When we look at how big data analytics has enhanced Customer 360, one of the first disciplines that comes to mind is sentiment analytics. It provided the means for expanding the traditional CRM interaction view of the customer with statements and behaviors voiced on social networks. And with advancements in natural language processing (NLP) and artificial intelligence (AI)/machine learning, one would think that this field is pretty mature: marketers should be able to decipher with ease what their customers are thinking by turning on their Facebook or Twitter feeds. While sentiment analytics is one of the most established forms of big data analytics, there's still a fair share of art to it. Our take from this year's Sentiment Analytics Symposium held last week in New York is that there are still plenty of myths about how well AI and big data are adding clarity to analyzing what consumers think and feel.