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Leveraging Big Data and IOT for Retail


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

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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Abstract Views: 344

PDF Views: 177




  • Leveraging Big Data and IOT for Retail

Abstract Views: 344  |  PDF Views: 177

Authors

A. Vintha Rao
RMD Engineering College, Kavarapettai, Gummidipoondi, Tamilnadu, India
P. Shalini
Vels University, Chennai, India

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.