Determining When to Automate Customer Care and When Customers Need the Human Touch

As retailers begin to gear up for Peak 2023, they need to ensure that customer care has the capacity to scale, deliver self-service options, and improve — rather than detract — from a positive customer experience. At any time of year, customer care is often where customer loyalty is either saved or lost forever. During peak season when customers are pressed for time, a positive customer experience has even higher stakes. So how do you know when to automate self-service and when to leverage agents?

With peak, comes the need to scale. Traditionally, retailers scale customer care by staffing up their contact centers or outsourcing to BPOs. Today, retailers walk a fine line to determine when and where agents are needed to maintain customer loyalty and where automated self-service options can provide that experience. It’s not an easy line to determine.

AI has proven to be a very effective tool at delivering self-service options such as intelligent virtual agents (IVRs), and intelligent virtual response (IVRs) that let customers choose from options and solve issues that can be handled without an agent.

AI seems like the golden solution to scaling customer care, but before you strategically deploy it, there are some things to consider.

AI is full of potential and it has proven to be able to handle transaction-based tasks, like automated bill pay, payment, order status, and initiating returns processes. But many retailers make the mistake of assuming that customers are happier if they don’t have to talk to an agent.

Customers are happy when they are able to solve problems with the least amount of effort on their part, in a timely fashion. So, AI that makes customers wade through numerous options, that does not have enough options, or that does not (gasp!) allow customers to reach a human agent, only frustrate customers. They’d rather talk to a human agent because it would just be faster, they’d be able to easily explain their problem, and the human agent would understand them.

The point is: customer experience depends on speed, accuracy, convenience, and feeling understood with minimal effort on the customer’s part (i.e., not having to repeat their info several times, etc.). AI that cannot deliver that does not improve the customer experience.

Typically, AI applications are first deployed for transactional interactions. Simple tasks. More advanced AI is able to take on more complex tasks. Prior to ChatGPT, training AI for customer service required intensive work by data scientists and continual training and maintenance.  ChatGPT has reduced the need for training due to its pre-existing vast knowledge base to draw responses from; however, ChatGPT needs to be curated, monitored, trained, and governed for it to represent a brand’s values, product solutions, and desired outcomes for customer care.

Customers that have more than the most basic transactional requests look to human agents to have the empathy, understanding of context, and the ability to relate to them as they solve issues. They expect human agents to be able to do more for them than AI can do, and turn to humans when that is the case.

So, how do you decide what tasks to have AI handle and what tasks your human agents should handle? And then be able to scale both as needed?

Omnichannel has taught retailers to be present for customers on all channels; that the customer’s choice of preferred channel should guide their experience. This is true in omnichannel shopping; however, when customers need support it’s to solve a problem. People with problems want to be directed to the best, most efficient solution.

Retailers should not shy away from providing clear direction to customers for the best way to solve their issue. This should go beyond a simple IVR that asks them to select 1, 2, or 3 to be routed to the right place; it should direct them to the best channel to solve their problem.

This allows the retailer to align customer issues with the channel that can best support them; rather than leave it entirely up to the customer to choose voice, chat, email, sms — or as in some cases today, have only a virtual agent to deal with.

Much of the call deflection purposes of self-service options comes off to customers as a callous lack of concern for their problems. Retailers that have aggressively deployed AI as a primary customer service solution often leave customers feeling at best unhappy, and worst, uncared for. Poorly developed and deployed AI has this effect.

Directing customers by type of problem to the channel that can best support them helps to alleviate this disconnect. It also helps them feel cared for.

Rather than looking to AI to primarily offload work from agents, retailers can look to AI to handle issues that truly are only transactional and assign more complex relational transactions to agents. Many contact centers believe they are currently doing this, but real-life experience says otherwise.

How many people have dialed customer service only to wade through a tedious AI-led routing process or attempt to solve a problem, with no or little recourse to reach a human being for help? How many have had AI be limited in what it can do and unable to solve the problem?

In many ways, AI has unintentionally made customer service less friendly and a more antagonistic customer experience. Retailers can change this by fully leveraging the benefits of human agents, by directing customers to channels based on the type of issue they have, and by making sure that agents are always available and readily within reach — until AI has matured enough to truly deliver an exceptional customer experience.

AI definitely enables retailers to scale customer support as virtual agents can respond to every inquiry without delay, and scale to meet demand. However, this needs to be carefully balanced with human agents who are available to meet customer needs. For many retailers, scaling AI is easy, but scaling human agents by hiring up during peak times can be challenging. One solution is to outsource your customer care to a third-party provider, like Radial, that can provide the customized AI and human agent solutions, at scale, as needed.

Leveraging human agents and an AI workforce for their inherent benefits and strengths — rather than trying to make them interchangeable — enables retailers to create customer experiences that retain customer loyalty.

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