This blog was written by Zhecho Dobrev, Partner at Human2outcome.
Imagine this scenario: A customer calls wanting to return a product. The customer explains to Sue, the agent she’s speaking with, that she needs to return a product her husband had ordered. But sadly, he passed away a couple of days before receiving the package. As you can only imagine, the woman is struggling to speak and her emotions are at the surface. But Sue doesn’t offer her condolences; instead she quickly asks, “Do you have a receipt?” and moves right into processing the return. Sue was just focused on dealing with the call. Showing empathy wasn’t at the top of her mind, as her training didn’t teach her how to engage with customers using empathy. The story might seem a bit extreme, but it’s more common than you’d think.
Recently, a bank that I had a long-lasting working relationship with was about to go through a merger with another bank. I was asked to visit both of their contact centers to assess their performance. Among other things, one of my most striking findings was the lack of empathy shown by agents.
In fact, a business owner had called the bank to complain about the messy cables the point-of-sale equipment installation crew had left behind. The agent listened but said they couldn’t do anything as “…these are the cables we have.” The customer was taken aback and asked again, “So, really, you won’t do anything? It’s because of small things like this that I’d like to cancel all of my accounts.” The call wasn’t even logged as a complaint — no empathy was shown for the situation.
I used that call later during training sessions. I asked the agents “What do you think the customer actually wanted?” Only a handful acknowledged that what the customer really wanted was to be listened to, understood and treated as a valuable customer.
I asked the agents some follow-up questions: “This caller was the store owner. How many stores does she own? Does she have credits? How much does it cost to send a crew back versus losing the customer?” The agent’s actions could have cost the bank a high-value customer. The key to handling the customer better was empathy — which is about really understanding how the customer feels, what they really want and how to handle the emotional side of the interaction.
The Value of Empathy in CX and AI’s Role
To put the above examples into perspective, empathy was rated as the No. 1 most valuable contact center agent attribute by contact center managers. Another report found that customers who didn’t have their inquiry resolved — but had an interaction in which the agent understood and acknowledged their emotions — were much more likely to be satisfied (20%) than those who had their query resolved but had an experience where they felt their emotions were not understood or acknowledged at all (8%).
While it seems that the agents simply need training to show more empathy — and raise your customer satisfaction ratings — it’s more complicated than that. Changing a behavior is not that easy and rarely occurs simply when just telling people to do so.
While writing my book, I came across some really interesting research in which a machine learning algorithm was used to analyze millions of call interactions and find the agent behaviors that drive customer sentiment and satisfaction scores. Those were behaviors such as “taking ownership,” “active listening” and — you guessed it — “empathy.” I’ve also found those to be drivers of customer ratings. So, I trained the bank’s agents on those agent behaviors, proven by AI, to drive positive customer sentiment scores.
Unfortunately, the contact center management team, which had all changed since my first visit, couldn’t attend the training — and no one was enforcing the new behaviors. On top of that, due to higher volume, the bank hired hundreds of new agents who weren’t trained on those proven behaviors.
Both banks had already invested in (and continued to invest in) the development of AI bots. The bots can handle some of the customer inquiries and relieve the already tired and stressed agents. But that still doesn’t solve the empathy problem.
Here are some ways that AI can be used for a real transformation of how the business understands and serves its customers with empathy.
Sentiment Scoring
What could help is to use AI models that provide a sentiment score rating on every single interaction. Those are so advanced that they give more weight to phrases occurring toward the end of an interaction because research has shown that they have a stronger prediction of outcomes than those spoken earlier in the call.
What’s more, agents could be automatically scored on the different behaviors proven to drive customer sentiment. One agent might be better at showing empathy, another at effective questioning and so on. This could help the quality assurance team — instead of randomly picking and listening to calls, they can now cherry-pick which calls to listen to and use in their coaching sessions with agents. This can also be automated so that agents are pointed to some coaching and feedback learning modules that are automatically scheduled in their manuals.
Auto-Summarization for Agents and Supervisors = Data Democratization
We know that the contact center could be a great source for insights, but we also know that executives hardly spend any time in it. AI-generated call scripts and summary notes, however, not only save agents precious call handling time but essentially represent labelled data. When combined with call sentiment analysis, executives from all functions can skip right into the parts of the call that are of interest to them and listen to what customers say about a product (the good and bad parts) from the comfort of their offices.
Customer Journeys
Another important AI use case is tracking the end-to-end customer journey behavior. Wouldn’t it be helpful to eliminate unwanted and unnecessary contacts? Wouldn’t it be good to see the journey of those prospects who abandon their carts, interactions or leave and never call?
With an AI-powered customer experience platform, you can track the end-to-end customer journey, allowing for continuous improvement teams to find behavior bottlenecks and use behavior nudges to shape the desired customer behavior.
Don’t Just Do What Everyone Else Is Doing — Identify Your AI Use Case
Some years ago, when all the buzz was about social media, we worked with a water utility company that was planning to invest further in social media channels for customer service. We did research and found that those channels weren’t driving value for the company — 94% of the contacts came from the phone and many of those calls were about blocked sewers. When there was a complex or urgent issue, customers preferred to contact the company via the phone channel.
After evaluation, we determined that investing in a social media channel didn’t make sense for that company. The takeaway: Just because everyone is investing in something, doesn’t mean it’s right for you.
A Canada-based energy company we worked with had switched how they received orders from their commercial customers who needed to refill their heating oil tanks. Customers had to call a 1-800 central number, instead of their local office. This felt impersonal and took away the feeling of having a relationship with the company. This led to hundreds of complaints and many customers leaving the business. The company soon reverted back — allowing customers to engage with their local offices.
Was the company wrong to pursue new ways to drive more efficiency through technology? Not necessarily. However, they should have thought about how to use technology to preserve the relationship, which is a major driver of value for organizations. Technology, such as Caller ID and having a 360-degree view of the customer, would certainly have helped. Тhey could have also used AI-based predictive routing to connect with the agent that is best positioned to build rapport with the customer.
AI is more than hype — it can help make meaningful improvements to the customer experience. However, organizations need to think it through and follow this advice:
- Don’t be solely focused on cost-cutting opportunities. Ask the question: “How can we transform the customer journey/experience with the use of AI?” Then look at where AI can help to improve the customer experience, reduce churn and generate more revenue.
- Don’t forget the human element. Not only are calls that reach agents more complex and require more empathy, but most contacts don’t originate from the contact center. They are created by what the rest of the organization does (e.g., supply chain, finance, marketing, product development and digital teams). Consequently, for a true AI transformation you need to change their minds and micro-behaviors as well.
AI transformation can’t happen without humans. AI is the facilitator and enabler for transforming the customer experience. To make CX transformation a reality, you need to engage and change the minds and micro-behaviors of the organization. For more information on how to do this, visit Human2outcome or contact us.
