Humans can easily interpret emotions and feelings. Social and emotional intelligence are automatic to us, allowing us to react on instinct, respond with empathy, and connect with the other person—contributing to a flawless customer experience. Now, the question is: can this automatic understanding be taught to a machine, allowing a bot to know how you’re feeling? Sentiment Analysis is the answer behind all this…
Sentiments can be perceived as positive, neutral, or negative. For a better understanding of how Artificial Intelligence (AI) recognizes feelings and their magnitude, we decided to explore sentiment analysis (also known as opinion mining).
What is sentiment analysis?
Sentiment analysis is the process of analyzing customers’ input to determine the emotional tone they carry. This allows the brand to determine the user’s attitude toward the subject and stay on top of consumers’ opinions and intervene where possible.
This technology is a branch of machine learning, which aims to improve communication between man and machine, creating an AI that is able to communicate in a more authentic way. It tries to decode the emotional tone of conversations powered by advanced language algorithms. Sentiment analysis senses whether the feelings in a conversation are positive, neutral, or negative, while also quantifying them.
Why is it useful for your contact center?
Sentiment analysis is a valuable tool that provides insights into the actual mood behind the text and can be applied in multiple ways in contact centers. It can be used to assess the nature of customer comments in phone calls, text messages, emails, and chat sessions. Based on the customer’s sentiment, the call can be routed, for example, to an agent that is very good at handling angry customers.
Contact center sentiment analysis is a powerful feature that analyzes conversations in real-time for words suggesting positive, neutral, or negative feelings toward a brand, product, service, or company. This allows you to have a better perception of how customers feel toward you, giving supervisors a global idea of how interactions are going, and helping agents to adapt the way they handle the call.
Some extra Workforce Optimization (WFO) suite KPIs are added, allowing a correlation between sentiment and metrics like call duration, hold time, silence, evaluation score, and Net Promoter Score (NPS). This allows you to identify opportunities that until now may have gone unnoticed.
With sentiment analysis technology, AI is one step closer to gaining emotional intelligence and replicating those emotions! Who knows if in the future we will have bots completely capable of learning empathy…
How can Collab help you?
Speech Analytics is Collab’s AI solution with Sentiment Analysis that enhances contact centers’ operations, extracting value from sentiments. This technology examines calls and assesses both the agent and customer’s tone, and transcripts voice into text to extract relevant information. The results are indexed, searchable, and can be used to improve CX, as well as identify selling opportunities.
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