It’s impossible to overstate the value of positive customer experiences, but businesses are clearly struggling to crack the code on quality care. Fortunately, generative AI can demystify care and help contact centers deliver the experiences customers crave.
In this blog, we’ll outline 5 key ways generative AI helps drive efficiency and effectiveness in contact centers focused on customer care.
The right information at the right time
In order to provide quality customer care, agents need access to information. But answers to customers’ questions may be housed in scattered repositories across the organization. Even if the contact center uses a central knowledge base, there’s no guarantee that it’s easily accessible—some agents are stuck manually scrolling through PDFs or calling an internal help desk any time they need to find an answer. This leads to longer wait times, frustrated customers, and burnt out employees.
This is an obvious drain on agents, but it impacts customers, too. More than 60% of customers say they have hung up mid-call due to frustration with an agent, and roughly the same percentage have been forced to follow up with a company more than once to receive an answer to their question.
While it’s not the agent’s fault that they can’t access the relevant information quickly enough, this fact is invisible to customers—the poor experience ultimately has the same impact, regardless of the cause.
But generative AI can eliminate this problem. AI-powered knowledge assist surfaces the exact answers agents need in real time, allowing generative AI to do the work for them by taking the context of the conversation into account, proactively querying all of the internal knowledge resources across the organization (no matter where they live), surfacing answers, and linking to the source—all from a single interface.
For more complex, cause/affect situations, guided workflows give agents a proven decision tree guiding them through all possible scenarios, ensuring they provide exceptional customer care. And the right solution can even deploy smart compose and one-click suggested response capabilities to speed agent response times in chat.
As a result, customers quickly receive the answers they’re looking for, increasing customer satisfaction (CSAT); they receive those answers on the first try, increasing first call resolution (FCR), and agents waste less time sifting through scattered information, driving down average handle time (AHT).
Offloading after-call work
While the amount of time dedicated to after-call work (ACW) varies by industry and organization, it’s universally true that tasks like note taking and call summarization are hidden drains on agent efficiency.
Still, there’s no way around it. In order to provide superior customer care, notes and necessary follow-up items from conversations need to be properly documented. This documentation is particularly important for transferred calls—all too often, customers are passed around through cold transfers, forcing them to recount the entire conversation to a new agent rather than picking up where they left off. But with generative AI, these routine tasks can be offloaded from agent to tech.
AI-driven solutions can pull key information from the live conversation, handling note-taking tasks in real time and eliminating this element of ACW entirely. Similarly, generative AI platforms can summarize conversations and even upload them to the organization’s CRM or schedule follow-up tasks. And when a call must be transferred, generative AI ensures the new agent has the necessary context to deliver the best possible CX.
With ACW off their plates, agents can steadily field customer inquiries rather than pausing to handle administrative work.
Customer-centric analytics and strategies
Many companies claim customer obsession as a core tenet, but few live up to it. In fact, only 3% of companies were classified as customer-obsessed in 2022—a 7% drop over the previous year. For contact centers focused on customer care, this is clearly unsustainable.
Even as customer obsession and CX apparently trend downward, contact centers have the opportunity to leverage generative AI to keep customers at the center of their strategies. With insights organizations can now unlock data that is often buried within the business including the customers’ reasons for calling, common topics, and frequently used keywords, contact centers can detect trends and anomalies before they spiral out of control.
For example, a contact center using an analytics solution powered by generative AI may notice a spike in calls related to shipping delays. By gaining visibility into this trend early, contact center leaders can craft a response immediately rather than leaving agents to fend for themselves.
Not only does generative AI empower an almost clairvoyant level of customer care, it also ensures agents have the guidance they need to efficiently respond to customer queries.
Personalized coaching when it counts
With agent churn rates reaching pre-pandemic levels, care-focused organizations rank retaining and developing the best people as a top priority in the immediate future. Coaching is undeniably one of the most effective ways to keep agents engaged and help them excel—when managers have the bandwidth for it.
The traditional approach to coaching is slow, incomplete, and (often) ineffective. Managers rely on a small sample of calls to identify coaching opportunities and coaching sessions are held days—or even weeks—after the coachable moment has passed. As a result, managers coach with major blindspots, and agents rarely retain the new skill right away.
With generative AI, managers can augment their coaching bandwidth by identifying coaching opportunities and allowing agents to request support in real time. And without manager intervention, generative AI solutions can prompt agents with suggestions based on the conversation at hand, such as advising them to show empathy.
Not to mention, managers gain visibility into 100% of agents’ conversations, meaning coaching sessions can be highly personalized based on a complete picture of agent performance. In parallel, agents can access their scores, conversation insights, and coaching plans, enabling a more transparent relationship between supervisors and agents built on facts rather than assumptions.
This gives care organizations a leg up—by embracing generative AI, care-focused contact centers can transform into revenue generation centers thanks to customized coaching during the conversation, such as when an upselling or cross-selling opportunity arises.
From improving response times to ensuring consistency, generative AI drives efficiency and effectiveness in a variety of ways throughout care organizations. To learn how Cresta’s generative AI-driven platform can transform your contact center, view our solution brief or reach out for a personalized demo.