SmartReader

An analysis of Amazon Reviews of a Nike T-Shirt

The Challenges

Customers buying from online megastores such as Amazon more often than not leave verbatim reviews, explaining their likes and dislikes about the brand or product in question. These reviews if mined can give a great insight into the user's mind.

The challenge, however, is the sheer number of reviews that a brand of Nike’s magnitude generates especially on a point of sale as popular as Amazon. Textual mining of these reviews although valuable, cannot warrant the resource drain in terms of money as well as time. A way of automating the process of feedback analysis is hence, the call of the hour.

Our Approach

A thorough analysis of over 100,000 Amazon reviews for a Nike T-Shirt was undertaken. The goal was to answer these key questions:

  1. What is the general sentiment of buyers in regards to the Nike T-Shirt?
  2. What is the underlying emotion that reviewers display in regards to Nike and the product in question?
  3. What are the key themes that customers talk about in their reviews and what themes can be considered as parameters of success or failure?
  4. What is the individual sentiment towards each of these key parameters?
  5. What are the most frequently used negative keywords in order to gauge the key areas of improvement?

Faster and better

By leveraging the customer reviews on Amazon with ParallelDots’ AI-based solution echoed the customer's voice. SmartReader undertakes a deep analysis and provides targeted results which cannot be identified by conventional methods. In contrast to typical tracking studies, which are limited to simply measuring satisfaction levels, ParallelDots yields not only intelligence about the actual factors driving satisfaction but also quantifies the extent to which each factor actually influences satisfaction. An organization like Nike can use the insights generated by ParallelDots to improve their product’s quality and create an effective retargeting strategy.

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6-7 days

Reduction in time required for feedback analysis

4

Number of unique insights discovered with SmartReader

40%

Expected savings on feedback analysis costs

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