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Unleash the Power of AI to Boost Your Customer Connections

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In a game of inches, communication service providers (CSPs) are looking for tools or practices to help them get ahead. With revenue in the communications services market projected to reach $337 billion in 2024, there’s inevitably a lot at stake. To explore how CSPs can gain a competitive advantage and get ahead of the competition in this growing market, let’s take a look at the potential impact of connecting with customers on their terms and leveraging generative AI (GenAI) to personalize those interactions.

For CSPs, the ultimate goal is to turn potential customer issues into meaningful steps that enhance their experience and drive loyalty. Previously, CSPs could predict the likelihood of someone calling in and would have a generic, purely reactive solution in place. Those predictions were based on large, nonspecific sample sizes and not very personalized to the individual calling in, treating valued customers like numbers or problems to be solved rather than people. With the evolution of customer analytics (thanks to AI), CSPs can get more personalized than ever before and tailor each conversation to the customer’s specific wants and needs.

Breaking Free from One-Size-Fits-All

CSPs aren’t just guides on a customer journey, they’re the cartographers who made the map and the meteorologists who let the guide know when a trail is safe to travel. CSPs can’t afford to specialize in one tiny part of the customer journey but should use all available tools to provide a great experience from start to finish. With GenAI, customer journey analytics and mapping now in play, CSPs can more seamlessly contextualize their unique customer data and predict their customers’ next steps before they even realize themselves. In doing so, they can deliver personalized experiences that make customers come back for more and differentiate them from the competition.

Now, GenAI is based on models that have been trained on giant public data sets, and while they provide interesting information, this information is available to everyone. To truly gain valuable insights, models need to be augmented to the industries in which they specifically support. Why is that relevant? Because CSPs have an opportunity to refine these models with their unique structured and unstructured data that is relevant to their industries. This next level of data intelligence will also allow them to engage on a much more personal level with their customers.

So What?

The big change in this approach is that CSPs can’t be solely satisfied with predicting the “what,” meaning what the problem is; they must proactively get ahead of the “so what,” find the root of the problem and explore how to solve it. As an example, it is not enough for them to know bill confusion is the main driver of call center traffic – the “what” but understand what led to the bill confusion in the first place – the “so what” – and how to prevent it. In getting there, it’s worth remembering that not all friction is bad if you prepare for it. However, preventing confusion will be more valuable to the customer than clarifying the bill for them.

With this proactivity in mind, it’s time to think about the “so what” and what’s next for CSPs to do after having reacted. What if CSPs asked their customer what parts of the bill they were confused about and then leaned into that confusion instead of skirting around the issue? If customers are confused about an unexpected fee, for example, then what’s next? CSPs should use this direct feedback to personalize the experience by breaking down the customer’s bill using step-by-step navigation that explains what has changed and why. This itemization of charges helps customers understand the “why” behind each charge with clear and contextual explanations that leave the customer informed and in the know about what’s coming. But CSPs shouldn't stop there – if they understand the confusion and then engage with the customer, maybe they can create a better service offering that is tailored to their needs. CSPs should strive for a dynamic catalog of offers to direct the customer experience, seeking out personalized customer input for the customer engagement all consumers want.

Beyond running the analysis to identify issues, GenAI will also allow CSPs to prioritize outbound communication and interactions—the “what”— without adding extra work for human representatives for each engagement—the “so what”. Similar to how they can now hand off basic analysis work to GenAI, when employees have more time to focus on the tasks that give their work meaning, they are happier and more satisfied. GenAI allows them to do just that: offload more mundane tasks so they can devote their time and attention to more fulfilling projects. This means not just an improved customer experience, but a better employee experience overall. This combination of efficient analysis and employees who are focused wholly on customers will also prevent the faux pas of overstepping boundaries when it comes to personalization, which can turn customers off rather than add to the overall customer experience.

Proactivity + Personalization = A Happy Customer

Happy customers and improved employee efficiency have always been (and should continue to be) priorities for CSPs, but there is an additional benefit: the capacity for increased revenue. By using GenAI to its full potential, CSPs can get to the heart of customers’ needs quicker, which will increase loyalty, drive new promotions and create market differentiation. As always, the bottom line for the bottom line is customer experience, and a happy customer has always resulted in a competitive advantage.

The game is changing for CSPs. GenAI, when used correctly, will become the tool that lets CSPs predict and tackle customer needs before they even realize they have them—it's like having a crystal ball for customer satisfaction. And it's not just about keeping customers happy; employees also get to break away from mundane tasks and focus on what really matters. By understanding the “so what” behind customer problems and being proactive with innovative solutions, CSPs aren't just in the business of happy customers – they're on the road to increased revenue and a leg up against competition.

Mr. Dunavant serves as Chief Strategy and Product Officer at CSG, responsible for developing, communicating, executing, and sustaining corporate strategic initiatives. Mr. Dunavant has been with CSG for over 20 years, previously as Senior Vice President and Global Head of Product Management (2017-2020) where he developed the strategic direction for CSG’s products and services. He possesses deep industry knowledge and experience developing enterprise SaaS software for multiple industry verticals and is an author and speaker on best practices for driving profits in the digital era. Mr. Dunavant holds a BBS in Finance and Management Information Systems from Gonzaga University and received an MBA in International Business from the University of Denver.