Patent AU-2021106426-A4 (AU)
Title: System and Method for Online Marketing recommendation using Internet of Things (IoT) sensor-based product availability in retail environment
Inventor: KULKARNI GOPAL
IPC: G06Q30/06
Filed: 2021-08-22
Granted: 2021-12-02
Abstract: System and Method for Online Marketing recommendation using Internet of 
Things (loT) sensor-based product availability in retail environment 
ABSTRACT 
The present invention relatesto a system and method for customer relationship management 
system by providing online marketing recommendation regarding product availability 
automatically using Internet of Things (loT) sensors in retail environment. The objective of 
present invention is to solve the anomalies presented in the prior art techniques and using 
advanced technique for providing product recommendation in online e-commerce space 
automatically by providing an automatic system for determining product availability in retail 
environment. In retail environment, to determine the product availability and managing the 
retails shops need with limited number of staffs or human resources, there is a need of such 
system that can determine the product availability using advanced techniques automatically 
and provide recommendation to the customers automatically to improve customer 
relationship and improving retail market performance. The disclosure presents an automatic 
online marketing product recommendation on the basis of product availability which will be 
determined using Internet of Things (loT) sensors dynamically on the basis of category of 
products customers often purchase or interested. The proposed invention is performed on 
the central server and loT sensors are installed in the retails shop orwarehouse premises. The 
RFID tags are attached with each product that are automatically read by loT sensors 
automatically and determines the product availability dynamically. The determined product 
availability along with the customer purchase history and other data are processed at the 
central server using machine learning model which automatically determines the category of 
the products in which individual customer are interested in dynamically and recommend the 
products based on the product category on the computing device of the customer on which 
the customer is crawling the products using e-commerce website or application of the retail 
shop or retail organization. The proposed invention is greatly helping the retail merchants 
running e-commerce business. Further, the proposed invention requires less staff and 
determines the product availability dynamically on regular interval basis automatically.  
Further, the proposed invention also capable of determining the product category 
recommendation using machine learning model based on customer purchase history and 
other data. The proposed process and system automate the process and greatly improves the 
business in retail environment.  
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Database (102) 
Customer 1 
Customer 2 
server (103) 
Communication 
network (101) 
Customer n 
Machine 
learning 
model 
(104) loT sensors 
installed 
(105) 
Figure 1: Block diagram of automatic system for online marketing recommendation using Internet 
of Things (loT) sensors-based products availability 
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