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Reintroducing Human Aware Data and AI to the Call Center

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Joshua Feast

Globally, over 15 million people are employed by contact centers – and this number continues to increase.  This workforce may be the largest single global workforce dedicated to encouraging positive customer experiences. Agents intuitively understand how best to engage with customers.  A main reason for this intuitive strength lies in their ability to hear emotions in voice.  Not just what is being shared, but how the message is communicated.  Modern AI solutions recognize the value of human-centered data and build Emotion & Conversation models to help address conversational complexities.  Solutions that mine human-aware signals and data to empower conversation are critical to the modern contact center.  Let’s take a look at why. . . 

More Complex Interactions with Higher Stakes

McKinsey recently published insights featuring the State of of customer care in 2022-  and succinctly summarized what many contact center leaders have realized in the last few months—the digital transformation investments of the past five years have proven to be almost too successful.  These solutions have effectively deflected and automated away the most basic, transactional and simple customer interactions. What remains are the complex, frustrating, and difficult interactions for professional service agents to manage.

Most live customer/agent interactions are triggered by either an escalation from a self-service channel or a request for assistance from a digital process. In both scenarios, the customer couldn’t complete what she was trying to accomplish and tended to enter the conversation expressing frustration and annoyance.  Both of these experiences feature the common denominator: a human at the center of the back and forth.  So how the agent delivers a message and how the customer receives that information require some level of understanding that humans are unpredictable and represent a diverse set of cognitive and lived experiences.  

Customer Obsession and Customer Centricity

Enterprises continue to incorporate “customer obsession” into their overall strategy—not just the marketing of products and services, but at the center of the organization’s leadership, strategy and business processes.  The result is a positive customer experience- or better perception of the interaction customers have with the business.  The emphasis on the customer interaction is central to most investments prioritized by the contact center, with an agent supporting customer queries through a “single pane of glass,” additional digital channels to service customers at all entry points to the brand, and more up-sell and cross-sell suggestions fed during real-time interactions.  Customers are being trained to expect personalized service that recognizes what they want, how they want it, and how they are feeling in the moment.  

In response, agents are expected to assess how a customer is feeling and lead a conversation that is emotionally nuanced.  Agents need to assess how customers are feeling and consider their needs before making some of these automatically generated next best offers.  Such intense, high-stakes conversations are taking an incredibly high toll on agents.  They must be better equipped, with what we call human-aware data that surface how customers feel and provide them with actionable cues to adjust what they say and how they say it.  

A Focus on Employee WellBeing

The pressure to deliver positive customer experiences, increase productivity or efficiency, and in many cases increase opportunities for up-sell or cross-sell can take its toll on the agent.  Most agents are covering 8-10 hour shifts and fielding at least 30-40 calls a day.  In addition, they are navigating these complex calls with increasingly more complex technical tools & systems.  Despite new automation solutions that are designed to “make it easier,” we know agents are experiencing higher burnout than ever before.  Attrition numbers suggest this phenomenon is increasing – especially when remote work makes it easier to jump from one contact center to another. 

A recent survey of Fortune 500 employers in the  contact center found that half witnessed an attrition over the past 12 months.

The innovative enterprises have begun tackling this challenge with cross-functional workforce optimization teams – with a mission to invest in understanding the Employee Journey with just as much focus and diligence as the Customer Journey has traditionally been considered.

Human Centered AI will Make a Difference

Humans are instinctively sensitive to emotional states. It’s particularly true in face to face interactions by reading our facial expressions or hand gestures.  On the phone, our voices provide all the emotional information and context necessary.  With modern AI, machine learning scientists can distill the signals in the voice to understand emotional states. Training AI models to identify the nuances in how we convey information, and then feeding real-time guidance to agents results in richer, more authentic customer interactions.

McKinsey predicts that by 2025, the most successful organizations will have integrated data into their decision making processes in order to enhance the “human” part of customer experience & employee experience.  

For the Contact Center and their agents, this means introducing real-time insights that anticipate customer  and agent needs – Emotion AI & Conversation AI.  Emotion AI and Conversation AI reflect machine learning built upon a combination of non-verbal and verbal signals generated via conversation. Emotion AI refers to the acoustic signals of how things are said, while Conversation AI reflects what is being said. This powerful combination of machine learning delivers human-aware data covering not just the conversation but agent well-being and customer experience and sentiment.  The resulting models that assess CX and EX are gleaned from all calls, all interactions – delivering nuanced insights and opportunities for interventions in the moment – without waiting for longer term process initiatives to catch up.

Human-aware AI meets the customer expectations as well as the agent’s needs – empowering agents to deliver on expectations of personalized customer interaction without taxing the agent’s mental efforts.  Emotion AI models are delivered in real-time and agents who respond to the behavioral guidance participate in a feedback loop – supporting the development of better models and ultimately better guidance.  In Conversation AI, the signals pick up on the topics and themes in conversation to activate reminders, next best action offerings, or instructional guidance during a conversation. What may have originally been a 1-way query from customer to agent, becomes a three-way conversation between the agent who can respond, the customer who can more thoroughly engage, and the AI which offers appropriate and relevant feedback.

Unlike purely quantitative data, human aware data is more sensitive to identifying stressors that can impact both customer experience and employee wellbeing. With employees, we can take advantage of this data to hone in on the teams or sites at increased risk of burnout, and track the success of workforce optimization solutions that are designed to mitigate unfortunate attrition.  

The near future will feature more and more emphasis on the applications of data to improve interactions – Cogito has never forgotten that the front line should be equipped with resources to enhance and improve these human interactions – tools and guidance for the moment – that feel human, relate to the human, and empower the human.


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