How AI Drives Innovation for a Better CX
This is the last in a series of blog posts examining key contact center trends for 2020, and the first three lead up to this broader theme of innovation driven by Artificial Intelligence (AI). We began by looking at the impact of digital transformation, then the importance of personalization, and most recently the power of agent engagement for improving the customer experience (CX).
Each of these trends is important in their own right, but they are all driven in some way by AI, which is now being infused across all business processes and modes of communication. These capabilities are now being applied to the contact center, and while we’re still in the early adopter stage, AI is coming, and there’s no need to wait for proof-of-concept.
Before addressing how AI drives contact center innovation, it’s important for decision-makers to understand that AI represents a broad set of data science disciplines that are iterative in nature. This means that AI applications for the contact center do not come fully-formed. Rather, they start from a base of handling simple, routine tasks, and as machine learning capabilities grow, more elements of CX can become AI-driven.
By coming to AI with a set of realistic expectations, IT decision-makers can start exploring the possibilities. The full potential of AI won’t be realized right away, but even with an entry-level approach, it should be clear how it will enable the kind of innovation contact centers need to meet today’s customer expectations and keep them loyal as new technologies continue to re-shape CX. To help get you on this path, here are three core applications of AI that are gaining traction in 2020.
- Chatbots to help map out the customer journey. AI provides unprecedented capability to understand the end-to-end touch points that define the customer relationship. Instead of solving a customer issue at face value, agents can address that in the broader context of everything in the customer’s history that led up to that point. Not only does this provide for deeper customer engagement, but with predictive analytics, agents can be more proactive and go beyond the transactional nature of providing customer service. Customer journey mapping involves a variety of AI-driven technologies, and chatbots have a key role to play, especially in making the process seamless so agents can take CX to a higher level.
- 24/7 Self-service. Chatbots can go a long way to elevating self-service beyond legacy IVR, and with that come enhanced levels of customer support. Automation is a leading use case for AI, and as chatbots mature, they will go beyond the menu-driven options that have long-defined self-service. They will become even more conversational, taking on more complex needs that customers would otherwise wait endlessly on hold for a live agent. Equally important, chatbots work 24/7, with nominal impact on your cost structure.
- Higher-performing agents. This should always be the goal for any contact center, and it should be clear how the above two examples support that. AI can improve agent performance in many other ways, and that’s what makes it so valued. Consider how AI can make routing more intelligent, ensuring that inquiries go to the right agents so they can do their best work. Or, how AI can monitor agents’ phone and messaging conversations and provide real-time expertise and coaching to new and learning agents. There are many other ways that AI can go beyond automating customer service, and by taking an agent-centric approach, AI can also have a major impact on both agent engagement and performance.
Just as your customers are on an engagement journey with your company, CX leaders can also view AI as a journey that your contact center can begin any time. Regardless of how conventional your contact center environment is, there’s a way forward with AI today, and we welcome the opportunity to get you started with Upstream Works enhanced omnichannel contact center solutions.