Being in the customer service industry, I’m often amazed how much money is spent on marketing to attract new customers vs the service function of a business which is often viewed as a “cost center” rather than a marketing ally.
A few weeks ago I had an issue with a purchase of a jacket. I contacted a customer service representative from the brand online, hoping for some guidance. Their response was quick, they were understanding and mentioned they could help with an exchange if I had purchased directly from them. But since it was a store purchase, no dice. Instead, they advised going through the store to organize an exchange. The snag? It had been two weeks since the purchase, and the receipt was history. All I had was the credit card statement showing the time and date of the purchase. The store’s retail POS couldn’t look up customer purchases I was assured, so I was back to square one.
A service interaction for a return should not be this hard (and possibly even automated!). I calculated that I likely wasted more dollar value in salaries of each of the brand representatives that I dealt with than the actual value of the jacket.
Let’s break down why the above situation can still occur in today’s service industry. The answer likely is siloed data. The data about my purchase was strewn across various business units, systems and customer touch points. As a result, each service representative I interacted with didn’t have a full view of my customer profile, the transaction or what they needed to solve the enquiry on the first touch.
Now that I know how bad the service experience is, I can’t bring myself to buy something from them again. And while I am only one customer, you have to imagine this type of scenario plays out across their business daily.
I was lamenting this poor service experience to my father, who had recently been through his own frustrating experience trying to get a health insurance membership card reissued. Upon calling a prominent health insurer, their IVR announced to him that they were experiencing “unusually long wait times”. Ironically, that same IVR announcement plays every time you call them, which begs the question of whether they understand what the word ‘unusual’ really means!
After waiting on the line for almost an hour (burning telephony costs for the insurer) an IVR message announced that all agents were busy, but please try their new live chat service, which should be much quicker.
He went to the live chat service and waited in a queue for 10 minutes only to again be told that all the agents were busy so to try messaging them on WhatsApp. He signed up to WhatsApp (the upshot of which is I can now message my dad on WhatsApp) and low and behold, 48 hours later he got a response.
So why did this brand put him through what could best be described as an “omnichannel spaghetti”. Although well-intentioned, the above is a great example of a business shipping their organizational structure into their IVR. This contact center clearly doesn’t have blended agents and is queuing voice and customers sequentially. Their voice, chat and asynchronous messaging appear to be non-integrated agent pools. This is possibly caused by multiple platforms and teams handling different customer channels, causing duplication of work.
By failing to offer a call back or a live chat upfront, they not only frustrated a customer but also burned telephony costs. The fact that the only channel that received a response was an asynchronous messaging channel is great, but the response time of 48 hours is way too long vs customer expectations.
So what could these experiences have looked like in a parallel universe? For starters, in each of the above scenarios, the brands had an opportunity to delight the customer with how easy they are to deal with. This missed opportunity for word-of-mouth marketing is more valuable than any of the slick campaigns both companies run.
Both of the above poor service examples suffer from a lack of customer data, which plagues many brands. I often hear of organizations that run multiple internal CRMs, data stores and e-commerce systems. It would be ideal if all of these platforms could be collapsed into one. However, we need to be realistic that this can take time and often is outside of the sphere of influence for the contact center leadership.
An alternative approach is one where the contact center creates an abstraction layer for agents that unifies the customer data in these various internal systems into a single pane of glass. This allows systems to deliver the right data from the right data source to the agent without costly CRM migrations. This sounds like fantasy, but with modern cloud contact center platforms coupled with new GenerativeAI capabilities, this data unification becomes much more simple and effective.
We also need to think through our digital channel strategy to make the most efficient (and delightful channels) the most prominent for our customers. There are significant productivity benefits for a business to have their agents running multiple messaging conversations rather than being tethered to a single customer phone call. And the best news? Customers love it. Report after report reveals that the better availability of digital channels the higher the CSAT.
What’s the lesson in all of this? If we are going to set a dynamic IVR announcement to customers that our phone lines are “unusually” busy and encourage them to message us, then we need to staff up agents who can manage messaging queues.
Or even better, choose technology platforms that allow you to blend agents across all channels, routing the most important interactions to any skilled and available agent, thereby optimizing staffing.
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Local Measure, Engage is a pre-built cloud contact center platform powered by AWS and available in AWS Marketplace.
