From Scroll To Cart: Assessing The Impact Of Algorithmic Personalization And Seamless Checkout On Unplanned Online Spending

This study evaluates the operational mechanics of digital impulse buying across modern social commerce environments. While personalized social platforms aim to enhance user experience and product discovery, consumers frequently experience psychological and environmental triggers that lead to unplanned financial expenditure. Utilizing a stratified random sampling methodology, primary data was gathered from $400$ active social media shoppers across four major platform environments (TikTok, Instagram, YouTube, and Facebook). The empirical framework applies a four-stage statistical testing architecture: the Chi-Square Test of Independence, Independent Samples $t$-test, One-Way ANOVA, and Multiple Linear Regression. The empirical results reveal substantial disparities in impulsive purchasing behavior, driven primarily by algorithmic personalization, dynamic checkout features, impulse control, and daily screen exposure. While seamless purchasing mechanisms like one-click checkout and live-stream shopping drive high conversion rates among younger, highly engaged users, digitally cautious consumers exhibit lower susceptibility due to cognitive friction and intentional delay tactics. The paper concludes with targeted self-regulation strategies and platform design recommendations aimed at moving from hyper-frictionless, impulse-driven monetization toward a balanced, intentional consumer ecosystem.