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The intense competition to attract and maintain customers online is compelling businesses to implement novel strategies to enhance the customer experiences. It is becoming necessary for companies to examine customer reviews on online platforms such as Amazon to understand better how customers rate their products and services. The purpose of this study is to investigate how companies can conduct sentiment analysis based on Amazon reviews to gain more insights into customer experiences. The dataset selected for this capstone consists of customer reviews and ratings from consumer reviews of Amazon products. Amazon product reviews enable a business to gain insights on customer experiences regarding specific products and services. The study will enable companies to pinpoint the reasons for positive and negative customer reviews and implement effective strategies to address them accordingly. As the digital age has evolved, online shopping has seen tremendous growth. Every Business person wants to analyze what their customers are talking about their products. Reviews, star ratings are the accessories of the product that define the customer's engagement. The process of analyzing customer emotions is called Sentiment Analysis. In this article, Sentiment Analysis is performed on Amazon Dataset.

As the digital age has evolved, online shopping has seen tremendous growth. Every Business person wants to analyze what their customers are talking about their products. Reviews, star ratings are the accessories of the product that define the customer's engagement. The process of analyzing customer emotions is called Sentiment Analysis. In this article, Sentiment Analysis is performed on Amazon Dataset.

to achieve more success with more detailed training by comparing with other projects.

. To be able to predict disgust, joy, fear, sadness, surprise, trust, positive and negative sentiments from customer reviews the most frequent words associated with these sentiments are taken into account. Another analysis that is essential in portraying the most positive and negative of words used is the Term frequency – inverse Document frequency analysis, this method plots the most frequent terms in both positive and negative sentiments hence providing a clear picture of the reviews data.

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