In much the same way mutual empathy defines the development of long-term relationships with our friends, it also plays a key role in defining the success of our business’ relationship with its customers. When customers take the time to type their thoughts and feelings into a review for a product or service, share their feelings through a social media platform, or provide feedback through some similar medium, it behooves us to empathize with them as fellow human beings and determine how they collectively feel about what they experienced. Using programmatic solutions, we can quickly analyze and then adjust (or maintain) the experience we provide to our customers at scale, efficiently improving customer relationships with our brand.

Of course, unlike the human brain, computers aren’t raised and socialized to draw specific emotional conclusions from an evolving human language. They need to be trained to do so – and that’s where the field of sentiment analysis and classification comes into play.  Using Natural Language Processing (NLP) techniques, we can train Machine Learning algorithms to analyze and classify unique sentiments in text.

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