For Better Customer Interactions, Think Beyond Bots

At times, we all have conflicting priorities. This is especially true when it comes to customer service. Everyone wants faster resolutions, but the best customer service interactions are often those that introduce personalization, human-to-human engagement, and maybe even a little novelty. Is it possible to be fast and high-touch? Some companies have built a reputation around either fast service or personalized experiences. Few have learned how to truly excel at both.

While artificial intelligence-powered chatbots and virtual assistants are a popular and important part of the customer service mix, some of the greatest CX benefits happen when human agents are given powerful just-in-time help from AI-based platforms and natural language processing (NLP) tools. These solutions give agents real-time feedback to get to the heart of customers' concerns quickly, while also providing the deep context needed to provide hyper-personalized experiences.

Unlike bots, the right AI tools can make each interaction feel more efficient and more personal at the same time. With relevant customer insights delivered in real time, agents can harmonize seemingly competing expectations within each interaction and not just excel for a specific type of issue or tier of customer, but consistently and across a variety of cases and customer personalities.

The Customer in Context

Our best interactions, both in and outside the realm of CX, feel effortless. They're built on empathy and rapport. Talking with family or a good friend often feels refreshing, rather than draining. That's because of a shared context, a natural affinity, and an understanding of each other. Customer service should feel just as satisfying. Creating those kinds of experiences requires a degree of emotional and intuitive situational understanding that's hard to consistently get right in every customer interaction without the right tools.

NLP-based solutions like acoustic and language models and sentiment analysis can pick up on subtle cues that would normally require the sharp intuition of seasoned customer service representatives to recognize. Equally important, these tools can apply predictive behavior modeling and customer journey analysis to get each customer conversation on the right foot from the very beginning, so agents can confidently engage with customers, even if they haven't directly interacted with them before.

Better Experiences at Scale

Once more accurate, less-intrusive analytics tools are in place to capture and measure sentiment, CX leaders can put those insights to work at an organization-wide scale. Agents now have a single source of truth to measure and improve their soft skills, like building rapport and active listening, rather than having to rely solely on human assessments, which are tim- consuming and often lead to divergent outlooks and recommendations based on the reviewer. Instead, purpose-built NLP tools can look at behaviors at scale to determine which are the most effective at creating better customer experiences. This high-level insight can then be turned back to individual agents, giving them reliable feedback to hone their skills.

Armed with a record of their own past performance, a broader view of organization-wide insights, and the relevant context on each case and customer ahead of time, agents are set up for success before even saying "Hello." That kind of readiness can make or break a business, especially in a virtual-first environment where digital interactions are often the only experience customers have. A study from Aberdeen found that contact centers that use AI-based tools had a 3.5 times greater improvement in overall customer satisfaction and lower levels of customer effort in resolving issues. The report also found that implementing AI led to a 10.5 percent increase in customer retention. In this way, real-time AI-powered insights can clearly translate to long-term brand loyalty.

Steps to Success with AI

So, how do you effectively introduce AI to your customer service operations? Contact centers have their choice of NLP and AI-based tools. But selecting the right purpose-built CX AI models and following a smart implementation strategy can be just as important as the technology itself. Here are a few key steps to get started:

  1. Identify the key players: Develop a clear understanding of who will be interacting with NLP tools regularly and who will be responsible for the implementation, review, and overall success of any solution you introduce. This typically includes customer service managers and broader CX teams, but can also extend to regulatory specialists and compliance experts.
  2. Consider bringing in new talent: Map out additional organizational or IT staffing you'll need to support deployment. Take the time to determine how easy solutions are to implement and which specific skills will be necessary to ensure success.
  3. Prioritize the right customer needs to automate: Draw from case studies, analogous examples from other organizations, and scenarios from your team's own experience to create a case that clearly conveys the benefits of introducing NLP tools. Solution providers can help build that case and illustrate how particular tools align with your key business objectives.
  4. Choose your solution: With a clear business case and a realistic view of what the implementation process will look like, it's time to choose a solution. Flexibility is an important factor to consider, and cloud-based tools often offer greater agility without requiring the infrastructure to maintain or support software on your own.
  5. Get help from experts: Managed services offer an efficient way to access technology expertise and industry knowledge quickly. Consider recruiting managed service providers to help set up your tools and prepare agents and supervisors to use them effectively.
  6. Collect feedback: Create an open channel that allows teams to easily share their feedback on new tools. This will help you continually monitor against your key performance indicators and course correct as needed.

Customer experience can improve dramatically when contact centers shift from evaluating agent KPIs to pinpointing the specific behaviors each agent needs to change to improve their KPIs. Their is a mindset shift from technology monitoring agents to the right technology empowering agents.

There's no better time to introduce NLP and AI-based analytics. These technologies have become increasingly practical, purpose-built for contact centers, and easier to adopt than ever.

Customers are also hungry for faster yet more fulfilling interactions with companies. The steps above provide a fast, easily justifiable way to provide the best of both worlds, while easing the burden on managers and agents alike. Your customers and your teams will thank you.

Chris Bauserman is vice president of NICE CXone.