As businesses in a wide range of industries are discovering, the powerful and versatile artificial intelligence (AI) capabilities embedded within the latest generation of contact center solutions can quickly and measurably upgrade the employee and customer experiences alike.
Take the case of a national network of urgent care facilities which my company works with. Its customer support teams were struggling to keep pace with an increasing workload as the company grew, plagued by problems related to their reliance on aging legacy contact center systems.
No longer willing to live with the deficiencies and mounting costs associated with maintaining a patchwork of disparate contact center systems, tools, logins, and data sources the company decided to modernize its contact center operation.
It chose a cloud-based contact center-as-a-service (CCaaS) solution embedded with AI capabilities and managed by a third party that together would ensure it could continue to meet its own high standards for customer support.
Following implementation in 2022, that decision was quickly vindicated. Today the company has deep insight into customer interactions and agent performance across channels. Its agents and their managers can easily access and view data from multiple systems on single screens for 360-degree insights into the customers’ journeys, agent performance, and high-level trends.
…a shift to CCaaS with AI…might be warranted.
Contact center data is simple to manage and analyze. And now, as readily as the company’s CCaaS solution integrates (via prebuilt connectors) with other key components of its IT infrastructure, including PCI Pal, Zendesk, and Salesforce, it is building a fully integrated, enterprise-wide digital ecosystem.
As this example illustrates, the AI capabilities available to contact centers (often as plug-and-play tools within a CCaaS offering) are indeed tantalizing for their ability to reshape the employee and customer experiences.
Shift to AI-Enabled CCaaS Warranted
Yet to maximize their value to a contact center operation, organizations first need to ensure they have a solid IT foundation in place.
Before we discuss what goes into building that foundation, let’s touch on the factors that suggest a shift to CCaaS with AI, like the one executed by the aforementioned urgent care network, might be warranted.
Increasingly high contact center capital and operating costs, often associated with on-premise equipment, are a big red flag. In particular, the capital costs associated with maintaining legacy contact center systems can be burdensome and unpredictable.
Another indicator to watch for is a low first call resolution (FCR) rate, which can result when contact center agents lack insight into their customers, as well as the tools to resolve customer issues in the moment. This inability to quickly and satisfactorily resolve customer issues can negatively impact overall customer satisfaction scores, which in turn can dampen sales and hurt the business.
In terms of customer experience (CX), long wait times, repetitive authentication processes, a lack of context from one channel to another, and limited channels for contacting the business are other telltale signs.
Factors like these tend to turn off customers, to the point where they’ll not only take their business elsewhere, they also may be inclined to share their negative experience with others on a very public platform.
On the employee experience side, a lack of current information about your customers hampered by cumbersome, repetitive processes requiring bouncing among multiple, siloed systems, lack of intelligent digital tools, and high agent churn are also indicators of trouble.
Laying the Groundwork
The issues like those listed in the preceding section could be ameliorated with AI-driven CCaaS. But for your organization’s contact center to benefit, you first need a solid IT foundation, one consisting of the following.
- Cloud readiness. Because AI requires a vast amount of computing power, most AI-driven contact center capabilities are cloud-based. So, in order to explore AI tools in the context of their contact center operation, an organization first must be ready to move from on-premise systems and hardware to the cloud.
- A powerful and flexible network platform. As more organizations embrace hybrid work (60% according to a Playvox study) they need a strong, resilient, reliable, and secure communications network. One that can enable agents and managers to readily access the apps, systems, and information they need, in real time, to work efficiently and support customers from anywhere.
- Strong security around your network and the data, users and apps attached to it. The prevalence of hybrid work creates new vulnerabilities that organizations must protect.
- The best way to counter the growing sophistication and persistence of cyberattackers (who are embracing AI according to Google Cloud’s Cybersecurity Forecast 2024) is with sophisticated security solutions. Examples include Secure Access Service Edge (SASE) and Security Service Edge (SSE).
- Both of these methods integrate multiple security layers into a single, cloud-native software stack to safeguard all the potentially vulnerable surfaces of a network, even when the contours of that network are shifting.
- In tandem with a more sophisticated security solution, be sure to implement and enforce strong bring-your-own-device (BYOD) policies as a protective measure, perhaps with support from a mobile device management (MDM) solution.
- Develop a plan for reskilling members of your IT staff so they’re equipped to take on new responsibilities related to the cloud. No more on-premise equipment to manage means new roles for some people.
- (Re)train agents to deliver support across multiple channels. Your agents must be skilled in the nuances of multichannel customer interactions, and if you follow a hybrid work model, you’ll also need to ensure they’re comfortable working remotely.
- A mastery of your data. AI depends on fresh, trusted data to learn and provide valuable insights. The more accessible, reliable, and comprehensive your data is, the better your AI tools will be at delivering value to the business.
- A strong in-house understanding of AI. From your customer support agents all the way up to the C-suite, when your people have a good working knowledge of AI and the specific AI platforms and capabilities they’re using, your AI-driven contact center investments are likely to provide a faster time-to-value.
As more organizations embrace hybrid work…they need a strong, resilient, reliable, and secure communications network.
As you’re putting these foundational elements in place, keep in mind that this investment of time and resources to prepare for AI can benefit your entire business, not just the contact center. As versatile as AI is, you’ll be well-positioned to put it to work across your organization in a wide variety of use cases.
Compelling Contact Center Use Cases
Once the groundwork has been laid, now comes the fun part: watching AI go to work inside your contact center and your business.
The CX is one area where it can make an immediate impact. It enables organizations to offer more nuanced, highly personalized support, preserving the context of interactions across channels, with seamless, natural conversations and interactions that can jump between phone, text, chat and email without a blip.
Resolving issues becomes a much more straightforward exercise because agents have the complete picture of the customer right in front of them: communications channel preferences, past interactions, buying history with the company, etc.
These capabilities, coupled with AI-driven sentiment analysis tools that enable an organization to track evolving changes in customer satisfaction, can help an organization reinvent the customer experience.
On the agent side of these customer interactions, AI tools embedded in the contact center platform are listening and providing agents with contextual resources and information. They work to recommend follow-up questions and best next actions, all in real time, so agents have exactly what they need to provide excellent customer interactions and resolve issues faster.
Once a customer interaction concludes, a Generative AI tool saves huge amounts of time by summarizing the interaction and applying disposition codes. All the agent needs to do is review the AI-produced summary to ensure it’s on target.
…AI also can help organizations manage their contact center workforce more efficiently by analyzing historic data to make scheduling recommendations.
AI also can learn to identify interactions that may not require agent contact, routing customers to a chatbot for resolution, which, in turn, frees agents to focus on interactions that require a higher, human touch.
Ultimately, improvements like these create a positive experiential loop, where agents feel empowered because AI tools are consistently feeding them the right information and resources, and the right questions to ask, at the right time.
As a result, they’re more productive and feel more engaged in their work, which translates into a higher caseload capacity and resolution rate for the contact center, along with a better overall experience for customers.
There’s a big training benefit too. With AI by their side to fill in knowledge gaps, even new agents can perform like seasoned ones, climbing the learning curve much faster than they otherwise would.
AI also makes contact center quality management a more straightforward proposition. Rather than supervisors manually reviewing recorded customer interactions – a tedious and time-consuming process – natural language processing-driven tools can review, summarize, analyze, and pull trends from those interactions. This sharply reduces the cost, time, and effort required for supervisors to evaluate agents.
AI is also good at gleaning insights into high-level contact center quality trends across channels, as well as trends in customer queries, with predictive capabilities that can identify emerging customer issues sooner than they otherwise would be spotted, and alert managers accordingly.
On the resource management front, AI also can help organizations manage their contact center workforce more efficiently by analyzing historic data to make scheduling recommendations.
Ultimately, AI use cases like these not only can turn the CX into a true competitive advantage, they also can give organizations an edge in retaining high-performing agents with a superior employee experience: a critical consideration amid today’s prevailing labor shortage.
What’s more, as rapidly as the models behind AI can learn, the range of potential use cases inside a contact center is bound to grow. Organizations that have a solid foundation for AI in place will be well-positioned to explore them.
