Customer Support vs Customer Experience: How AI Drives Better Service and Outcomes

There’s been a lot written about the shift from companies focused on customer service and support to companies focusing on customer experience.

Customer experience--or, more specifically, customer experience management--is about understanding a customer’s journey throughout the range of relevant touchpoints. Then, finding ways to make that experience as seamless and enjoyable as possible.

Although the customer experience has always existed, the idea of actively managing it at both a strategic and tactical level is still an emerging field. But not one without merit. According to McKinsey, firms that lead in customer experience report 5-10% higher revenues and 15-25% lower costs.

For most firms, there is a big gap between thinking about a series of individual touchpoints and thinking about the customer journey holistically.

What are your customers thinking or doing in the times between when they directly interact with your company? This may seem like a strange question to ask. But it’s critical to understanding the customer experience. Especially when it comes to providing great service or support, the trigger that initiates that touchpoint is likely negative--something has gone wrong and now I need to contact customer support to have it fixed.

As such, service and support teams can help to defuse negative situations, reduce customer service inquiries, and provide a better customer experience by proactively and strategically managing the entire customer journey.

Of course, this isn’t a simple flip of a switch.

It takes sometimes dramatic shifts in customer service operations. It takes retooling the support strategy. And it takes the right tools and technology.

One technology leading the way is artificial intelligence. AI makes it possible for firms to switch their emphasis from reactive customer support and service--i.e., taking requests and answering questions as they come in--to managing the customer experience in a proactive way.

But to understand the full range of implications, we need to first take a step back and discuss customer experience more broadly.

Customer Experience Strategy

Developing a strategy for how to manage the customer experience requires a concentrated effort on the part of many different stakeholders. The idea of customer experience itself spans everything from marketing and sales to service and support--along with each of the associated executives and team members.

This means, to delve into the customer experience requires a clear strategy.

Firms must enter this process with defined goals and armed with as much real-world data as possible.

Setting a customer experience management strategy requires companies to:

• Develop a deep understanding of the customer profile
• Define the customer journey, including individual touchpoints
• Understand the goals, questions, and emotional state of the customer at various points throughout the journey
• Gain insight into the needs and wants of customers throughout the customer lifecycle
• Build a framework for identifying and deploying tools, information, or resources to customers at the point where they’re needed
• Create a way to measure, track, and analyze the effects of changes to the customer experience

This is not a one-time process.

The customer experience is likely to change and evolve. And changes made to improve the experience must be carefully evaluated for effectiveness. This requires collaboration and iteration on the part of many different stakeholders.

For customer support teams, in particular, it’s important to focus on anticipating questions and issues that customers may experience. These situations that would otherwise have triggered a call or email to the support team can, in many cases, be addressed proactively with the right strategy.

In other cases, these situations may be defused or eliminated entirely as an outcome of improved customer experience.

The key here is that customer experience management is, at its core, a proactive process meant to resolve issues before they occur.

Focus on Proactive Support

The goal of customer experience management should be two-fold:

1. Minimize friction; Give the customer as seamless and intuitive experience as possible
2. Maximize value; Deploy time/resources in the areas that create the most value for customers and the company (versus spending those time/resources on putting out fires.)

With these two goals in mind, it’s clear that most customer service operations do not deliver an optimal customer experience.

Agents and support teams spend the bulk of their time on the front lines, responding to requests and answering emails. Rather than focusing on the highest-value items, they simply manage a queue and prioritize on a first-come-first-served basis.

From the customer perspective, this is a poor experience. In order to get the help or information they need, they first need to run headfirst into an issue. Then, reach out to the support team. And, finally, hope that the issue can be resolved with minimal effort and without waiting hours for a response.

No wonder this model hasn’t been a customer favorite.

This leads us to a clear and logical conclusion. This means understanding the customer, anticipating their needs, and deploying the right information and resources in real-time and on demand.

In order to provide a superior customer experience, firms must embrace a proactive support strategy.

For customer service teams, this means a lot of changes need to take place. The entire customer service operational playbook shifts as firms find new ways to dissect and understand customer behavior. More importantly, the customer service team becomes responsible for uncovering insights about the needs of the customer and then building out tactical and technical solutions for dealing with those issues.

How do teams achieve this level of service at scale?

Enter the role of artificial intelligence.

AI is a tool used by more and more customer service and support teams to facilitate day-to-day operations and also bolster their ability to develop creative and strategic initiatives--to manage the customer experience in a proactive way.

Companies are taking notice.

A report by Gartner from 2017 estimates that 55% of established companies have already started investing in AI technology or will by 2020. Much of that investment will either directly or indirectly impact the customer experience.

AI’s Role in Customer Experience Management

While AI has many application and implications for all types of business, one use case that is fairly universal is applying machine learning and natural language processing tech to the role of customer service.

Although we’re still not at the point of having AI capable of answering any and all support requests, there are already real and tangible applications for the technology.

For starters, AI-powered support chat and AI-assisted support agents are able to solve most--or all--customer requests in much less time than human agents alone.

Less time and fewer resources spent on reacting to customer issues and questions mean that the customer support team is able to focus their efforts on proactively managing the customer experience.

Firms that are able to invest more time and resources into the customer experience can expect a higher level of return--and more satisfied customers.

At this point, we’ve come full circle.

Not only does AI allow customer support teams to provide a higher level of service with greater speed and accuracy, but it also allows the team to invest in other areas that will impact the experience across the entire customer journey.

AI can’t yet develop your entire customer experience strategy.

But it can free up the time and resources. In turn, those resources can be allocated toward proactive strategies.