In the past few decades, telecommunications companies have not only created a prosperous environment where digitally native companies can grow and provide services to billions of consumers but also facilitated the digitalization of countless industries. And, as entire generations of digital natives expect a different standard for their online experience and network infrastructure costs keep mounting, the telecommunications industry itself is also experiencing a fundamental shift toward new models of operation.
The industry calls it “telecom transformation,” and it is moving network operators into a more customer-centric model, based on services that are on par with the expectations of consumers who not only were online for most of their lives but also expect the best online experiences.
Recent years have shown how large telcos are integrating technological advancements at scale, providing superior online services and products and working hard to transform the customer experience. All of these changes require a data-driven approach to truly transform the telecommunications industry.
What Is Telecom Transformation?
Telecom transformation is an industry term that describes the move from traditional network services toward more user-friendly, dynamic and service-focused business and operating models in telecommunications. This transformation is driven by mounting infrastructure and maintenance costs, a decline in traditional service use (such as SMS or voice calls) as well as changing consumer expectations, among other factors.
Since there are many ways for telcos to transform their services and product offerings for better differentiation, higher customer lifetime value and new revenue streams, every network service operator needs a lot of data to find their focus areas and base their decisions on how exactly they should transform their business.
Data-Driven Telecommunication Transformation Features
While telecommunication transformation can take many forms, as the CEO of a company that develops network intelligence solutions, I’ve found that there are at least a few key data-driven aspects that are worth closer examination.
1. Diversifying Product And Service Portfolios
Telecommunication companies have the opportunity to diversify their offerings to meet customers’ growing needs. Consumers crave services and online experiences that are fast, secure, resilient and dependable. On top of that, there are key customer segments that can greatly benefit from custom service plans, timely upgrade and relevant product offers.
Recent years have also shown the importance of differentiation in the space: As the expectations for online experiences can transform almost overnight, there is a great drive to have more resilience and flexibility. Smart home and IoT usage might also create key opportunities for network operators to provide new services.
Discovering these shifts in user behavior, device use and adoption is key, and I believe truly transformative telcos also leverage big data analysis to make informed decisions.
2. Leveraging Big Data
Even though businesses operating in the telecommunication sector transfer the largest amounts of data, they often have limited insights about their customers. This means that network operators that focus on getting and analyzing data about their user base and service usage gain a major advantage in the market.
Big data can help operators make decisions that are best for their user base. For instance, our company’s research shows that European and American homes vary in IoT usage from 20 to 40%, so only some consumers might benefit from smart home and IoT solutions offered by their telco. In my experience, there are also different levels of smart home device adoption between different network operators.
There are also some key areas that telecommunication companies should optimize with data about their network usage.
• Use predictions about substantial network usage periods for bandwidth allocation to avoid congestion.
• Uncover areas of concern for preventative network maintenance.
• Infer the primary causes of customer concerns and usage patterns to reduce churn and greatly improve customer care.
• Search for technologies, products and services that could transform the entire online experience.
3. Taking Advantage Of Machine Learning
As the telecommunications industry struggles to gain precise data about its network usage, device adoption trends, customer behavior patterns and needs, machine learning algorithms have a substantial role to play in telecom transformation.
Computing and processing the metadata of hundreds of millions of devices is a task for artificial intelligence, an efficient and precise way to identify and classify devices and create device inventories or datasets of device adoption and usage data that help network operators gain those Big Data insights.
By uncovering these datasets, machine learning algorithms help network operators improve the reliability of their networks as well as create new opportunities for their product, marketing and customer care specialists. Telcos leveraging machine learning should look for incongruences in data, carry out root causes analysis, enhance managed services and network optimization.
We live in a technology-dependent, highly-digitalized environment where telecommunications companies are experiencing mounting pressure to transform their businesses. This transformation is what creates data-driven network operators that not only differentiate and improve their services but also gain new revenue streams through data-driven decision-making.
Machine learning is often the backbone for those data-driven decisions, as it allows network operators to uncover new data about their network and user base.