Customer service has never been the telecommunications industry’s strong suit. Between confusing contracts and bills, inconsistent customer support and spotty network quality, carriers regularly struggle to deliver the kinds of experiences that subscribers expect.
Exhibit A: Net promoter score (NPS) ratings for telcos, which track customer loyalty, were the lowest of any industry tracked by CustomerGauge last year.
The fact this problem continues to rear its ugly head every year points to one fundamental truth: Communication service providers (CSPs) need to accelerate digital automation efforts to enhance customer experience. If they do not, they will keep losing customers and missing business opportunities.
By digital automation, I mean a combination of technologies for turning customer data into meaningful and actionable insights that CSPs can use to automate back office workflows and tailor services specifically to the needs of their subscribers. These systems would identify and prioritize urgent requests requiring human attention while invisibly addressing common issues on their own. They would also make intelligent recommendations on the next-best action to take, thereby anticipating customer needs based on their brand interactions or “journeys.”
From a technology standpoint, these capabilities require supporting data quality, integration, and observability tools to manage customer data. They also need artificial intelligence (AI) or machine learning (ML) to eliminate time-consuming manual processes and accelerate decision-making and productivity across all sales, service and support cycles.
Taking automation to the next level with machine learning and artificial intelligence
To be fair, most CSPs are already using some degree of automated technology for customer service. Some of the most common examples include chatbots, virtual assistants, recommended product purchases based on buying and browsing history or tools to spot abnormal network behavior indicating a cyberattack is under way. All of these applications, which the industry has embraced for years, have proven valuable.
But today’s more sophisticated AI and ML algorithms could enable so much more for subscribers. Imagine, for instance, a carrier struggling to stay on top of customer complaints against the backdrop of COVID-19. Late last year, many carriers saw their workforces shrink as part of the Great Resignation, where millions of Americans willingly quit their jobs because of pandemic-related challenges. If carriers had fully digitally transformed and embraced automated technologies, they would have been well-positioned to automatically handle most requests coming into their call centers. Instead, many shifted inquiries to overseas staff, left customers on hold too long, and couldn’t keep up with support tickets. As a result, even brands that had made significant recent gains in customer satisfaction saw it drop precipitously.
Why using automation to improve operations is more critical than ever
Automated technologies could also be applied to help CSP leaders see and better understand operations to improve the efficiency of customer-facing systems. In many organizations today, especially larger ones, technologists in various departments have deployed a multitude of fragmented tools for understanding what and who might be accessing network services, such as an online shopping cart, customer support portal, or streamed movie. This is problematic because it prevents CSPs from gathering enough accurate data to provide proper, timely and customized services and support to subscribers. By combining data visibility and analytics tools with AI and ML, however, they’d gain a 360-degree view of each consumer or business customer and have the ability to spontaneously address their needs.
CSPs, of course, increasingly recognize that they need to evolve their customer services. In fact, telco investment in AI technologies is expected to grow from $1.36 billion in 2020 to $5.3 billion by 2028, according to Reports and Data. More than half of CSPs surveyed by Anodot, a data analytics company, say improving service experience is a key reason for that interest. In addition, 46 percent say better network performance troubleshooting, early warnings and visibility into service degradation will improve customer experience and loyalty. Conversely, studies also show experience and loyalty suffer when websites and shopping carts fail to load within seconds.
Putting AI experiences into practice
AT&T took such data to heart as part of its ongoing digital transformation. Its service and support teams could be working in dozens of different applications at any given time trying to collect relevant data from different parts of the company. In the fiercely competitive telco industry, these kinds of time-sucks simply do not cut it. So, AT&T invested in a customer relationship management (CRM) platform supported by AI that allowed it to centralize systems and enable frontline agents to gather critical customer data with just a few clicks.
Dutch telecom KPN also set out to digitally transform its internal operations to maximize experiences when customers purchase its products, reach out for support or manage their accounts. The company set a goal of handling 1,000 new orders per week without increasing headcount. So, it deployed a combination of CRM, cloud and AI technologies to automate manual processes and improve staff visibility into customer journeys. As a result, reps were able to better identify when to cross-sell Dutch telecom KPN offerings and hit 90 percent first-time resolution on issues. Since going down this path, the company has improved its NPS rating by 84 points.
Why CSPs must now anticipate customer needs to remain relevant
To remain relevant in the telecommunications industry, other CSPs must go down similar paths. It is critical to lay a digital foundation capable of not only recognizing — but anticipating — customer needs in order to deliver the kinds of personalized experiences they expect and deserve. Those that do so stand a greater chance of differentiating themselves and creating new business opportunities. CSPs failing to seize the momentum risk being leapfrogged by competitors and becoming irrelevant to their subscribers.
