Machine Learning-based Mobile Application for Store-to-Door using Sentimental Analysis

Abstract

With the rising demand for consumer products, delivery time must be satisfactory. Due to the Internet’s efficiency and convenience, consumer items are increasingly sold online. The majority of young people prefer to buy their daily requirements online, although this has had minimal impact on sales of essential products. Many store owners who want to enter the online market are confused by the constantly evolving digital technologies. As a solution, this study intends to develop a platform for business owners to sell their goods and services to the general public directly via online. This method directly connects customers and store owners. In exchange, the store owner will receive a data feed on the items that are most commonly demanded in their community. Consumers, on the other hand, have the chance to decide which stores to visit or even having their purchases delivered. This will diminish the market dominance of e-commerce companies like Amazon and Flipkart. Also, the buyer is instantly aware of how simple it is to obtain the goods.