Data Science
Improve customer experience by analyzing product reviews of e-commerce website
Help Snapdeal build a Machine Learning model using Sentiment Analysis in R to improve customer experience for fashion product categories
About this Menternship

Snapdeal is building India's most reliable and frictionless commerce ecosystem. It currently operates across more than 6000 cities and partners with 300000 sellers for selling 60 million + products. The data Science team at Snapdeal is taking on the ambitious project of building a platform that empowers the future generation of creators to be successful online.


When you go to purchase an item online - what is the first thing that you do? Check out product ratings and reviews! Reviews are all the more important for the category of womenswear as they provide customers vital information about quality and fit that a customer couldn't have ascertained from pictures alone. Womenswear holds as large as 50% of e-commerce market share and its volume is only growing every year. The e-commerce website that can deliver the highest value for money to their customers womenswear would definitely have an edge in this industry that's brimming with both multi-national and hyperlocal competition.



In this menternship, you will be challenged to build a natural language processing model using Sentiment Analysis in R to identify the pain points of customers purchasing goods within the womenswear category. You will work with a dataset of product reviews from an e-commerce website.



Why take up this Menternship?
On completing this Menternship, you will learn about
You will explore: 
R studio
Sentiment Analysis in R

You will apply:
Data wrangling, Data cleaning, Data Visualisation
R Programming
Research and Intuition - Product reviews

You will create:
Recommendations for improving customer experience in e-commerce


Expected Output
  1. Complete research report on Applications of NLP in E-commerce
  2. R Script including proper comments and working codes for Tasks 1 and 2.
  3. Complete Code - R Notebook
  4. Presentation with final recommendation
  5. Video of self
Improve customer experience by analyzing product reviews of e-commerce website
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