The world grows more digital by the day. It’s become a simple matter for network subscribers to jump ship to a competing operator if they run into service glitches or find a better pricing plan. There’s no longer any need to visit a brick-and-mortar store: customers simply activate new services online, thanks to the digital on-boarding solutions that many providers now offer.
In 2021 and beyond, the opportunity for customer churn will only intensify as new 5G-based services hit the market. 5G providers will find themselves pressured to gain and retain customers to earn the revenues they require to recoup and profit from their huge 5G infrastructure and spectrum investments. Success, in large part, requires finding ways to tightly control customer experiences such that they meet or exceed the ultra-high expectations of modern-day subscribers.
Take a walk in each customer’s shoes
Creating customer loyalty and stickiness in the 5G era requires operators to understand customers’ real-time service experiences much more deeply and at an individual subscriber level. Only when they know what’s occurring from the individual subscriber point of view can they take corrective action, if needed, or capitalize on individual buying trends with targeted services and promotions to delight customers and create revenue.
The traditional internal view of network operations alone is no longer enough because it often doesn’t match what the customer sees. Network monitors might indicate that all systems are a go, for example, while a subscriber might actually be having connectivity difficulties, experiencing dropped calls, seeing a choppy video, or experiencing any number of other issues that could drive a change in providers.
Seeing exactly what the customer sees requires collecting and analyzing data, both historical and real-time, from myriad sources inside and outside the operator’s network. That means merging traditional internal network monitoring data with external data about the subscriber’s location, device manufacturer and software version, service subscriptions, access network in use, and even social media. Aggregating and analyzing this internal and external data with the help of automation allows operators to deeply understand individual subscriber experiences and behaviours. That information gives them the power to act accordingly to improve service, offer appropriate new services to specific customers, build customer relationships, and win loyalty.
Training algorithms and finding opportunities
Aggregated internal and external data can be used to train machine learning algorithms to identify the complex relationships between the operator’s key quality indicators (KQIs) and the customer variables mentioned (location, device, service subscriptions). These algorithms can then be applied to deliver operator insights into how network operations are impacting subscriber experiences on a micro-segment basis.
Creating a 360-degree customer experience view in this way requires the use of real-time analytics, real-time stream processing, edge analytics, and machine learning. A system that continually collects, correlates, and analyzes data from every relevant source helps operators avoid losing subscribers before even realizing there’s a problem.
Protecting an operator’s streaming video customer base provides a good example. Third-party content providers — often called over-the-top or OTT companies — piggyback on the networks of incumbent communication service providers (CSPs) to deliver video streaming and content services to that CSP’s subscribers. OTTs have become fierce competitors to the CSPs’ own content services. Smart operators monitor their own video services and which OTT services (Netflix, Hulu, Amazon Prime, and so forth) their customers use to determine if they’re losing market share to the OTTs. If they are, they can now apply analytics tools to win some of that business back.
Analytics reveal exactly what customers are experiencing with the CSP’s video services. If subscribers have unstable or poor video experiences, they are ripe for the taking by the OTT provider. Those subscribers should become immediate candidates for network improvements. Subscribers already showing strong experiences and high levels of satisfaction, on the other hand, might be targeted with a marketing campaign for new or additional video services or new pricing packages.
Personalizing services also helps build customer relationships and loyalty. Many operators tend to have multiple systems that look at different aspects of a customer; however, they can consolidate that source data and run analytics to get a complete picture of the subscriber, including preferences and behaviours, so they can treat each customer appropriately.
For example, we’re working with a CSP customer in Asia to customize the subscriber experience thoroughly. They’re using analytics to gain a holistic view of subscribers based on 10 different indices. They currently have multiple systems that look at different aspects of the customer, but they want to consolidate those systems to address problems well before it’s too late. With all the source data consolidated, they’ll be able to run analytics to learn what apps the subscriber prefers to personalize the customer experience further. If the subscriber likes to communicate using WhatsApp, why not communicate with the subscriber that way? Analytics also will enable them to anticipate when the subscriber is likely to want to upgrade a device and what kinds of services each subscriber is interested in to run campaigns tailored specifically to each subscriber’s needs.
5G automation and standards
With the current explosion in data and the real-time nature of so many emerging applications, it’s imperative to reduce the human factor in network operations—particularly in highly complex 5G environments—to stay on top of network issues that can degrade experiences and erode customer loyalty. One small problem can quickly snowball into many others, and if operators don’t react immediately to fix the root cause, a large number of subscribers could be impacted.
Because of 5G’s complexity, it relies on analytics and automation to function properly. The Third-Generation Partnership Project (3GPP) has specified machine intelligence for real-time monitoring and management as part of the 5G standard in the form of a network data analytics function (NWDAF).
NWDAF helps operators find and fix issues in time to maintain high-quality services by incorporating standard interfaces for collecting data from a number of 5G Core Network Functions (NFs). It then applies those analytics to automating specific operations.
To leverage NWDAF, operators simply procure NWDAF software from an equipment manufacturer, a systems integrator, or a third-party software supplier. When installed on a device, the software automatically registers with a centralized repository and discovers all the network functions it needs to communicate with. From there, operators can collect data from any of those network functions, integrated with other NWDAF sources across the 5G Core, 5G New Radio RAN, data/transport network, and edge network without any data reformatting required.
One example of how NWDAF translates into better experiences and, in turn, customer loyalty is in private 5G network use cases. Private 5G networks require a capability called network slicing, which creates logical segmentation between customers or applications over a common physical network infrastructure. In a private 5G environment with tens or hundreds of network slices, it could be difficult to determine which network slice can provide the best service to a given device, based on its current traffic load. NWDAF automatically determines the load for each network slice and to which slice it should assign a newly registered device for optimal performance.
Leveraging tech for differentiation
Without an automated system to deliver continuous insights into customer experiences and behaviour, mobile operators will eventually find themselves in competitive trouble. Getting to know individual subscribers’ preferences and looking ahead and serving their changing needs, rather than reacting to issues and user dissatisfaction after the fact will ultimately differentiate the providers that thrive from those that fall into obscurity.