Quantitative Analysis of Consumer Perception on E-commerce Platforms: The Modulating Role of Age and Perceived Ethnography

This study assesses the predictive capability of 27 Customer Experience (CX) factors on Age and the influence of Skin Tone (as an ethnographic proxy) on the valuation of these factors in e-commerce. A cross-sectional quantitative design was utilized with a sample of N=1425 experienced online consumers. The methodology employed Analysis of Variance (ANOVA) (Fisher, 1925) to validate sample independence by Age, Chi-square Test (χ2) (Snedecor & Cochran, 1989) to assess ethnographic dependence, and Multiple Linear Regression (MLR) (Cohen et al., 2003) to model Age prediction. MLR results indicated that the Age prediction model was significant (R2 Adjusted=0.154), confirming that User Experience (UX) and Live Chat Availability are inverse and direct predictors of Age, respectively. Ethnographic analysis using segregated heatmaps revealed a focalized and significant disparity based on Skin Tone in the Trust/Logistics and Brand/Support blocks. A trend of lower valuation was observed in darker skin tones (Tone 6) for factors like Price Transparency and Assisted Support (Live Chat Availability), while a higher demand was noted for Review and Rating Availability. It is concluded that CX personalization must transcend basic demographics, focusing on relational equity and risk mitigation for ethnographically vulnerable segments. Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1275Dimensions.Open Alex.