Understanding customer feedback gets harder and harder at greater scale and with a greater variety of channels through which customers can provide feedback. Businesses that seek to better grasp the sentiments of their customers might have to sift through thousands of messages in order to get a feel for what customers are saying about their products or services. In order to save time and resources, businesses might look to automation that can quantify customer feedback from channels such as chat messages, emails, call center recordings, and social media comments in real time. Natural language processing (NLP) may help some businesses with a high volume of customer feedback garner insights from it in the form of quantifiable trends, or in other words, increases and decreases in the frequency of specific customer complaints.

Let us see how we can process user reviews of any product and extract some meaningful insights which could be helpful in taking complex business decisions, let’s talk about Amazon Alexa.

Please check out this article to know more.

https://towardsdatascience.com/natural-language-processing-in-apache-spark-using-nltk-part-2-2-5550b85f3340