AI: Friend Not Foe of Contact Center Agents

Many of us dread the experience of calling into a company’s contact center, for the sheer fact that we often can’t get to the right person to get the right answers.

Today, there is an increased focus and competition to provide premier customer experience thus making it even more important for companies to consider emerging technologies like artificial intelligence and voice analytics to support their fleet of agents. Although agents may fear that AI will soon replace the need for people, nothing can substitute the human touch that a live agent can provide.  Rather than displacing agents, artificial intelligence is providing an opportunity to increase an agent’s knowledge base and assist them during their interactions to enhance the experience for contact center managers, agents, and the end consumer.

Below are five practical applications of how data-driven contact centers and their agents can leverage AI to improve selling, reduce churn, and enhance the customer experience.

Start with digital first

Sydney calls into her telecommunications company to inquire about changing her internet speed. Sydney is immediately greeted with a digital assistant, where she can use voice navigation to get answers to commonly asked questions using automated, friendly, and conversational self-service.

Digital assistants, also known as chat bots, use natural language processing (NLP) to provide the ability to understand and interpret meaning while gathering context to personalize every interaction. In this example, Sydney is quickly able to understand what internet speed packages are available for her location.

Get routed to the right person to get the right answers

Sydney has further questions about what package would be appropriate based on her historical usage and asks to be connected to an agent.

Intelligent call routing is applied to determine which agent is best suited for her in order to get her specific question answered and drive the best outcome. Compared to traditional IVR, which simply looks at the first available agent, intelligent call routing automatically routes Sydney’s call using AI models that optimize data such as her demographics, interaction history and lifetime value, and the agent’s historical performance to help her get to the right representative – in this case, she is matched with Ryan!

Understand context and emotions

Before the conversation even begins, Sydney’s intent for her call has already been captured and is readily available for Ryan to engage. Data from the digital assistant and AI routing models can be leveraged and Ryan can now apply this context to provide a personalized conversation with Sydney.

During the call, voice analytics is applied to translate her speech to text real-time and analyzes audio patterns to evaluate Sydney’s sentiment and emotional content in her voice, such as a heightened sense of frustration, anger, or overall satisfaction.

Drive the conversation to the best statistically predicted outcome

With tools such as sentiment analysis, emotion detection, topic categorization, and predictive modeling, Ryan can be equipped with real-time analytics and insights to guide the customer conversation with confidence by predicting outcomes supported by a data-based confidence interval. Predictive modeling helps Ryan analyze the call real time to predict the outcome of various scenarios, and the net impact to customer satisfaction based on a set of goals, hypotheses and other factors.

Ryan receives data-based insights and prompts on his user interface at the optimal moment within the customer interaction to guide the conversation. Using this context, Ryan successfully recommends the optimal product package to suit Sydney’s specific internet needs, resulting in the best outcome and personalized experience.

Individualize training through data-driven learning

Once an organization becomes rich with real time data, companies can evolve to support a training strategy that is personalized to Ryan’s individual learning on a daily and even minute-by-minute basis. Ryan’s performance metrics and voice analytics help to shape his individualized training program that focuses on Ryan’s specific knowledge gaps and help increase his knowledge base.

New personalized training can provide real-time, direct feedback and coaching using techniques such as webinars, quick popups, or direct supervisor feedback –creating an environment for positive learning and overall improved customer experience and outcomes.

By implementing these best practices, businesses will see even more improvements to contact centers and deliver world-class customer service that drives revenue and growth – at the same time eliminating the cliché of the dreaded contact center experience altogether.

Jeniffer Walsh is a senior management consultant specializing in CX transformation, digital optimization, and Artificial Intelligence technologies for growth.