Sentimental Analysis

Project : E-commerce Women Clothing Review

Who isn’t reading them?

Before you purchase a product, very likely that you would read the customers’ reviews before you determine what products to buy and which services to purchase. Customers’ reviews are a great source to analyze what and how the company can improve further. In this dataset, we are exploring on customers’ sentiments and how the retailer can identify the strengths and weaknesses of products.

Source: Kaggle - Women's E-Commerce Clothing Reviews

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Observation

Observation

‘top',5266,

'shirt',2569,

'color',2527,

'fabric',2301,

'really', 2014,

'great', 1921,

'skirt', 1889,

'perfect', 1790,

'think', 1744,

'flattering', 1743

Top 10 most used words - Frequency count

Observation

Explore the reviews that customer gave a Rating #5 but with negative sentiments

Explore the reviews that customer gave a Rating #1 but with positive sentiments

Thoughts to Takeaway

1. Reviews obtained can be used to improve the product features. Example ; The retailer can look at the category “Top” first as this is the most frequent count in all ratings to determine what went well and what went wrong.

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• Since 82% of the customer would recommend the products to their friends, the retailer can build a loyalty program to encourage word of mouth and stickiness to their e-commerce store.