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Related Experiment Video

Updated: Sep 28, 2025

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

Published on: July 24, 2017

Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store.

Jaikishan Khatri¹, Javier Marín-Morales¹, Masoud Moghaddasi¹

¹Instituto de Investigación e Innovación en Bioingeniería (i3B), Universitat Politécnica de Valencia, Valencia, Spain.

Frontiers in Psychology

|April 1, 2022

Summary

This summary is machine-generated.

Virtual reality (VR) technology can identify consumer personality traits through behavioral analysis in virtual stores. This research uses VR sensors to recognize personality domains, aiding in understanding purchasing behavior.

Keywords:

Big Five personality consumer behavior eye-tracking (ET)machine learning navigation statistical learning virtual reality virtual store

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Area of Science:

Consumer Behavior
Human-Computer Interaction
Psychology

Background:

Personality traits significantly influence consumer purchasing behavior.
Virtual reality (VR) offers immersive environments for studying behavior realistically.
Understanding personality in retail settings is crucial for targeted marketing and user experience.

Purpose of the Study:

To classify consumers into Big Five personality domains using behavioral data collected in a virtual shop.
To investigate the correlation between specific behaviors in VR and personality traits.
To assess the efficacy of VR hardware sensors for personality recognition.

Main Methods:

Collected behavioral data (eye-tracking, navigation, posture, interaction) from 60 participants in a virtual hypermarket.
Utilized free and directed search tasks within the virtual environment.
Employed a support vector machine (SVM) supervised machine learning algorithm for personality classification.

Main Results:

Open-mindedness was identifiable through eye gaze patterns; extraversion correlated with posture and interactions.
Conscientiousness and negative emotionality required a combination of behavioral signals for accurate classification.
Integrating all behavioral measures and tasks enhanced classification accuracy across all personality domains.

Conclusions:

Consumer personality can be recognized using behavioral sensors in commercial VR devices during virtual shopping experiences.
VR provides a viable platform for non-intrusive personality assessment in consumer research.
Behavioral biometrics in virtual environments offer new avenues for personalized marketing and retail strategies.