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Emotional AI: Unlocking VoC with Sentiment Analysis


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Every customer behavior is driven by an emotion, and as we know, some emotions are more powerful than others. Anger, disgust, rage — these are feelings that typically lead to customer churn and a very negative perception of a brand. But how can organizations understand these emotions and adjust their strategies in real-time to transform a bad customer service experience into a positive one? By implementing speech analytics powered by emotional artificial intelligence (AI), companies can finally begin to unlock the voice of the customer (VoC) for new insights on customer behavior, attitude, and sentiment like not previously possible.
Sentiment: The verbiage of emotion
Through sentiment analysis, we’re able to evaluate language and voice inflections, gleaning information on a customer’s attitudes, opinions, and emotions toward products, services, and policies. Sentiment analysis allows for objective interpretation of factors, such as the amount of stress in a customer’s voice or how fast the individual is speaking and what that could mean. And by comparing sentiment analysis scores across certain segments, companies can easily identify common pain points, areas for improvement in the delivery of customer support, and overall satisfaction between product lines or services.
There’s no emotional measurement without context
Missing from traditional call center measurement is context that allows for driving efficiency and improvement. When you combine emotional AI with contextual data, call centers now have information on why some calls are long, why some are short — and can improve processes to accommodate each, such as moving short calls to self-service channels. When calls contain long periods of silence, we can analyze and discover what exactly is driving that.
Also, context of the words spoken is crucial. There is so much more rich communication when you can overlay the tonality that accompanies the spoken word, helping to truly understand the sentiment.
The benefits of reading emotion
Sentiment analysis provides critical insight into rapidly growing customer service issues in order to swiftly identify and act on the root cause of issues — mitigating problems before they reach critical mass. Other benefits of sentiment analysis include helping to uncover and improve your brand’s reputation; gaining insight into customer attitudes on services, products, campaigns, or other topics; and providing a unified view of the full customer journey.
Sentiment analysis also helps contact center agents develop an emotional connection with customers, as well as cultivate empathy — which is crucial, seeing as 46% of callers just want to be listened to when speaking with a contact center agent.
Through identifying agents’ words and phrases that show empathy and put the customer at ease, as well as tracking great active listening skills that not only help to isolate the source of the customer problem but also secure agreement to the proposed solution — organizations can bring customer experience (CX) to the next level through giving customers what they need.
Misunderstanding the customer can negatively impact the bottom line through increasing customer churn, diminishing customer loyalty, and decreasing sales opportunities. Through pulling actionable insights on customers’ emotions and sentiment, organizations can reshape their entire CX for optimal success. Behaviors – like resigning a contract or writing a positive review – are driven by emotions. With emotional AI, you can promote customer happiness and satisfaction for optimal results – not fuel anger and rage for churn.
Check out just how prevalent anger is in the contact center with our latest research on consumer profanity and what it means for your business.