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Related Experiment Video

Updated: Jan 30, 2026

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Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application.

Onur Dogan1, Jose-Luis Bayo-Monton2, Carlos Fernandez-Llatas3

  • 1Department of Industrial Engineering, Istanbul Technical University, Istanbul 34367, Turkey. odogan@itu.edu.tr.

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Summary

Customer path analysis using Bluetooth technology reveals distinct male and female shopping behaviors. Process mining effectively visualizes these differences in mall navigation and dwell times.

Keywords:
Bluetoothgender behaviorindoor locationsprocess miningshopping mall

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Area of Science:

  • Consumer behavior analysis
  • Data mining and analytics
  • Spatial analysis

Background:

  • Understanding customer movement within retail environments is crucial for optimizing store layout and marketing strategies.
  • Traditional methods often lack the granularity to capture detailed spatiotemporal customer journeys.
  • Bluetooth-based positioning systems offer a novel approach to collect high-resolution movement data.

Purpose of the Study:

  • To analyze customer paths in a shopping mall using Bluetooth technology.
  • To investigate gender-based differences in customer behavior and movement patterns.
  • To evaluate the effectiveness of process mining for analyzing customer journey data.

Main Methods:

  • Deployment of iBeacon devices for Bluetooth-based positioning within a shopping mall.
  • Collection of spatiotemporal data for approximately 8000 customers over three months (December 2017 - February 2018).
  • Application of process mining techniques to analyze event logs and visualize customer paths, inferring gender based on restroom usage.

Main Results:

  • Significant differences observed in the paths and duration of male versus female customers.
  • Customer journeys, including dwell times and movement patterns, are not similar across genders.
  • Process mining provides a clear and understandable visualization of complex customer behaviors.

Conclusions:

  • Bluetooth-based technology combined with process mining is a viable method for detailed customer behavior analysis.
  • Gender is a significant factor influencing customer navigation and behavior within a shopping mall.
  • The findings offer valuable insights for retailers seeking to personalize customer experiences.