AnalyzingIn-store Shopping Paths from Indirect Observation with RFIDTags Communication Data

This paper presents in-store customer behavioral model gathered from RFID (RadioFrequency Identification) tags communication data. Although this kind of research has beenmade by various methods such as interviewing or tracking behind customers, Conventionalresearch methods are made by with the existence of customer tracking research, so far. Forcollection of natural customer behavior, we made a customer in-store behavior research withRFID tags in a real retail store. In a conventional store design theory, it has been thought thatincreasing the length of staying time can raise the amount of money per person. Therefore,the store has been designed in the form that goes inside of a shop around. The experimentalresults suggest that there is a correlation between the spent of time and the length of customerwalking path.

[1]  Takao Terano,et al.  How Do Customers Move in a Supermarket? : Analysis by Real Observation and Agent Simulation , 2010 .

[2]  Hiroshi Sato,et al.  A Method to Translate Customers’ Actions in Store into the Answers of Questionnaire for Conjoint Analysis , 2009 .

[3]  Masakazu Takahashi,et al.  Building Knowledge for Prevention of Forgetting Purchase Based on Customer Behavior in a Store , 2011, KES.

[4]  Rebecca Angeles,et al.  Rfid Technologies: Supply-Chain Applications and Implementation Issues , 2004, Inf. Syst. Manag..

[5]  Katsutoshi Yada,et al.  Consumer Behavior Analysis by Graph Mining Technique , 2006, KES.

[6]  Komuro Nobuyoshi,et al.  Indoor Location Estimation using UHF band RFID , 2007 .

[7]  Takao Terano,et al.  Extracting the Potential Sales Items from the Trend Leaders with the ID-POS Data , 2009, KES.

[8]  Takao Terano,et al.  Generating Dual-Directed Recommendation Information from Point-of-Sales Data of a Supermarket , 2008, KES.

[9]  Hiroshi Sato,et al.  Video-Based Conjoint Analysis and Agent Based Simulation for Estimating Customer's Behavior , 2007, IDEAL.

[10]  Peter S. Fader,et al.  An Exploratory Look at Supermarket Shopping Paths , 2005 .

[11]  Takao Terano,et al.  Agent-Based In-Store Simulator for Analyzing Customer Behaviors in a Super-Market , 2009, KES.

[12]  John D. C. Little,et al.  A Logit Model of Brand Choice Calibrated on Scanner Data , 2011, Mark. Sci..

[13]  Sunil Gupta.  Impact of Sales Promotions on when, what, and how Much to Buy , 1988 .

[14]  Katsutoshi Yada,et al.  Is this brand ephemeral? A multivariate tree-based decision analysis of new product sustainability , 2007, Decis. Support Syst..