies from this fraud by identifying phrases commonly used by cybercriminals and intercepting spam calls and emails. To detect unusual behaviors, analytics also works on common data such as call records, device data, and location data.

Take Sky Shield as an example. This Chinese mobile operator developed an app that uses AI and big data technology to identify fraudulent behavior in the telecom industry. Utilizing the police’s database of fraud cases lets Sky Shield identify fraudulent communication behavior, distinguish it from legitimate communications, and stop spam calls and texts.

Examples of Telecom Companies Using Data Analytics

Several big telecom companies have already begun to leverage big data analytics to enhance customer insights and boost service quality.

1. AT&T

AT&T Logo

AT&T is one of the largest telecom firms in the world, having allocated millions of dollars to developing AI-based network technologies.

Always staying updated with the newest trends in big data and artificial intelligence, they are gearing up the hardware and software for the necessary adoption of fifth-generation (5G) network technology.

AT&T is building cutting-edge AI-enabled networks that will be loaded with massive data collected from multiple sources, such as:

  • Edge computing solutions tailored for IoT devices;
  • Intelligent software-defined networking solutions that provide network configuration, troubleshooting, and management.

2. Deutsche Telekom

Deutsche Telekom Logo

After collecting and analyzing big data for many years, Deutsche Telekom decided to build and provide third-party big data products and services, including:

  • Mobile advertising
  • Smart fleet management
  • Smart parking
  • Soccer analytics
  • Traffic management

Other services that Deutsche Telekom offers include secure hosting and data transfer.

3. Vodafone

Vodafone logo

Vodafone not only collects big data for internal use but also provides it to third parties for business intelligence (BI) tools. Its newly introduced platform, Vodafone Analytics, aids in deriving valuable insights from the collected data.

The solution also helps streamline processes and boost productivity, especially for sectors like retail, real estate, and insurance.

Final Thoughts

In the telecommunications industry, harnessing data analytics is pivotal for profitability. Whether improving customer experiences, optimizing networks, or preventing fraud, data analytics is a game-changer.

As a startup or established player in the telecommunication industry, adopting data analytics is your ticket to staying ahead of the curve.

At Neurond, our expert data analytics professionals are poised to guide you through the journey. From initial consultation and measurement to ongoing monitoring and tailored-modeling, we help you extract the full potential of your telecom analytics strategies. Contact us now and take the first step in optimizing your telecom business with data-driven decisions.