Breaking market barriers with telecom analytics solutions


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The events of recent years have made it evident that data analytics with artificial intelligence and machine learning is the next frontier of business transformation, while data is rightly considered modern-day gold. The connected network of devices in the world produces vast oceans of data every day. It is up to telecom companies to collect that data, intelligently analyze it, and derive valuable insights. Organizations have begun to realize that those that do not take advantage of analytics intelligence through data stand to miss out on a wide array of opportunities.

The telecommunication sector is almost at the top of the list when it comes to the amount of data being produced daily. From smartphones to broadband and, more recently, 5G networks, the volume of data available to them from their vast subscriber base has immense potential. While market research predicts that the telecom analytics industry is expected to grow at a compound annual growth rate of 14.5% from 2020 to 2027, many companies are at a loss on how exactly telecom analytics can have a profound impact on their business and revenue growth.

Challenges in adopting telecom analytics

Though telecom company stakeholders are aware of the benefits of intelligent analytics, many roadblocks hinder successful analytics adoption. They are unable to unlock any real value from the accumulated data. Let us explore some of the common challenges that telcos continue to face today:

Legacy systems

A good majority of telecom companies house legacy systems that are unable to keep pace with the changing customer requirements. These systems are extremely difficult to maintain, scale or upgrade. Obtaining any kind of usable data from these monolithic systems is often a challenge for companies. With the advent of network optimization, the amount of data produced has seen highs like never before and these internal legacy systems are often unable to cope with its sheer volume, let alone use the data to produce insights.

Data Complexity

Today's telecommunication companies deal with data from a variety of sources like connected devices, 5G networks, websites visited, and other OTT apps like Whatsapp and Facebook. While telcos do realize how this data can be leveraged to gain insights into the customer mindset, its sheer volume, variety, and velocity preventing them from having a comprehensive blueprint to obtain results.

Operational complexity

While the reduced cost for services is certainly a great selling point to get more consumers, providing exceptional service with the right security measures in place is the key to retaining them. The number of high-speed network options has snowballed in the last decade, making it cumbersome for companies to dive through the complex operational setups and gather the right data to analyze.

AI-driven analytics for telcos: Is it really the saving grace?

Experts say that analyzing telecom data to gain intelligence is a sure-shot way to get a foothold in this competitive industry. However, is it the end-all and be-all for better telecom services? Let us delve a little deeper into this.

  1. IoT analytics can leverage a large amount of telecom data available from connected devices and sensors that are spread across various geographical locations. These diversified streams of data can then be combined, validated, and transformed to provide answers to critical problems that companies face. IoT analytics can also be used for network optimization, identifying which products and services will be a hit with the customers and consequently increasing revenue.
  2. IoT analytics can also help identify and predict customer churn patterns by analyzing data and service usage and network failures. Having this information handy and acting on it will help telecom service providers to finetune their operations and increase customer loyalty in the long run.
  3. Telcos can make use of edge computing analytics to use bandwidth more efficiently, increase network visibility and reduce operational costs. Analytics in edge computing also combines advanced processing powers, AI, and state-of-art connectivity and provides intelligence for better connectivity and greater automation.

Telecom analytics of big data allows companies to capture a more sweeping view of their business operations. The data scientist and engineers at Tredence can help with this by providing intelligent insights and last-mile solutions through customer analytics, enhancing network quality, security, and expanding telecom networks. Learn more about Tredence’s telecom services here.

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