INSTAGRAM FILTERS FOR THE FASHION INDUSTRY : THE MEDIATING ROLE OF PURCHASE INTENTION ON CUSTOMER ENGAGEMENT

Abstract

The COVID-19 pandemic has significantly transformed consumer behavior, shifting towards online shopping. This transformation has limited consumers’ ability to physically try on products. This study aims to determine the extent to which Instagram filters, specifically augmented reality (AR) try-on filters, influence consumer purchase intention and the level of engagement they generate among users for fashion products. Employing a quantitative approach, this research collected data from 307 active Instagram users who frequently utilize filters, using a Likert scale questionnaire (1-5). The variables examined include Instagram filters, customer engagement, and purchase intention. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) through WarpPLS Version 8.0. The findings reveal a significant positive influence of Instagram filters on customer engagement, mediated by purchase intention.