1000/1000
Hot
Most Recent
Analyzing customer shopping habits in physical stores is crucial for enhancing the retailer–customer relationship and increasing business revenue. Radio-Frequency Identification (RFID) technology has emerged as a solution and has been implemented in physical stores for purposes such as smart trolleys and analyzing customer shopping paths. Additionally, previous research has demonstrated that the phase readings and received signal strength (RSS) of RFID, combined with machine-learning algorithms, can effectively track customer activity within the physical store, including product browsing. Therefore, employing machine learning models for identifying customer behavior inside the store is crucial to enhance the efficiency of customer behavior analysis.