Take on any CX challenge with Pipeline+ Subscribe today.

Enabling Productive CX in Challenging Times

Enabling Productive CX in Challenging Times

Enabling Productive CX in Challenging Times

Can AI help square customer and contact center needs?

Customers expect excellent products and services from companies and deservedly so. After all, it is their money. Particularly in challenging times like these with inflation and other financial worries where every dollar (or other currency unit) - and when every buying (and referring) customer - counts.

That makes it imperative for companies to offer an excellent customer experience (CX). But they too often have to watch their dollars (or other currency units). Consequently, they must maximize the returns (ROI) through obtaining superior, expectations-exceeding performance and productivity from their customer service budgets.

Barry Cooper

Artificial intelligence (AI)-driven software has shown much promise in enabling contact centers to manage both CX and costs. But is it really delivering? And can it do more in the future?

To gain insights into how to enable a superior CX using AI in this environment, we recently virtually interviewed Barry Cooper, President, CX Division, NICE. Here is our conversation.

Q. What are the top CX trends, what are their drivers, have these changed since 2023, and why?

Here are three:

1. We are seeing an increase in the number of blended agents. They manage both voice and digital interactions as digital interactions become more prevalent.

For 2024, I predict a 75% increase in the use of blended agents. As companies invest in AI, this allows agents to become super-agents and easily handle voice and digital interactions. AI is a vital tool that can increase productivity, eliminate mundane tasks, and elevate both the agent and customer experience.

2. The gap is widening between good and bad AI. This is becoming more prevalent as more discussions happen around AI regulations, putting a spotlight on the importance of having purpose-built AI created with the proper guardrails.

When it comes to customer service, this means AI that is domain-specific and built from rich CX data, ensuring that responses that are generated are accurate, relevant, and appropriate. AI is the answer to managing the overwhelming complexity of customer service in the digital omnichannel age.

But that does not mean that all AI is created equal. Increasingly, businesses are struggling to optimize AI tools for their needs.

Intelligently communicating with customers, supporting contact center agents, and operating in the cloud at scale are all vital parts of successful CX. Only AI which has been purpose-built and trained on millions of customer interactions is suitable and trustworthy to manage an organization’s CX efficiently and effectively.

3. Cloud adoption is on its way to peaking in 2024. AI advancements are leading to mass adoption of the cloud, with companies realizing the necessity of bringing their operations to the cloud to be able to fully utilize AI and succeed in the digital era.

Here’s why the cloud is essential to AI-based applications. The cloud allows for much easier data sharing across an organization and applications. This is very important as AI is trained on this data. The easier this data is to access, the easier it is to train AI.

Organizations are no longer able to manage complicated tech stacks of patchwork solutions. In the age of AI, organizations can’t afford to operate like this any longer. They need their data to be easily accessible and shareable.

Consequently, organizations are moving to adopt a single, open cloud interaction-centric platform, underpinned by AI, allowing organizations to seamlessly connect third- party resources with native capabilities on the platform.

Q. The U.S. Bureau of Labor Statistics is forecasting slower labor market growth and a decline in the demand for customer service employees over the next 10 years. Will these macro trends affect contact center delivered CX, including agent performance and productivity?

AI is allowing CX organizations to do more with less, enabling these organizations to not only maintain service levels despite the impacts of economic uncertainty but become more efficient and improve overall operations.

Even with slower labor market growth, we see a constant increase in the volume of customer service interactions in the post-COVID Digital Economy of today. Less and less is done face to face which means more business is done virtually.

While Conversational AI will pick up many of those interactions, human agents will be needed as more complex business processes move from face-to-face to virtual.

And this represents the second area where AI will make an impact as Augmented Intelligence supporting the agents to do more complex work. It enables offloading repetitive tasks and giving agents access to what they need as they deal with ever more complex tasks.

Integrating the Front Office (Contact Center) With the Back Office

Consumers often interact with an organization’s front office for transactional interactions. With the reduction in face-to-face interactions, that front office can be the traditional contact center or an organization’s digital storefront: mobile app or website.

Generally, those transactional interactions involve business processes that extend into the back office for ordering, approvals, billing, or payments. So, we asked Barry Cooper to discuss what is happening: trends, opportunities, and challenges, with front-office-back-office integration. Is it becoming more or less important and if so, why? And is or will AI play a role there too?

“Digitalization and economic uncertainty are forcing CX organizations to rethink how they manage their operations leading many to combine back-office and front-office functions,” says Barry. “This speeds up processing, increases first contact resolution, and reduces errors.

“Combining the two functions in the digital age requires a different way of managing time. CX organizations need to be able to manage asynchronous work which makes up a majority of the back-office work and is increasingly more common in the contact center.

“Advanced workforce engagement management systems powered by AI now allow organizations to break down their staffing into ‘activity-based staffing’ taking into account asynchronous and synchronous work items.

“On top of this, AI is further breaking down barriers between the back office and contact center, eliminating siloes and improving efficiency across the organization.

“When the front and back office are managed on the same cloud platform underpinned by AI, this makes the relationship between the front and back office very smooth. Back-office employees have the information they need to complete service requests quickly. This reduces the chance of customers calling in requesting status updates.

“With a comprehensive view of operations through the platform, CX leaders can also make better-informed decisions about staffing needs to move staff around from the back to front office when needed. AI provides rich insights to truly optimize operations and bridge the long-standing gap between the front and back office.”

Q. There appears to be a trade-off between providing an excellent CX and agent performance and productivity. Namely, “I would like to stay online to serve you better, but my supervisor wants me to go to the next customer.” Please discuss. Is it possible, and if so, how, for CX for performance/productivity to be on the same page?

AI removes a lot of the pressure on agents to do it all. Before AI, agents not only had to worry about getting through phone calls but also took care of non-customer-facing tasks like post-call summaries. Agents also had to spend a lot more time combing through clunky knowledge bases to find answers to customer inquiries, lengthening the time to resolution.

AI eliminates this extra work, freeing up time to focus on building customer loyalty and looking for upsell opportunities. It writes post-interaction summaries. And it also creates robust knowledge bases where agents can instantly pull the information they need to resolve an issue.

Finally, AI frees up the agents’ time to build deeper relationships with customers and shift the focus of an interaction away from simply solving a problem.

Q. AI, like Generative AI, has been seen by some in the industry as being overhyped: overpromising and underdelivering for contact centers. But is it? What types of functions and value is it delivering? And what new applications and value do you see for it and why?

AI has transformed post-interaction summaries. What once was a cumbersome, loathsome task for agents has turned into an automated, much more efficient process.

Before, agents had to spend time after every interaction dictating a summary of how the interaction went. It was subjective and an afterthought as agents dealt with more pressing priorities.

Now agents don’t have to worry about it at all. AI generates an objective, detailed summary of every interaction, noting the appropriate context needed for the next agent who interacts with that customer.

As we look to the near future, ticket-based systems will be phased out and will be replaced with interaction-based systems to provide a more modern, seamless help-desk approach.

“...AI frees up the agents’ time to build deeper relationships with customers and shift the focus of an interaction away from simply solving a problem.” —Barry Cooper

Generative AI is enabling organizations to build more robust knowledge bases and train more intelligent chatbots. This will allow organizations to move to interaction-based systems, able to answer inquiries on any channel, automating many support requests, and reducing the need for manual intervention by support staff.

Advancements in AI will also enable organizations to drive seamless asynchronous customer interactions. These will allow customers to pick conversations back up with human agents or bots right where they left it without needing to repeat information or start the interactions from scratch.

Developments such as this will eliminate the frustration that can commonly be felt by the customer who is asked to repeat things during an interaction. It also gives the customer more freedom if they need to leave an interaction at any time.

This concept, which customers have been demanding, is the future of customer service. It will be fully realized by businesses in 2024 and will lead, I predict, to a 50% bump in CSAT scores.

Q. What are your recommendations to contact center decision-makers?

It has become increasingly difficult to manage customer service compared with even five and 10 years ago. With the rise of digital interactions, there are so many different ways a customer can reach out to an organization, and they demand that organizations be reachable at any touchpoint.

“Organizations need to think of the customer service interaction at the center of their operations. It should drive everything they do.”

Customers want their problems solved immediately on their channel of choice. What may seem like a daunting task is a quite simple fix. There are tools available on the market today that can allow organizations to manage the complexity of interactions we are seeing today.

Organizations need to use an open interaction-centric cloud platform with a suite of solutions underpinned by AI. Organizations need to think of the customer service interaction at the center of their operations. It should drive everything they do.

AI is the future of CX, and we are already seeing a shift from fear to fear of missing out (FOMO) of AI in CX. It is integral to the contact center of the future.

  • AI can be used to analyze every interaction, revealing rich insights about customer sentiment to show how CX organizations can improve operations to provide a better CX.
  • AI can also greatly improve the employee experience, offloading repetitive tasks so that employees can focus on higher-value tasks.
  • Finally, AI can also be used to improve knowledge management systems, creating an effortless system where employees ask anything and receive an accurate, relevant answer, instantly leading to quicker resolutions.

If you would like to learn more about Barry please click here.

Brendan Read

Brendan Read

Brendan Read is Editor-in-Chief of Contact Center Pipeline. He has been covering and working in customer service and sales and for contact center companies for most of his career. Brendan has edited and written for leading industry publications and has been an industry analyst. He also has authored and co-authored books on contact center design, customer support, and working from home.

Brendan can be reached at [email protected].

Contact author


Most Read

Ultimate CX ICMI 20240514
Upland 20231115
Cloud Racers
Mind the Gap Infographic 20240514
Verint CX Automation
Ultimate CX ICMI 20240514