Stefani Barbero

Empathy in customer service doesn’t always look the way we expect. Sometimes it wears a disguise.

A few years ago, I bought my daughter a new mobile phone for Christmas. She planned to make a 3-hour drive, mostly through rural areas, to visit her cousins the next morning. We needed to get the phone working before she pulled out of the driveway. 

But nothing we tried did the trick. So, late in the afternoon on Christmas day, we needed customer support.

Our service provider’s website offered two options, phone or chat. I hate chat for support, but the wait time for a phone call was more than I could commit to while getting ready for a family dinner.  So, I fired up the chat and asked for help. At first, I wasn’t sure whether it was a bot or a human. I didn’t care either way as long as we got the phone working. Over nearly two hours, I alternated between the chat and my family. And in the end, the problem was fixed. 

What does empathy actually look like in customer experience?

I don’t recall the agent (human after all) saying anything particularly compassionate. And yet, this was one of the most empathetic customer service experiences I’ve ever had. Here’s why:

1. The interaction resolved my problem on my schedule without requiring a call or visit to the store.
2. I had a clear choice between phone and chat and knew the current wait times.
3. I got the problem resolved without missing Christmas dinner with my family.

The bottom line is that my service provider gave me options for how to engage and a convenient way to get what I needed.

This is how empathy sometimes wears a disguise. It masquerades as efficiency, convenience, and ease. 

In an industry hyper-focused on the emotional side of empathy, we too often overlook this crucial practical side. But we shouldn’t. It matters to customers, a lot. 

• 93% of customers expect their issue to be resolved on the first call
• 62% of customers would prefer to “hand out parking tickets” than wait in an automated phone tree for service or have to repeat themselves multiple times to different team members
• 80% of American consumers say efficiency is the most important factor in the customer experience, and more than half say it’s worth paying more for

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The often-overlooked practical side of empathy in CX

In recent years, the CX industry has focused intently on empathy. Businesses spend time and resources to upskill agents on active listening, emotional intelligence, and expressing care and compassion. They even provide lists of empathetic phrases their agents can use. And a growing number of contact centers use AI to detect customer sentiment throughout each interaction. All of that is great. It reminds the agents that customers are human, too, and they need to hear that someone cares about their problem.

Validating a customer’s feelings is an important component of putting empathy into practice. But it’s only one component.

Caring alone doesn’t resolve a customer’s issue, and it doesn’t automatically make the process of reaching a resolution easy or convenient. 

Long wait times, multiple interactions, and chatbot failures are not empathetic. Many CX leaders view those points of friction through the lens of contact center efficiency with metrics like transfer rates and digital containment. But friction also increases customer effort, which is an important component of empathy in CX. And too many contact centers deliver experiences that require a lot of customer effort – ineffective self-service, complicated IVR menus, disconnected channels, and more. An agent who says they understand your frustration can’t erase all that effort and wasted time.

Empathy in CX strategy: Are we making it too complicated?

The concept of empathy is somewhat vague and squishy, so it’s not surprising that CX leaders sometimes convert it into something else when crafting CX strategy. The problem is, they often convert empathy into the equally vague concept of customer-centricity. What does that mean? Keeping the customer front and center at all times, sure – but how? It isn’t always clear how centering the customer translates into actions and processes for the contact center to follow. 

The vague nature of both empathy and customer-centricity tends to give rise to complex frameworks that attempt to make the strategy more concrete. For example, a framework might categorize elements in the CX ecosystem into systems of listening, understanding, action, and learning. Those frameworks can help shape perspectives within your business, but they still require additional translation to make them actionable for your frontline CX team. 

Here’s a simpler approach. Embedding empathy into your CX strategy means consistently aiming to do these four things:

1. Resolve the customer’s issue in the first interaction.
2. Take up as little of the customer’s time as possible.
3. Make the entire process easy and convenient.
4. Treat your customers and employees like the human beings they are.

Getting to the point of empathy with generative AI

In contact centers, early AI implementations increased efficiency, but employees felt the impact more than customers. In some cases, AI deployments actually increased frustration by raising customers’ hopes with big promises of faster, more convenient service that didn’t ever materialize. Consider chatbots. Even with improved language processing, bots can’t take action to resolve a customer’s issue. So, they require time and effort from the customer but often, can’t truly help. When it comes to the practical side of empathy, they fail to deliver. 

But that was then, and this is now. The technology has matured, and current implementations of generative AI are improving contact centers’ performance on both the emotional and practical sides of empathy. AI solutions increasingly take over repetitive and time-consuming tasks, freeing agents to focus more effectively on the customers they’re serving. This shift makes space to engage with more empathy across the board. 

Customer-facing AI agents will generate a larger, even seismic, shift in how empathy is embedded into customer experiences. Generative AI agents can listen, understand, problem-solve, and take action to resolve customers’ issues. That ticks all the empathy boxes for me. This massive leap forward lays the groundwork for CX leaders to shift the emphasis of their AI investments toward solutions that do more than talk in a natural way.  

Practical empathy that’s just a chat or call away

That Christmas a few years ago when I needed customer service, I didn’t care whether I chatted with a human or AI. I just wanted my problem resolved before my daughter left town, preferably without having to call or visit the store the next day. I got lucky that time. My service provider had agents available. But we all know that’s not always the case. With a generative AI agent ready to respond 24/7/365, the customer’s luck never runs out. Effective, efficient, and convenient service will always be just a call or chat away. For me, that’s the part of empathy in CX that too many businesses are missing today. But I suspect that’s about to change. 

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Ever heard the phrase, "Customer service is broken?" 

It's melodramatic, right? —something a Southern lawyer might declaim with a raised finger. Regardless, there’s some truth to it, and the reason is a deadly combination of interaction volume and staffing issues. Too many inbound interactions, too few people to handle them. The demands of scale do, in fact, break customer service. 

This challenge of scaling up is a natural phenomenon. You find it everywhere, from customer service to pizza parlors.

Too much appetite, too little dough

If you want to scale a pizza, you have to stretch the dough, but you can't stretch it infinitely. There’s a limit. Stretch it too far, and it breaks. 

Customer service isn't exactly physical, but physical beings deliver it— the kind who have bad days, sickness, and fatigue. When you stretch physical things too far (like balloons, hamstrings, or contact center agents), they break. In contact centers, broken agents lead to broken customer service.

Contact centers are currently stretched pretty thin. Sixty-three percent of them face staffing shortages. Why are they struggling? Some cite rising churn rates year after year. Others note shrinking agent workforces in North America and Europe. While workers flee agent jobs for coding classes, pastry school, and duck farming, customer request volumes are up. In 2022, McKinsey reported that 61% of customer care leaders claimed a growth in total calls. 

To put it in pizza terms (because why not?), your agent dough ball is shrinking even as your customers' insatiable pizza appetite expands.

What’s a contact center to do? There are two predominant strategies right now: 

• reduce request volumes (shrink the appetite)
• stretch your contact center’s service capacity (expand the dough)

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Contact centers seem intent on squeezing more out of their digital self-service capabilities in an attempt to contain interactions and shrink agent queues. At the same time, they’re feverishly investing in technology to expand capacity with performance management, process automation and real-time agent support. 

But even with both of these strategies working at full force, contact centers are struggling to keep up. Interaction volume continues to increase, while agent turnover carries on unabated. Too much appetite. Not enough dough to go around. 

How do we make more dough?

Here’s the harsh reality – interaction volume isn’t going to slow down. Customers will always need support and service, and traditional self-service options can’t handle the scope and complexity of their needs. We’ll never reduce the appetite for customer service enough to solve the problem.

We need more dough. And that means we need to understand the recipe for customer service and find a way to scale it. The recipe is no secret. It’s what your best agents do every day:

1. Listen to the customer
2. Understand their needs
3. Propose helpful solutions
4. Take action to resolve the issue

The real question is, how do we scale the recipe up when staffing is already a serious challenge?

Scaling up the recipe for customer service

We need to scale up capacity in the contact center without scaling up the workforce. Until recently, that idea was little more than a pipe dream. But the emergence of generative AI agents has created new opportunities to solve the long-running problem of agent attrition and its impact on CX.

Generative AI agents are a perfect match for the task. Like your best human agents, they can and should listen, understand, propose solutions, and take action to resolve customers’ issues. When you combine these foundational capabilities into a generative AI agent to automate customer interactions, you expand your contact center’s capacity – without having to hire additional agents. 

Here’s how generative AI tools can and should help you scale up the recipe for customer service:

1. Generative AI should listen to the customer
   Great customer service starts with listening. Your best agents engage in active listening to ensure that they take in every word the customer is saying. Transcription solutions powered by generative AI should do the same. The most advanced solutions combine speed and exceptional accuracy to capture conversations in the moment, even in challenging acoustic environments. 

2. Generative AI should understand the customer’s needs
   Your best agents figure out what the customer wants by listening and interpreting what the customer says. An insights and summarization solution powered by generative AI can also determine customer intent, needs, and sentiment. The best ones don’t wait until after the conversation to generate the summary and related data. They do it in real time.

3. Generative AI should propose helpful solutions
   With effective listening and understanding capabilities in place, generative AI can provide real-time contextual guidance for agents. Throughout a customer interaction, agents perform a wide range of tasks – listening to the customer, interpreting their needs, accessing relevant information, problem-solving, and crafting responses that move the interaction toward resolution. It’s a lot to juggle. Generative AI that proposes helpful solutions at the right time can ease both the cognitive load and manual typing burden on agents, allowing them to focus more effectively on the customer.

4. Generative AI should take action to resolve customers’ issues
   This is where generative AI combines all of its capabilities to improve customer service. It can integrate the ingredients of customer care—listening, understanding, and proposing—to safely and autonomously act on complex customer interactions. More than a conversational bot, it can resolve customers’ issues by proposing and executing the right actions, and autonomously determining which backend systems to use to retrieve information and securely perform issue-resolving tasks.

Service with a stretch: Expanding your ball of dough

Many contact centers are already using generative AI to listen, understand, and propose. But it’s generative AI’s ability to take action based on those other qualities that dramatically stretches contact center capacity (without breaking your agents). 

A growing number of brands have already rolled out fully capable generative AI agents that handle Tier 1 customer interactions autonomously from start to finish. That does more than augment your agents’ capabilities or increase efficiency in your workflows. It expands your frontline team without the endless drain of recruiting, onboarding, and training caused by high agent turnover. 

A single generative AI agent can handle multiple interactions at the same time. And when paired with a human agent who provides direct oversight, a generative AI agent can achieve one-to-many concurrency even with voice interactions. So when inbound volume spikes, your generative AI agent scales up to handle it. 

More dough. More capacity. All without stretching your employees to the breaking point. For contact center leaders, that really might be as good as pizza for life. 

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