How to balance CX and Contact Center Efficiency

No need to sacrifice customer experience to gain on contact center efficiency. Leveling them up is possible through contact center transformation and the right technologies. Diving into CX, chatbots and agent experience.


Anyone who recently called their credit card company can most likely relate to the following.

The voice response system leads callers through a series of steps before handing the call over to a real person; such as the reason for calling, a reminder to check their website for the requested info and lastly, an identity verification. If one’s lucky, there are not that many different queues; diminishing the risk of ending up in the wrong queue and waiting to be transferred to an agent that can resolve the issue at hand.

Usually, frequent credit card users, will jump to the front of the queue and get to speak to a live agent quicker than a regular one. Nonetheless, the first thing the agent asks is to do an identity verification again, mostly through the same ones that were done through the IVR.

This is where poor customer experience starts; why the need to provide this much information when clearly it is not transmitted to the agent? Is it to withhold the occasional customer that calls the premium line? Is shaving off 20 seconds from the agent call time and gaining on efficiency worth sacrificing a good customer experience?

One of the problems is that only a few CEO’s and top-level managers realize that the contact center is many times the only customer interaction point.

Let’s talk about chat-bots

Lucy: Hello I am Lucy, I am your chatbot, how can I help you today.

Customer: Hi Lucy I have received a mail from your company that does not apply to me, but I cannot respond to the email because it has been automatically generated.

Lucy: Please tell me which of the following examples is most applicable to you 1, 2 or 3

Customer: None of them

Lucy: Sorry I cannot help you further, Our live chat will be available as of 10 am.

These services are designed to discourage people to make contact. Even trying to find the right contact number on an average website seems to be designed to be impossible, having to navigate at least 3 pages before landing to the contact number, really harming customer experience.

Chat-bots have been around for a few years now; they’ve rarely met consumer expectations or provided a positive customer experience since their rise. However, conversational AI has significantly advanced and transformed how companies can use chat-bots. They offer more and more, dynamic experiences, and this is helping to change how consumers think of chat-bots fundamentally.

Customer and agent experience

It is time for a paradigm shift in thinking, and the latest technologies will enable that. This new way of thinking should be centered around providing the right balance between improving customer experience and creating efficiency through facilitating the agents’ tasks.

What if we can do both? What if we can have happy agents and happy customers?
The first obstacle to be overcome; is the idea of the contact center being a cost center, it should be seen as an integral part of a company’s service and sales strategy instead. Analytics can deliver a sharp view of which processes work well, whether agents understand the processes and content, and how they deliver this. The analytical capabilities of the latest technologies can serve as a self-learning center for agents based on objective measurements of all of their conversations and comparing them against peers and company standards.

Real-time agent efficiency

The latest developments in AI enable agent coaching in Real-Time. Think about Augmented Reality; putting on VR glasses suddenly shows all kinds of information about your surroundings. Real-Time analytics provides this kind of service in an ‘ always-on” mentorship and provides agents with continued advice, thus easing their job and enhancing efficiency.

This is a win for everybody. The customer wins by receiving better service, and the agent wins by performing better, which generates job satisfaction and lower agent turnover rates. Overall the company wins because it will reduce handling time, increase compliance, increase the NPS and provide better customer retention and upsell opportunities. After all, wouldn’t you rather steer the conversation on forehand than try to recover after the fact?

The next step in providing AI support is to connect it directly to predictive engines. Starting with offline and then moving on to real-time to estimate the next best step for customers at any given point in time, taking the previous customer experience and journey into consideration.

Over time as the machines learn, they can provide dedicated services in a faster way. It will be a long way before machines understand the complexities and nuances of all human interactions—the ironic double negations and what more. But these engines will be able take over routine work in a much more sophisticated manner in the future.

Think about the collection of bills, for example.
Have you paid your bill?
No -> will you pay your bill within 7 days?
Yes -> Ok, that will be noted. Thank you for your cooperation.
No: Please provide a reason.
Thank you, if needed our organisation will contact you.


The reason recorded and analysed. A human agent can follow up on that conversation prepared, fully trained on the complications of various situations, with the subsequent best action recommendations provided by AI, based on thousands of cases.

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