How telecom companies use big data analytics – Top 10 use cases

Sudeep Srivastava January 17, 2022

With the increasing use of smartphones and other connected mobile devices, there has been a surge in the amount of data flowing through the networks of telecom operators. They need to rapidly store, process and extract useful insights from the available data. 

This is where big data analytics comes into play. 

Big data can help telecom companies to increase profitability by helping optimize network usage and services, enhance customer experience, and improve security. 

Big data also provides the telecommunications industry with access to new opportunities. It can improve the quality of service and routing traffic more effectively. By analyzing call data records in real-time, tele companies can also identify fraudulent behavior and act on them immediately. This ultimately gives them a competitive advantage in the market and helps uncover hidden potential.

While you must have got a brief idea about why big data analytics is important for telcos, in the next sections, let us discuss in detail the use cases of big data in the telecom sector and its countless benefits for the telecom companies. 

But before dwelling into the use cases, let us have a brief overview of the global big data analytics market to understand why it is important for your business to tap into the growing market. 

Big Data Analytics Market Overview

As per Valuates Reports, the global big data analytics market is projected to reach USD 684.12 billion by 2030 from USD 198.08 billion in 2020 growing at a CAGR of 13.5% during the forecast period. 

The increased adoption of big data analytics software by various companies to deliver faster and enhanced decision-making by analyzing and acting on information in a timely manner is driving the big data market growth.

Big data and business analytics market

Data analytics in the telecom industry: Use cases

Big data has become important to drive progress in the telecommunication industry. With the right data analytics approach, telecommunication companies can dramatically improve their services and make their subscribers happier. 

Companies and enterprises that implement big data analytics can reap several benefits such as informed decision-making, improved customer service, and efficient operations.

Here are some major big data applications in the telecommunications industry through which your business can reap the numerous benefits of the technology.   

Big data analytics use cases

Network optimization 

The telecom industry is starting to leverage big data analytics to monitor and manage network capacity effectively, build predictive capacity models and use it for planning network expansion decisions. 

With real-time data analytics, the telecom service providers can determine highly congested areas where network usage is nearing its capacity thresholds to prioritize expansion for new capacity roll out. 

Based on real-time analytics, they can also develop predictive capacity forecasting models and plan for additional capacity in case of outages.

Data analytics for telecom can also help detect anomalies and ensure that the network systems execute in a secure, reliable, and efficient manner.

Predictive churn analysis

It takes a lot of effort to engage customers for a long time. Every year a large number of customers in the US stop taking services from their telecom provider due to reasons like poor customer service. 

Analyzing the behavior of customers and taking actions accordingly is crucial to prevent customer churn. Data analytics can help continuously monitor and manage any drop in service performance, model network behavior, and map future demands.

It also helps understand customer preferences and identify issues like churn risks by accurately analyzing hundreds of data points and millions of network usage patterns. According to Mckinsey & Company, the telecom industry can predict and reduce customer churn by 15% using advanced data analytics.

For example, data analytics in the telecom industry can help operators proactively reach out to high-value customers who have experienced a series of quality issues or reported negative experiences regarding the service on social media.  

This would help service providers to address the issues and offer discounts or service credits to prevent customers from leaving their services. 

Price optimization

With the rising competition in the market to attract more subscribers, it has become crucial for telecom operators to set optimal prices for their products and services. 

With the help of data analytics, telecom operators can gain accurate data insights and create optimal pricing strategies by analyzing customers’ reactions to different pricing strategies, purchase history, and competitor pricing. 

In addition, telecom providers can maximize their ROI, identify the perceived value of their product or services, and improve their sales team’s effectiveness. 

Optimizing the pricing strategy based on profit and revenue earned can boost sales, help gain more customers, and most importantly, retain loyal customers. 

Attracting new subscriber

Big data for telecom industry helps companies retain customers and attract new subscribers by offering new services and content. But how do they know what their customers want? Big data analytics helps telecom companies to build a customer persona and guess the needs and interests of their customers. 

The right content and flexible offerings retain old customers, attract new ones, and increase operator’s revenues. 

Let’s take Netflix for example. It earns up to 75% on purchases offered by a recommendation system based on both personalized and collaborative algorithms. 

Targeted marketing

Big data solutions help understand customer behavior by reviewing how they use the services offered by the telecom. A detailed analysis of purchase history, service preferences, and customer feedback enables customized product offering to target the right audience at the right time.

This way, they can develop personalized offers and advertising deals for customers, maintain competitive advantage, continue steady development, and improve conversion rates.

Preventing fraud

Based on industry estimates, telcos annually lose approximately 2.8% of their revenues to leakage and fraud, costing the industry approximately US $40 billion every year. 

Big data analytics can protect the telecommunication industry against such fraud. It can recognize phrases typical of cybercriminals and intercept spam mailings and calls. For instance, a Chinese mobile operator launched an app called Sky Shield, which utilizes big data and AI technologies to prevent fraud in the telecom sector. 

The police provided the developers with a database of fraud cases that helped Sky Shield to recognize fraudulent communication behavior, differentiate it from normal calls, and intercept spam calls and texts. 

[Also Read: How machine learning helps in financial fraud detection]

Product development

There’s no denying that developing a product is a complex process that requires control and careful management. Integrating data analytics can ensure the product’s high-quality performance according to the customer’s requirement.

Data analytics for telecom helps in the data-driven product development process, internal feedback, and marketing intelligence.

Product innovation

The real-time data from multiple sources can be used to improve the products offered by telecom. They can also analyze customer usage to develop new and innovative products that will serve users’ needs and save money. 

One of the perfect examples of such an innovative feature offered by telecom is the ability to use their Wi-Fi service from anywhere. The customer only needs to log in, and they can use the Wi-Fi whether they are at home, in a restaurant, a coffee shop, or at the airport.

Performing preventive diagnostics

Using data analytics telcos can identify patterns of system behavior that precede the occurrence of failures and determine the causes of such failures. 

Early diagnosis helps operators to plan preventive maintenance, replace and repair equipment.

Predictive analytics based on big data can also help the operators to analyze the intentions of their customers by taking information from their social networks. Big data also allows telecom providers to find influencers among their customers.

Recommendation engines

The recommendation engine is a set of smart algorithms that indicates the customer’s behavior. On the basis of that behavior, it predicts the future needs of customers. Recommendation engines make use of both collaborative filtering and content-based filtering approaches.

Content-based filtering uses the attributes that show the relationship between the customer profile and the product or service a customer chooses. Collaborative filtering, on the other hand, relies on the analysis of data according to the user’s preferences and behavior.

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Real-world examples of telecom companies using big data analytics

Big data is a fuel that can and will drive the entire telecom industry towards better customer service and higher revenue. A few big telecom companies have already started leveraging big data analytics to improve their quality of service and get better insights into consumer behavior. 

telecom companies using big data analytics

Here are a few real-world examples of telecom companies that have been utilizing big data to their full advantage. 

Vodafone: Vodafone has been leveraging big data and artificial intelligence to understand customer preferences better and deliver instant customer services. By integrating data analytics, Vodafone has been able to track the voice and data consumption behavior of users and offer the most appropriate plan or pack options to them.

Reliance Jio: With the help of big data, Jio acquired 130 million customers within one year of its launch. While other companies have been underestimating the power of big data, Jio used it to its full advantage and successfully established an empire in the telecom world. They are making use of big data analytics to get a real-time and location-based view of users. Data analytics has also helped Jio to collect data on consumer habits, which ultimately helps them to enhance customer experience

Now that we have looked into how companies use big data to accelerate growth, let’s see how our experts can help in your big data journey. 

How Appinventiv helped a telecommunication company in their big data journey

We recently helped one of our clients in the telecom sector to enhance data quality and consistency by offering them data analytics services. Our first step was to store and analyze data on the cloud using a broad spectrum of Apache technologies.

This helped us to streamline the unwanted data cluster and analyze and prioritize data on one centralized platform in real-time. Our data analytics approach, coupled with ETL tools, resulted in a master repository that provided a 360-degree overview of our client’s 90 million+ customers. 

We followed an agile methodology to create an ecosystem that could process high volumes of data and classify it according to customer behavior and preferences.

The result? Our dedicated efforts led to an 85% increase in data quality and accessibility and 100% availability of customer data to every department of the organization.  

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Conclusion 

The advantages of using big data in telecom are countless. From improving customer experiences to offering clear insights into business trends, the implementation of big data analytics can enhance your business’s overall proficiency and effectiveness. 

At Appinventiv, our team of data analytics service professionals help you implement big data analytics while taking care of all your data challenges at the same time. Our big data solutions help transform unstructured data into actionable insights, enable data-driven decision-making, and assist you in staying ahead of the competition. Hire our experts. We will have all your needs covered!

Sudeep Srivastava
THE AUTHOR
Sudeep Srivastava
DIRECTOR & CO-FOUNDER
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