A Study on the Impact of Visual Elements in Chinese Beauty Live Commerce on Consumer Purchase Decisions Based on the KANO Model

This study aims to identify how visual elements within beauty live-commerce environments influence consumers' digital brand experience and purchase decisions, and to systematically analyze their underlying structural mechanisms.Accordingly, a two-stage research path-comprising qualitative interviews, thematic analysis, and a KANO-based survey-was employed to deeply explore the mechanism by which visual stimuli affect consumer decision-making.Based on a preliminary semistructured interview, 23 key concepts were extracted, and a reverse-coded KANO questionnaire was designed.A total of 480 questionnaires were distributed between March and April 2025, of which 437 were collected and 385 were valid.Using the KANO matrix, customer satisfaction and dissatisfaction coefficients ( 𝐶𝑆 + 、 |𝐶𝑆 -| were calculated, and a three-layer weighted hierarchy of "attributescategories-elements" was constructed.The results show that the attractive/exciting type reached the highest level (𝑊 𝑂 = 0.521 , followed by the basic type (𝑊 𝑀 = 0.353 , while the indifferent type was the lowest (𝑊 𝐴 = 0.126 .Moreover, the 𝐶𝑆 + value was the highest (0.78 , indicating that the basic type was primarily associated with resolution, fluidity, segmentation, and consistency of realism.The attractive type emphasized "sense of presence" and "audiovisual immersion," while the indifferent type highlighted multi-visual realism and AR-based multi-dimensional scene inspection.These findings verify the strong logical chain of "foundation-thematic linkage-visual highlights," which enhances the continuity and interactivity of user experience.In particular, improvements in resolution and frame rate significantly increased satisfaction with the basic type, thereby raising the 𝑊 𝑂 value in the KANO matrix.Overall, this study elucidates the structural mechanism of measurable multi-visual elements and demonstrates a path of transformation from qualitative discovery to quantitative verification.