For telco companies in the Asia Pacific region, providing a better customer experience is more important now than ever before. As competition grows and consumers have more options available, poor customer experience rapidly leads to dissatisfaction and high customer churn.
In Singapore, the Institute of Service Excellence at Singapore Management University reported that customer satisfaction scores are down 4% for mobile and broadband providers due to various product and responsiveness-related factors. Network coverage, reliability, data speeds, efficiency and promptness of service all reached year-on-year declines in satisfaction.
Part of the problem is also the lag in rolling out digital services. According to Upstream’s report, APAC telcos in general trail other regions when it comes to digital channels, with 61% of revenues still in physical channels. By comparison, the EU has now switched to 50% digital channels and the US is 91% digital.
Consumers globally have become increasingly reliant on telecommunication technologies due to the Covid-19 pandemic and this reliance is likely to continue post-pandemic. As critical utilities and infrastructure, how can APAC telcos keep up with this increased dependency and accelerated digitalisation, without putting more strain on customer satisfaction and retention?
How graph databases can create more secure networks
Security is increasingly becoming a legal obligation for businesses with heavy penalties for breaches and non-compliance. With critical services reliant on internet connectivity, outages must be avoided at all cost. The problem with modern communication networks is their complexity: with network functions virtualisation (NFV), software-defined networks (SDN), and significant automation, all intertwined with existing infrastructure.
This complexity, along with vital data stuck in siloes, makes troubleshooting extremely challenging. Data volume is increasing, but even more so is the growth in connections (or relationships) between data. Connected data will grow exponentially in the next few years. Traditional databases can’t cope with relationship queries as the number and depth of relationships increase.
Graph data technology is a much more powerful alternative. It’s able to model all the nodes and interdependencies on a network: how and where everything connects, the relationships between entities, and mapping changing/non-static environments. Relationships take first priority in graph databases. Connected data is equally (or more) important than individual data points. In terms of performance, graph databases stay constant even as data grows year on year.
Creating better end-user experiences
Many APAC markets, Singapore being no exception, have seen a surge in competition in recent years. Large incumbents are vying with new digital players for subscribers. Traditional telcos are struggling to manage their cost bases, faced with running retail outlets, legacy services and higher staffing costs, while online-only telcos offer highly customer-centric, 100% digital self-service models. The customer experience (CX) has become all-important to winning and retaining customers.
Graph data technology can play an important role here. It enables monitoring real-time end-user experience for automated responses. For example, Singapore’s Starhub has used graph databases to bundle products and services to maximise value, building a unified database of every product and service with its rules and relationships to ensure that appropriate services are bundled.
By mapping its commercial product line hierarchy in a graph, Starhub has been able to greatly improve its business agility and IT responsiveness. Graph data platforms have also helped optimise customer services by providing real-time information to floor salespeople.
Graphs for improved service assurance
A key aspect of end-user experience is improving service assurance. With 5G and the Internet of Things adding an exponential amount of devices and data to networks, potential issues and failure can also spiral. Graph databases can provide real-time insight into what is actually going on, allowing much earlier detection and resolution. Service disruptions, such as maintenance, can also be predicted and measures taken to mitigate or avoid them altogether.
With multiple options to choose from, users won’t stick around if a telco is offering poor service. Telcos need to embrace next-generation service assurances that leverages a comprehensive, real-time view of services and infrastructure with an eye on end-user experiences, new service creation and predictive modelling.
Internationally, Orange is one example of a telco using graph technology for security insights and overall infrastructure monitoring “and to give us a fresh perspective on IT… and have a bird’s-eye view of all its components”. Orange engineers can then make measurable improvements in the customer experience by re-routing service to minimise disruption, or pre-emptively upgrading vulnerable servers based on their maintenance history.
Specifically, Orange engineers and operators are starting to use graph data technology to create a singular view of operations across multiple networks at once, including cell towers, fibre lines, cable, customers and consumer subscribers or content providers. As a result, they are starting to make measurable improvements in the customer experience by minimising the impact of system maintenance or outages, being able to re-route services during an unexpected interruption, or identifying and pre-emptively upgrading vulnerable servers based on their maintenance history and availability.
From the network graph, to the social graph, to the call centre graph, and the master data graph, telcos around the world have begun to use graph databases to achieve competitive advantage. Graph data technology provides unparalleled performance improvements and agility benefits over relational databases, enabling new levels of performance and insight and helping them maintain a vital competitive edge in an increasingly cut-throat market.
By Nik Vora, Vice President – APAC, Neo4j
This article was first published by The Fast Mode