The ever-increasing availability of data has provided a host of opportunities for connectivity providers to better serve their customers and grow their business.
Yet, it has also presented many significant challenges as they continue to grapple with managing and integrating vast amounts of data, often from diverse sources, while ensuring it’s of the highest quality, particularly given the stringent compliance requirements placed upon companies.It’s an issue that Riaan Smit, director of business intelligence at plan.com, is acutely aware of.
“Network and service providers are required to proactively build scalable, high-performance infrastructure to handle increasing data volumes,” said Smit. “In most instances, this requires integrating new state-of-the-art technologies with legacy systems and transitioning to the cloud.”
“Operators (especially MVNOs) are, as a result, required to balance cost-efficiency (i.e., capital investment) with delivering high-quality, reliable services in order to provide customer with the personalised, seamless connectivity experiences they demand.”
Smit said that the widespread rollout and adoption of 5G in recent years has been the main catalyst fuelling this big data revolution within the industry. As a result of 5G’s faster speed, he said that low latency and reliable connectivity, data usage per customer has drastically increased and, in turn, fuelled multiple use cases where big data technologies can be used to provide improved customer experience and retention. Thus, he said that service providers are increasingly turning to predictive analytics for insights into base management (i.e., churn), fraud prevention and enhanced pricing strategies.
“At plan.com, we are proactively looking at ways to transform our operations using advanced analytics and, in the process, maximise our value offering to our customers,” said Smit. “A key focus area for the company is to acknowledge its customers as ‘a segment of one’ and, in doing so, offer personalised propositions which are aligned with their individual needs.”
Advanced analytics
All aspects of the underlying customer value chain – from customer onboarding to renewal, said Smit, stand to benefit from advanced analytics. It’s, therefore, important, he said, for service providers to identify the specific area(s) of their business which will get the most from data-driven insights and have a clearly defined implementation roadmap to deliver the final solution.
“At plan.com for example, the customer service function was originally identified as the immediate area of focus as part of the company’s advanced analytics and insights roadmap,” said Smit. “Over the course of approximately six months, the existing customer service processes were redesigned/enhanced through bespoke AI and big data solutions, which resulted in a drastic improvement in most service KPIs.”
Through the use of advanced data analytics and insight, companies can turn data to their advantage. It enables them to drive better productivity, efficiency, customer outcomes and retention, as well as to improve control of their workforce activity and grow their business.
Smit said that through the use of predictive modelling and segmentation, service providers can accurately classify customers based on their behavioural patterns and, in doing so, gain a deeper understanding of their needs and preferences. These insights can, he said, in turn, inform strategies for churn reduction, to upsell opportunities and communication preferences.
“Robotic Process Automation (RPA) has had a significant impact on addressing the cost and production inefficiency of repetitive/manual tasks,” said Smit. “Through the automation of these tasks. service providers have been able to maintain/reduce staff levels and, in the process, reduce costs while increasing overall productivity / accuracy.
“One of the more successful use cases has been the impact of AI-powered virtual assistants in areas such as customer services and operations. These conversational interfaces have resulted in enhanced operational efficiency, reduced response times, as well as lowered operational costs. Personalised customer interactions facilitated by these AI-driven insights also tend to improve customer satisfaction and loyalty.”
Data overload
A big problem with data, however, is that companies can quickly become overwhelmed by the amount they receive and manage. They also need to ensure that they are focusing on the right information.
To achieve this, Smit said that a well-defined and robust data governance framework is an absolute necessity to ensure data is properly curated and seamlessly fed into the respective process which informs real-time decisioning.
“One of the challenges service providers face is poorly structured (legacy) data sources which inevitably result if ‘multiple versions of the truth’ being reported on,” said Smit. “This can be disruptive and have an adverse impact on overall productivity. Ensuring data quality through regular cleansing and validation is therefore crucial.”
He added, “Reliable data sources (structured and unstructured), combined with the recent advances in computation and storage, allows for ‘features’ to be extracted from vast amounts of data. Feature engineering is the process of extracting and combining data in a way which provides valuable/actionable insights.
“This allows service providers to extract and focus on a subset of the data which presents the most valuable (i.e., predictive) insights from the date lake at its disposal. Through this process, service providers can make sense of the (data) chaos in a calculated manner.”
Role of AI
Moving forward, Smit said that AI will play an ever-increasing role in enhancing operations and customer experience, as well as service providers’ overall efficiency. This will, he said, in turn. drive a combination of cost savings, revenue growth and customer retention.
“By utilising AI-powered chatbots and virtual assistants for example, customer inquiries can be handled round the clock, improving satisfaction and reducing opex,” said Smit. “Personalised AI interactions enhance customer loyalty by tailoring services to individual preferences.
“On the other hand, AI-driven process automation such as RPA will drive operational efficiencies, which increases the productivity and accuracy of processes and employees. Predictive modelling capabilities allows service providers to analyse customer behaviour, predict churn, enable targeted marketing as well as proactive retention strategies. Additionally, AI can facilitate revenue optimisation through dynamic pricing and personalised upselling, which allows service providers to differentiate their offering from competitors without diluting revenue.”
plan.com itself has been proactive in introducing AI and advanced analytics across its customer life cycle and business value chain. Evidencing this, in the last year, it has introduced propensity models to inform ongoing customer management strategies related to churn and profitability.
“AI chatbots now form a key part of the customer service operations function and have had a significant impact on operational efficiency as well as cost savings,” said Smit. “The company is also in the process of addressing a number of business use cases using robotic process automation, which is expected to significantly reduce the need for manual processes and, in doing so, free up staff capacity for focus on more high impact deliverables.”