Open AccessRestaurant Success Rate Prediction
Author(s) -
Apoorva Shete
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.37257
Subject(s) - competition (biology) , marketing , scope (computer science) , business , quality (philosophy) , advertising , online business , computer science , the internet , world wide web , ecology , philosophy , epistemology , biology , programming language
Online reviews are becoming more and more vital when it comes to decision making of the consumer. Every business wants to succeed in the present and the upcoming future, thus good online reviews help the business grow. Especially in a restaurant business, its rating holds an important indicator to whether the restaurant is any good or not. It not only helps us understand the quality and services but also attracts more customers. Ordinarily a new restaurant owner would have to invest time in building a menu, setting the correct price range and making something unique to scope out their competition as well as improve their ratings on online services such as Zomato. Thus, this paper attempts to ease the efforts of new restaurant owners by predicting the success rate of a restaurant on the Zomato app.