Verizon’s Technology teams are using machine learning to enhance the customer experience.
Building an innovative customer experience while garnering trust is critical to any successful business. In today’s hyper-connected world, customers expect excellence, personalized interactions, and frictionless transactions.
Learn how Verizon engineers are proactively solving network issues to enhance the customer experience.
Bringing trust, excellence, and faster solutions to customers.
According to Gartner, 83% of consumers say they will not do business with brands they don’t trust. For businesses struggling to keep up, AI-enabled experience scoring has emerged as a powerful tool that’s driving the customer experience revolution and reshaping the business landscape.
AI experience scoring is a predictive modeling technique that can identify patterns and predict potential issues before they arise. One of Verizon’s AI experience scoring models is called Network Quality of Experience Scoring (nQES). This new approach helps engineers correlate the experiences customers have on Verizon’s network to instances of customers calling in with problems or even leaving Verizon.
Annie Wong, Director of AI Science at Verizon, shares, shares that our engineers can now identify a problem within the network and trace it back to degrees of network experience degradation on a customer’s line.
“This is super cool because we typically look at network events at a network element level or customer level separately,” Annie said. “This is the first ever tie-in of customer experience to network events.”
With nQES, Verizon’s engineering team can better understand each line's experience when using the network. This enables machine learning-led decisioning for proactive network optimization. Looking at this data holistically allows the business to make decisions and improve service quality, backed by real data.
Benefits expand from customers to businesses.
The benefits of this predictive approach don’t stop at improving the customer experience. The insights gleaned from data analysis can be used to optimize business processes, reduce costs, and drive overall growth.
While still in its early stages, machine learning-powered network monitoring shows immense potential ー leading to even greater levels of personalization and predictive power. This presents a future where the customer experience is not just seamless but almost precognitive, anticipating needs and exceeding expectations at every turn.
“It is exciting to see how predictive AI is helping Verizon take a proactive, customer-centric approach to network management. Our teams are doing work critical to Verizon’s future.”
Bottom line: Our teams are creating a top-tier customer-centric experience using AI.
Verizon is all-in on the advances presented by nQES, the tasks it helps streamline, and how it puts the customer first to create a top-tier experience.
Here are some key takeaways on AI and the customer experience:
- Personalized customer interactions. Verizon is tailoring communications, offers, and recommendations to match individual needs and preferences.
- Optimized customer service. Identifying customers requiring immediate assistance and prioritizing their requests leads to faster resolution and improved satisfaction.
- Proactively engaging with customers allows teams to anticipate future needs and offer solutions before customers even realize they need them. This ultimately creates a smoother, more satisfying experience where the business can avoid churn.
Want to learn more about the team behind nQES? Explore Verizon’s technology teams.
