Data Analytics

2024 Telecom Transformation Through the Top 10 Data Analytics Strategies

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A technological overhaul in the Telecom industry is vital for customers and organizations worldwide, especially in the era of digitalization, with new technologies accelerating growth and improving telecom infrastructures at a high rate.

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According to Statista,

Digital transformations are profoundly changing the industry, and current trends and emerging opportunities will have a game-changing impact. Among all innovations, Big Data analytics holds a place of relevance:

The global big data analytics market is expected to grow from $198 billion in 2020 to $684 by 2030, with a CAGR of 13.5%.

Big data plays a relevant part in the telecom industry as well. Data analytics companies are rapidly gaining relevance by offering telecom analytics solutions to the biggest players in the industry: here is what is happening.

Telecom analytics and Big Data: what’s the meeting point?

The telecommunication industry has always produced an enormous amount of Big Data: call volume, call duration, call frequency, customer behavior and network traffic are only some of the many types of data collected.

Analytics for media and telecom allow companies to reap many benefits, like data-driven decision-making, increased operational efficiency and improved customer service.

But what are the best use cases of data analytics solutions in telecom industries?

  • Customer experience
  • Price optimization
  • Network optimization
  • Real-time operational analysis
  • Targeted marketing
  • Product development
  • Predictive churn analysis
  • Fraud prevention
  • Recommendation engines
  • Customers attraction

Investing in a good data analytics company to set up the perfect strategy will allow you to leverage the power of Big Data to improve many aspects of your business and drive growth. Read the case study- Data-Ops on Cloud for a North American Telecom Giant

The best strategy for 2024: focus on improving customer experience using data analytics

While industries like Big tech set the bar high, telecommunication companies are lagging in offering good customer experience. However, data analytics technologies can help boost it by gaining more insights into users’ needs and solving issues at every step of the customer journey.

All the following strategies address issues that have an impact on customer satisfaction.

Using data analytics for price optimization

Competition to attract new subscribers is becoming increasingly fierce, and the right pricing strategy is crucial to win over competitors. Using big data to gain accurate customer insights (consumers’ reactions, feedback, purchase history, competitors’ pricing strategies, etc.) is a telecom analytics solution with the potential to identify the perfect price to maximize both ROI and subscribers.

Optimize and manage the network

Telecom analytics companies already use big data to monitor and manage network capacity, but there’s much more potential. Real-time data analytics open up new opportunities:

  • Identify highly congested areas and prevent churns
  • Develop predictive capacity forecasting models
  • Plan data-driven network expansions
  • Implement emergency additional capacities in case of outages
  • Detect anomalies in real time

Switch to real-time operational analysis

There’s more to real-time analysis. An expert data analytics service provider able to collect and analyze data in real-time can apply the insights gained well beyond network traffic control and churn prevention.

A telecom business’s operational side has much to gain from real-time data analytics. For example, it can analyze how the company spends money and resources and identify potential room for more efficiency. Moreover, it is possible to automatize network bandwidth and cell tower ranges in specific locations according to fluctuations in traffic.

Real-time operational analysis can be personalized with the support of a data analytics service company to establish data file format, timelines for data updates, and other parameters to comply with specific business requirements.

Improve your marketing effort with targeting and personalization

One of the biggest benefits of big data analytics is the enormous amount of in-depth customer insights it produces. Big data informs you of customers’ preferences, feedback, purchase decisions, purchase history, service preferences and preferred channels. A detailed analysis of all this data allows you to funnel your marketing efforts in the right direction, better understand your target, and implement personalized marketing.

But is it worth it?

The short answer is yes. The long answer is based on statistics:

Besides being up to 5.3 times more effective in increasing CTR, targeted marketing isn’t used to its full potential by 76% of marketers.

Using data to switch to a more personalized marketing strategy will likely give you immediate results and help you rise above the competition.

Product development and innovation

A very interesting use case of data analytics is its application for new product development. Integrating data analytics into product development presents several benefits:

  • It shortens the process
  • It aligns the product with what the market is asking for
  • It allows businesses to skip some trial-and-error steps
  • It opens up to product improvement and innovation thanks to customer feedback

Overcoming the Biggest Telecom Challenge: Customer Churn

Customer churn is a widespread problem across virtually every industry, but it is particularly serious in the telecommunication market, where it is believed to have reached saturation point. In 2022, customer loyalty to telecom providers was down 22% post-pandemic.

What are the main reasons for churn in telecom?

A comprehensive Telecom Customer Churn survey conducted by TechSee in the US shows that 39% of Americans who canceled a contract with a telecom company in the last two years have mentioned bad customer service as the primary reason.

As we have seen, big data analytics has the power to improve telecom customer experience. Analyzing data and taking informed actions are crucial to preventing customer churn and can be used to develop a predictive model. According to McKinsey, by building a churn predictive model based on hundreds of data points and millions of network usage patterns, advanced analytics can reduce churn by 15%.

Fraud and leakage prevention

According to industry estimates, telcos lose approximately 2.2% of their global revenue to fraud and revenue leakage; in 2021, the loss was valued at $39.89 billion.

Telcos can leverage the power of big data to protect themselves against such fraud. By analyzing tons of data from previous cybercrimes and frauds (including police databases), data analytics can recognize fraudulent communication behavior and suspect phrases, intercept spam emails and block risky calls.

Exploit the potential of recommendation engines

Recommendation engines are sets of smart algorithms and data filtering systems that predict future customer needs using data behavioral data, computer learning, and statistical modeling. The global recommendation engine market was valued at $1.77 billion in 2020 and is expected to grow at a CAGR of 33.0% from 2021 to 2028.

Examples of recommendation systems are Amazon, Netflix, YouTube, and Tinder, which show users new products and content they will likely appreciate.

There are three types of recommendation engines:

  • Content-based filtering: making recommendations based on product attributes (“Similar items include…”)
  • Collaborative filtering: making recommendations based on clusters of users (“People who loved this show also watched…”)
  • Hybrid filtering: a combination of the two methods and the most accurate and efficient.

Recommendation engines do more than just make users buy more products or spend more time on the website; they offer a personalized experience.

Increase new customers’ attraction

Better understanding your target market, powered by advanced data analytics, has two positive outcomes. We already discussed the first: getting to know your customers and reducing churn by improving your offering. The second one is attracting new subscribers by aligning your offerings with real market demands and consumers’ needs.

For example, a large part of the market is now deeply invested in sustainability:

According to Analysis Mason’s survey, 46% of respondents in the USA and Europe considered sustainability level and green credentials to be crucial in their choice of provider.

As explained by Deloitte, sustainability data analytics focus on a wide range of sustainability-related factors to generate insights to guide a sustainability strategy, reduce waste and improve overall resource efficiency.

And with 3 in 4 consumers (76%) stating that companies should take initiatives to reduce their environmental footprint, it is clear that sustainability is vital for the planet and businesses’ bottom lines.

How Data Analytics is transforming the Telecom industry

The telecom industry is undergoing important changes due to new technologies and a constant increase in connected devices. The amount of data generated by telecommunications keeps growing, and now is the time to learn how to take advantage of it.

To thrive in this data-driven environment, providers must be able to use big data in the best possible way to extract as much value as possible. With the right data analytics strategy, telecommunication companies can obtain an important driver of growth and progress.

Abhishek is a vertical marketing lead and data science enthusiast with 9 years of experience. His insightful work and practical experience make him a trusted authority in the field. His impactful contributions extend beyond groundbreaking projects to influential thought leadership, as reflected in his authored publications.

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