A 50% containment rate looks great on a dashboard.
Fewer customers reached an agent, the contact center handled less volume, costs fell, and the contact center team has a result to take back to leadership. What’s not to love?
But what happens if half of those customers call back anyway?
This question was posited by Natalie Beckerman, Chief Business Officer at iQor and author of ‘When Did You Stop Caring?’, during a recent conversation with CX Today.
For Beckerman, if half of your customers are potentially calling back, that probably means that “their problems actually weren’t resolved.”
That is the issue with contact center efficiency metrics. They are easy to count, easy to compare, and often easy to celebrate. But they do not always show whether the customer got what they needed.
In some cases, the cost has not disappeared at all. It has simply been pushed into a second call, another channel, an agent’s workload, or a customer’s decision to go elsewhere.
The “Caring Recession” in Customer Service
Beckerman calls this trend a “caring recession.”
She believes the decline has been gradual, but accelerated during and after COVID, as businesses rushed to automate, reduce human contact, and speed up service operations.
“We really started to confuse reducing contact with improving experience,” Beckerman said.
The contact center industry has long tried to balance service quality with cost control; that is not new. What has changed is the speed at which AI, chatbots, self-service tools, and automated journeys can now be deployed.
Used well, those tools can take genuine effort out of the customer journey. They can answer a simple question, surface the right information, or route a customer to the correct person before frustration builds.
Used badly, however, and they can make it harder to get help while giving the business a stronger containment score.
“Efficiency without the humanity is a bad business strategy,” Beckerman said. “It’s very incomplete.”
When the Customer Is Doing the Work
The warning signs are often not difficult to spot.
Customers are asked to repeat their information after moving between channels. They navigate an IVR, then a chatbot, then a help center, then an agent who has no record of what came before.
In essence, they are forced to chase a resolution rather than being guided toward one.
For Beckerman, those journeys show that a business has made service easier for itself but harder for the customer:
“If you have customers that have to continuously repeat their information, even if there is not a human on, and you are navigating these endless IVRs or the automation put in before the IVR, then you have customers switching channels and chasing the resolution and fighting to speak to a human.”
That is where contact center leaders need to look beyond the customers who successfully completed self-service. Some will call back, others may complain, while some will simply leave.
Businesses should not assume a customer who did not reach an agent was successfully served. They may have found an answer elsewhere, delayed an important action, or decided the business was too difficult to deal with.
“The goal should never be to prevent customers from contacting us,” Beckerman said.
Automation Should Know When to Step Aside
Beckerman is not arguing against AI or automation. She describes the technology as “an extraordinary enabler.”
The problem is not that a customer interacts with a bot; the problem is when the bot becomes an obstacle.
Automation works when it simplifies a task, anticipates a customer need, or quickly recognizes that the request requires a person. A customer should be able to get where they need to go without becoming trapped in a maze of menus and repeated questions.
“You hear people saying, ‘I got right where I needed to go when I called,’” Beckerman said. “Or you can hear customers also talk about when I needed an agent, they sent me to an agent. That’s a great use of automation.”
