Customer experience: orchestrated or a fluke?

Managing customer experience across the entire customer journey and all touch-points is complicated: getting visibility into the network and service experience aspect using real-time analytics is a key requirement to proactively managing churn and dissatisfaction.

At CX Exchange Telecoms in London, the Head of Transformation at mobile operator 3 Ireland showed a video of an orchestra playing the Game of Thrones theme. (Yes, the vast majority of CX attendees knew the tune!)

He was making the point that customer experience involves managing or orchestrating the entire experience journey of customers at each touch-point with the brand, employees, technology, and product (in this case, the network). Getting all groups to play in tune requires continuous orchestration, practice, fine-tuning and the really hard part: instilling a performance-based, customer-centric culture.

This reinforces the top pain point shared by other customer experience executives: understanding the end-to-end customer journey, from acquisition and onboarding to upgrade cycles, billing and ongoing support.

Deliver the customer experience that’s actually wanted

As part of overall digital transformation strategies, communications service providers (CSPs) are trying to simplify products, operations and processes and implement a ‘digital first’ approach to customer interactions.

Yet, digital-savvy consumers are generally critical of telcos. According to Ericsson’s Consumer and Industry Lab report 2018, almost half (46%) of consumers think CSPs hide behind bad tech and are exhausted by the number of interactions it takes with service providers to get things done. On average it takes smartphone users 2.2 attempts and 4.1 days to complete a transaction. They want CSPs to be more proactive and real-time in their digital transactions. But it’s not that simple.

The customer journey is complex even for something like buying a new SIM card and phone contract. This involves customers jumping between multiple channels: web research, ordering online, going to a physical store to collect the new phone, calling support if the first bill is not correct, posting on social media if the experience is poor, and so on.

There is valid data at each of these customer touch-points that needs to be understood, analyzed, and streamed in real time so action can be taken to solve issues and proactively manage the customer experience. These data sets include customer profiles as well as product, offer, usage, and rebate history, plus data from call centers, web logs, network experience and pricing and promotions.

Customer Experience Directors, charged with improving Net Promoter Scores (NPS), and preventing customer churn, are spending a lot on omni-channel customer relationship management (CRM) software and intelligent chatbots, to communicate and guide customers better through that journey. But shouldn’t they also be proactively trying to understand, and resolve why customers have problems in the first place?  

Lackluster network and service quality really hurts the customer experience

Customer experience teams are striving to understand the end-to-end experience, but it does not appear that the networks are getting their attention. Maybe it’s a budget issue or that there’s too much technical jargon, and it’s too complicated to relate the KPIs and metrics to actual customer experience. Churn definitely gets attention, but that is mostly linked to tracking contract renewal dates and alerting when customers have called call center several times in a row. Yet poor network quality and problems using applications is a key driver of churn for telecom customers.

Service providers struggle to understand quality of experience (QoE) and how customers are actually experiencing services; often, the network is “green” yet customers are calling in with complaints.

Customer experience directors tend to rely on the CTO, network operations or service operations and analytics teams to understand how the infrastructure is impacting service performance and how customers are actually experiencing services. To prevent and predict customer churn, they need this data in real time to fulfill digital orders and make on-demand service changes.

Here’s an example of putting that into practice: UK service provider TalkTalk is using operational data and analytics to improve customer experience and reduce costs. This involved analyzing network data, customer data, IVR data and using it to reduce the number of faults reported and the time to resolve faults by as much as 25%. The most dramatic improvement is a 40% reduction in engineer visits, directly improving the bottom line.

Breaking down customer experience silos with big data analytics

Despite ongoing digital transformation initiatives, it seems as if few CSPs are joined up internally to orchestrate customer experience from engineering to operations to customer experience to data analytics teams.

The majority of service providers still rely on fragmented and static monitoring tools and processes for network and application monitoring. Yet, the current tools and systems fail to understand the customer experience, because they work in silos, frequently just looking at one part of the network, and completely miss visibility into the service and application layer. Dropped calls, bad signals, delay, buffering, choppy audio; all of these things have become commonplace.

Performance issues arise as network traffic increases or because current systems are unable to monitor new services, and provide a comprehensive view of the entire network and all services and importantly how they are performing for customers.

Customer experience issues have a direct business impact

Unified customer experience management involves many interconnected focus areas, each with a set of questions that must be answered to understand what’s happening, and the resulting business implications.

The ability to understand and solve network performance issues that are impacting customer experience requires having a big data analytics platform that can process relevant ‘clean’ data, analyze it, and deliver operational intelligence to improve the business.

Efficiently finding and resolving faults in the network is a crucial aspect of preventing customer churn. Machine learning and artificial intelligence (AI) algorithms enable service providers to become more proactive and predictive with identifying issues and anomalies before they impact customers.

Driving improvement in operations using performance analytics

Having an organizational view of network and service performance data in real time means that anyone, in any area of the business, at any time, can access the same data and the same business rules, subject to data governance and security controls. There is untapped value in the performance data generated by your network infrastructure, services and applications. Hidden in this data is the fuel you need to run your business, optimize your operations, improve customer experience, and generate revenue.

This affects the entire way an organization works. Analytics and data science teams can work with customer service to develop predictive models based on a wider set of data, leading to increased accuracy and efficiency. Teams can use self-service analytics to help understand customer behavior, recurring service issues, and customer response times. It’s game-changing! The magic here is that everyone gets to access the same data sets.

The companies that will thrive near-term and in the coming 5G era are those that orchestrate customer experience across their business and embrace analytics and AI’s ability to scale and analyze data. Bain Consulting reports that, when companies dramatically improve customer experience, they increase their revenue up to 5% above market rates. The effort will pay off!