Customer centric success: Navigating with data as your GPS

Data serves as an operator’s most reliable guide on the path to success. Every swipe, every tap, every call, every action offers a universe of opportunities to be leveraged, offering valuable insights into customer behaviour, network performance, and operational efficiency to make data-driven decisions, predict demand, and offer highly personalised services. The more operators know, the more they can provide extraordinary experiences and seize revenue opportunities that are there for the taking.

But those data-driven insights are not ready and waiting. They require some time and effort in the form of data mining. And despite the promising benefits, many operators are still hesitant to fully embrace data mining as a strategy. Concerns over data privacy, the complexity of implementation, infrastructure costs and competing priorities all contribute.

In this article, we explore the advantages of data mining for operators, the reasons behind hesitation, and how we might be able to get past that reluctance to unleash the long-term value of their data.

The benefits of data mining for operators

In an increasingly competitive market, hyper-personalisation has become a key differentiator for operators. Customers now expect services tailored to their specific needs and preferences. Data mining enables operators to analyse vast amounts of customer data to identify patterns and preferences, allowing them to offer bespoke services. This ability to customise services not only improves customer satisfaction but also builds long-term customer loyalty.

Real-time charging and customer value management systems event intelligence can unlock instant revenue opportunities by converting raw data into actionable insights. One simple example is capturing failed calls when roaming. By recognising that a customer has tried and failed to place a call while abroad and reacting with an SMS to suggest a solution, operators can recapture otherwise lost revenue.

By employing data mining, operators are also able to analyse network usage and predict customer demand trends. Insights gained from historical data can help operators make more informed decisions about network upgrades, capacity planning, and resource allocation. Predictive models, for instance, can indicate peak times for network traffic, enabling operators to optimise performance during these periods and prevent service disruptions.

Data mining is also crucial in identifying and preventing inefficiencies in network performance and operations. Analysing network data can reveal bottlenecks, potential failures, or underutilised assets. With these insights, operators can proactively address issues, enhance network reliability, and reduce costs related to unplanned outages and maintenance.

Addressing operator reluctance

One significant barrier to data mining adoption is the perceived complexity of implementation. Operators manage a massive amount of data, and the challenge lies in effectively organising and analysing it. Many make the assumption that AI has to be used to mine data, which comes with its own set of issues relating to safe and responsible usage.

Indeed, the fear of data breaches and misuse often leads to hesitation in fully committing to data mining and data optimization projects. While responsible usage and control mechanisms are feasible, the uncertainty surrounding compliance and risks keeps operators cautious.

However, it’s not the case that AI must be harnessed in order to successfully mine data. Data lakes are another option, with constant automation running on top in order to churn out insights. Orchestration engines are able to consume data from several systems. Pair this with software which takes those insights and converts it into actionable monetisation opportunities, and you have a relatively simple yet effective data mining strategy.

While the software and data storage solutions for data mining are relatively inexpensive, particularly if the operator is cloud-native, there are associated costs relating to resources and expertise, however, which presents another barrier to adoption. Operators often have to prioritise their investments, and with ongoing advancements in technologies like AI and eSIM, data mining takes a back seat. Although the long-term benefits outweigh the initial expenses, the initial financial outlay combined with the time taken to realise opportunities can be a deterrent.

Overcoming reluctance by proving long-term value

Despite these challenges, the long-term benefits of data mining far outweigh the initial hurdles. Operators need to shift their focus from immediate gains to sustainable growth and competitive advantage. Once a data mining strategy is set up, it can continuously generate insights with minimal additional input. By automating data analysis through data lakes and advanced software, operators can unlock revenue opportunities that have been lying dormant for years.

Data mining does not require a full-fledged AI system to start. Instead, operators can gradually introduce automated systems to run on top of their existing infrastructure. This strategy not only reduces costs but also ensures that operators can see early returns on their investment, increasing their appetite for further advancements.

Unlocking untapped potential

Data mining presents operators with a unique opportunity to leverage the wealth of data at their disposal. By enhancing decision-making, predicting demand, and offering personalised services, they can gain a competitive advantage in a saturated market.

Concerns around data privacy, implementation complexity, and infrastructure costs have meant that many have been hesitant to fully embrace the technology. The key lies in recognising that these initial barriers are temporary and that the benefits of data mining can unlock significant long-term value.

By taking small, calculated steps and prioritising investments in data analysis capabilities, operators can transform their business models and capitalise on opportunities that have remained untapped for years. It’s not just about having data; it’s about using it effectively to stay ahead of the competition.

Liz Parry joined Lifecycle Software in 2015 and most recently served as the Chief Commercial Officer, where she drove a growth strategy centred on strategic expansion and on the success of its telecom customers, before becoming CEO in July 2024. Liz has a proven track record of delivering robust solutions that meet the complex needs of modern telecommunications, quickly advancing through various leadership roles at Lifecycle. She has extensive experience in finance and revenue assurance and has been recognised for her management in championing partner projects that provide competitive advantages within the telco industry.