The Top Customer Service Trends for 2023: As Remote and Hybrid Work Continues, the Cloud and AI Loom Large

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During the height of the COVID-19 pandemic, almost all contact center agent jobs shifted to a work-from-home model. And now that the pandemic has basically come to an end, many of those jobs have returned to the office, but a large number of agents are expected to continue working remotely for a long time to come.

In its latest global contact center survey, Deloitte Digital found that 69 percent of organizations today still have a work-from-home program in place, with 73 percent of those expecting to continue having a work-from-home program in place two years from now.

With these work-from-home programs becoming integral to modern contact center operations, the technology landscape has already been transformed, and the pace of change will only accelerate, experts predict.

One of the biggest changes, implemented quickly to accommodate the move to remote work, was the shift to cloud technologies. In the past two years alone, the number of organizations that have moved analytics, CRM, knowledge management, interaction recording, and workforce management systems to the cloud increased by approximately 50 percent, according to Deloitte’s data.

Now artificial intelligence, analytics, self-service automation, agent enablement, and critical infrastructure upgrades are the top priorities for customer service organizations, Deloitte reported.

Many of these same technologies also topped the investment priorities cited by Gartner in its latest customer service and support tech trends report. The top five contact center technologies on Gartner’s radar this year include case management systems (cited by 83 percent of respondents), internal collaboration tools (82 percent), cloud-based systems (79 percent), knowledge management systems (78 percent), and customer analytics dashboards (78 percent).

Among those, analytics are likely to see the largest bump in deployment by the end of this year, Gartner says.

The analytics methodologies expected to have the most value in the next two years are predictive analytics (cited by 85 percent of respondents), digital experience analytics (84 percent), customer journey analytics (83 percent), sentiment analytics (72 percent), customer journey analytics (68 percent), and digital experience analytics (65 percent), Gartner says further.

Deloitte’s data also supports the claim that analytics is on a sharp upswing. Usage of voice and text analytics, for example, has increased from 62 percent in 2020 to 81 percent today, according to Deloitte.


In the broadest sense possible, the leading technology innovations being employed by customer service organizations today have centered on conversational intelligence, which can extract sentiment and other details from customer interactions, analyze customer interactions at scale, and give companies a sense of what’s on the mind of customers when they reach out across the wide variety of channels and platforms available today, experts agree.

“Customer service and support leaders see the value of tracking customer experience as they navigate digital and multiple channel offerings,” says Lauren Villeneuve, senior director of advisory in the Gartner Customer Service and Support practice.

Other technologies where Gartner expects to see significant increases in value to contact centers during the next two years are virtual customer assistants and chatbots. These technologies held the largest increase between current and future value, with roughly three-quarters of leaders indicating that chatbots will be highly or very highly valuable to their organizations in two years.

Customer self-service and assisted service will also be incredibly valuable going forward, Gartner maintains.

“Today, the most impactful technologies in service are the ones that support reps to deliver low-effort, value-enhanced experiences in the live channel,” Villeneuve says. “These technologies are critical to continue to shift customers’ transactional issues to self-service so reps can focus on more complex issues.”

That’s a sentiment shared by Deloitte, which found that nine in 10 customer service leaders will invest in additional self-service capabilities in the next two years, with a goal of driving customers to conversational interactive voice response systems, interactive FAQs, virtual agents, and/or chatbots. At the same time, 74 percent of organizations are currently at some stage of testing or deploying customer-facing chatbots, Deloitte says.

These are not the only channels that are on the rise, though, Deloitte expects channel growth to remain a high priority, with 69 percent of service leaders now saying they plan to expand (or keep expanding) their service channels in the coming two years.

But that will come with its share of problems. The biggest, according to Deloitte, is that only 7 percent of the contact centers that offer multiple service channels can transition customers between channels seamlessly by providing data, history, and context to the next agent or system when customers need to shift between them.


The effort to overcome that presents a huge opening for real-time agent assist technologies, says Frank Schneider, a vice president and artificial intelligence evangelist at Verint. His company added those capabilities, including real-time sentiment analysis and assist functionality, in the Verint Customer Engagement Cloud Platform in late 2021.

Only a few years ago, agents had to use linear decision trees, but now front- and back-end technologies work together to more quickly understand what an agent is attempting to do. In return, the technology provides agents with next-best-action recommendations for customer service, including upselling and cross-selling options, according to Schneider.

The benefits cannot be ignored, he adds.

Next-best-option recommendations and real-time coaching recommendations improve first-call resolution rates and Net Promoter Scores, he says. “Agent enablement technology is something that we have always wanted to get to. RealTime Agent Assist is taking us there.”

Agent coaching and assistance has been a priority since the earliest days of the contact center, but the main difference today is the desire for such capabilities to act in real time, while the agent is communicating with the customer, according to Michelle Tilton, vice president of marketing at Gryphon.ai.

“We’re seeing a ton of workforce automation to support agents in real time,” she says, noting that companies want to coach agents in real time rather than the legacy method of recording and reviewing calls later.

Workforce automation is also being applied to processes for onboarding new agents and arming them with the knowledge they need to get acclimated quickly, Tilton adds. “Companies are coming to us to reduce the burden of agent onboarding and to be able to provide guidance in real time.”

That’s not to say that post-call coaching has no value, because it does, she argues, pointing out that modern solutions can automatically flag positive and negative calls to make post-call coaching more effective.


All of these systems require a lot of data and quick access to it, which is also pushing companies to increasingly adopt customer data platforms (CDPs) and make them accessible to their contact center personnel.

Christian Wettre, senior vice president and general manager of the Sugar Platform at SugarCRM, sees tremendous value in data technologies. “CDPs create a combined digital surface area. They provide a single source of truth, making it easier for the organization to evaluate how well people are collaborating together,” he states.

Another growing technology category in the customer service space is customer journey orchestration, a strategy and toolset for the coordination of all customer experiences in real time, in an omnichannel environment, from the first customer touchpoints through post-sales and support.

Companies are using customer journey design to determine the channels that customers tend to use and where disconnects might exist, Verint’s Schneider says. Armed with this information, companies can develop repeatable workflows to more quickly resolve customer service issues.

Contact center technology can include a wide array of different systems, Schneider explains. “Customer journey design can be done in such a way that it is aware of all of these technology solutions.”

“Customer service and support leaders recognize that the future lies not in simply adding more channels but in delivering a continuous multichannel experience supported by consistent knowledge content and smooth, nonrepetitive channel transitions,” Gartner’s Villeneuve adds.

That also opens the door for greater and more varied use of traditional business intelligence. Though this isn’t a new technology, business intelligence for customer service has evolved, Schneider says. “We have finally moved to what we should have been doing all along, which is actually listening to customers. Customer experience used to be a nice-to-have, but now you need to make sure you keep the customers you have. This means building tools and systems that are customer-centric in every way. It starts with a business intelligence solution that focuses on listening to customers. You have robust data from the monitoring of agents and a scoreboard of how they interact with customers.”

That information, combined with website interaction data and workforce management data, enables companies to understand what customers truly want in terms of service, according to Schneider. “That means opening the door to good customer service.”


And no discussion of CRM technologies today would be complete without mentioning the increasing role that artificial intelligence will play. AI is being incorporated into most of the above technologies with the goal of further improving customer service.

“AI currently in customer service is being used to determine sentiment,” SugarCRM’s Wettre says. Companies have thousands of interactions with customers through various channels. AI goes through those interactions, categorizes them, and scores them in terms of customer sentiment so that companies can provide enhanced customer service, he explains.

With AI and natural language processing, call sentiment can be measured not just by the words spoken, but also by the tone of the caller’s voice, according to Tilton. This is important because it helps detect when customers are being sarcastic or serious when, for example, they say they are satisfied with the customer service they received. AI also detects when a call needs to be escalated from a self-service channel to live agent assistance or from a tier-one agent to a supervisor.

“AI is becoming smarter in learning how to resolve an issue,” Tilton explains. So if a high-value customer expresses anger, the technology can automatically push the call to a manager without waiting for the customer to say the word “manager.”


And, of course, there is no getting around generative AI, which is expected to have a huge transformative effect on contact centers going forward. Across all CRM sectors, it’s the AI functionality that is getting most of the attention today. “The hype for generative AI and everything around it has been insane,” Schneider says.

Customer self-service is going to be enabled by generative AI, with customers asking questions and receiving answers without ever needing to engage a contact center agent.

Generative AI can craft automated responses to customer queries across digital channels, including emails, text messaging, chat, social media, and more, and guide agents toward the right answers in agent interactions.

While many fear a generative AI takeover of the contact center, Schneider warns against looking at ChatGPT and similar large-language-model AI as a replacement for hundreds of live agents. “That is folly. It’s not just another chatbot. It’s a new source of data that is easier to query and leverage. But like nuclear power, it’s a little more dangerous at times.”

But that’s no reason to avoid the technology. “Customer and talent expectations have shifted greatly thanks to accelerated efforts to modernize contact center technology and deliver more seamless customer experiences,” said Dounia Senawi, Deloitte Digital chief commercial officer and a principal at Deloitte Consulting, in a statement. “By adapting to changing circumstances and embracing new technologies, such as AI automation and self-service options, businesses enable contact centers to deliver exceptional customer experiences and gain a competitive advantage.”

Villeneuve agrees. “The technology landscape in service and support is constantly evolving, and we expect it will continue to do so, particularly with the recent advent of generative AI,” she says. “For now, leaders are continuing to find value in the technologies which have traditionally supported service and are looking toward these technological advancements to further mature the function.

“Technology is moving quickly, so being immature is not a bad place to be,” she concludes. 

Phillip Britt is a freelance writer based in the Chicago area. He can be reached at spenterprises1@comcast.net.

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