Text analysis

Major E-Commerce Platform Review Analysis

The Challenges

Our client is a major player in the online apparel and cosmetic retail industry. They have been in the game since the early days of the Internet revolution and have built up a strong and loyal customer base. Such an organization hosts thousands of reviews from their customers on a daily basis. These reviews are unstructured and can lead to efficient buyer satisfaction strategies if analyzed for key metrics. ParallelDots ran a conceptual study using their strong expertise in analyzing verbatim with NLP. Our analysis encompassed opinion mining and emotion analysis of customer reviews on the client's web platform.

Our Approach

An estimated 900,000 feedback of all the brands were collected by the E-commerce giant. The goal was to generate these specific insights:

  1. What is the general sentiment of buyers in regards to the T-Shirt?
  2. What is the underlying emotion that reviewers display in regards to the brand and the product in question?
  3. What are the most frequently used negative keywords in order to gauge the key areas of improvement?

Understanding feedback to boost consumer satisfaction

By leveraging responses to open- ended comment and questions together with ParallelDots’ AI, we provide much deeper and more actionable insights than are obtainable with conventional analytics. In contrast to typical tracking studies, which are limited to just measuring satisfaction levels, ParallelDots yields not only intelligence about the actual factors driving satisfaction (the “Whys”), but also quantifies the extent to which each factor actually influences satisfaction. ParallelDots provides an automated way of turning hundreds of guest voices into a clear understanding of what matters to different groups.



Customer reviews analyzed


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