Informatics Publishing Limited

A. Vintha Rao ¹, P. Shalini ²

Affiliations
1 RMD Engineering College, Kavarapettai, Gummidipoondi, Tamilnadu, IN
2 Vels University, Chennai, IN

Abstract

Objectives: To give a good shopping experience to consumers in retail outlets. This is done by using the big data that is available with us and IOT to develop a mobile application that suggests products through his mobile.

Methods/Statistical analysis: The retail outlets can use the Big Data and IOT to give a better shopping experience to customers. This on another side can improve the business of retailers by converting the footfalls into business. The data is used to suggest products in the mobile based on shopping behavior. This method is already available in E tailing.

Findings: This approach is a novel initiative here.This can help people to buy more products in a short span of time as they now have will get suggestions from the retailer about the products. This will create a competitive edge for the retailer over others. This increases the loyalty of the consumers and retention of consumers will improve.

Application/Improvements: This technique which is followed in inventory management systems can now become a mobile application and improves shoppers experience and customers loyalty of brick and motor retailers.

Keywords

Retail(Brick and Motor), Big Data, Analytics, IOT, Browsers, Consumers.

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P. Shalini ¹

Affiliations
1 VELS University, Chennai – 600117, IN

Abstract

Objectives: The paper aims to study the influences of price, store image, perceived quality, and brand association on customer satisfaction of electronic store brands. Is introducing store brand in electronic goods advantageous for the retailer? What makes the consumer to purchase a store brand? Methods/Statistical Analysis: The paper uses multivariate statistical techniques to understand the reasons behind the purchase of the store brands (both small and big appliances). This paper provides empirical insights about how the introduction of store brands is giving the retailer the competitive edge. Findings: The consumer prefers the store brand due to the store image, price, perceived quality and brand association of the retailer. Of these factors the most influential is the perceived quality. Examination of the preference of the consumer reveals that the retailer is able to retain his shoppers due to store brand. The prices have to be set carefully along with the increased perceived quality to retain them. Lately, many big retailers have added store brands in their assortment in all their product categories which is discussed in the media with their implications on the dominated channel management. Applications/Improvement: The main motivation for this research is the Neilson report on Global Private Label. This study provides a comprehensive evaluation of that trend especially with consumer durables.

Keywords

Electronic Consumer Durables, Multivariate Analysis, Perceived Quality, Store Brands, Store Image.

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