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An Empirical Study on E-Commerce Site Using Unique AI Based Features and Data Science Tools

EasyChair Preprint no. 10674

8 pagesDate: August 6, 2023

Abstract

As with the advancement of modern day techniques in the field of Information Technology, the way of shopping through E-Commerce site is becoming outdated. there are two ways through which an individual can do shopping first is the online method and second is the offline one in today's world online shopping by having more variety of products available on individual platform with easy way of shopping because of this day by day the businessman who are doing business with offline method are facing daily challenges to increase their sales and getting data of demanding products that are available in the market , now with the growth of artificial intelligence ,they can use lot of beneficiary tools to boost their business. If a giant next generation E-Commerce site is made with which we can connect all the wholesalers ,retailers and customers with their own point of profits ,then it can bring a new revolution in the market where there will be different layers will be available with separate user friendly graphic user interface for all wholesalers, retailers and customers, where they will be allowed to access their own layers accordingly with several unique features and benefits to save time and making shopping more amazing for customers and selling their products and boosting daily sales for the retailers with the influence of top wholesalers available to help them with the unique kind of trading system and daily analytics and progress report using data science.

Keyphrases: Augmented Reality, e-commerce, image recognition, machine learning, QR code, Virtual Reality

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:10674,
  author = {J Jesy Janet Kumari and Aniket Singh and R. Ch. A. Naidu and M Sathya and Ramya M Sri},
  title = {An Empirical Study on E-Commerce Site Using Unique AI Based Features and Data Science Tools},
  howpublished = {EasyChair Preprint no. 10674},

  year = {EasyChair, 2023}}
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