Abstract
The E-Commerce industry is facing a big challenge of handling huge amounts of data and profiting from it by analysing the data. This is caused by the Information Revolution. Big Data Analytics (BDA) are techniques used in order to manage and study this pile of data, which comprises of text messages, social media comments etc. In addition to this, Big Data Analytics can be used in the e-commerce sector to get increased revenues and draw in more customers. This project focuses on analysing and implementing these functionalities of BDA in e-commerce for the benefit of both, the seller and the consumer. E-commerce vendors as well as other enterprises such are general stores, malls etc use BDA techniques to get the competitive advantage by understanding consumer behavioural patterns. These patterns are then studies and used to achieve consumer loyalty and thus getting higher revenues through their businesses. Plus, the recommendation systems that are obtained through big data analytics help the customers shop better due to a personalized and tailor-made searching experience. A business can experience tremendous growth if the customers and the customer reviews/patterns of the business are studied properly. The knowledge gained from this can be put to tackle the negatives about the business. Our project is based into two modules, Customer Segmentation and Sentimental Analysis. The project studies customers using the customer segmentation module. In Customer Segmentation, K-Means Algorithm is used to make clusters of customers based on their age, spending patterns etc. The second module is Sentimental Analysis which focuses on divide the positive reviews with the negative reviews. The business can then work upon tackling the negatives that the consumer thinks the business has.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have