A Personalized Visual Aid for Selections of Appearance Building Products with Long-term Effects

It is challenging for customers to select appearance building products (e.g., skincare products, weight loss programs) that suit them personally as such products usually demonstrate efficacy only after long-term usage. Although e-retailers generally provide product descriptions or other customers' reviews, users often find it hard to relate to their own situations. In this work, we proposed a pipeline to display envisioned users' appearance after long-term use of appearance building products to deliver their efficacy on each individual visually. We selected skincare as a case and developed SkincareMirror which predicts skincare effects on users' facial images by analyzing product function labels, efficacy ratings, and skin models' images. The results of a between-subjects study (N=48) show that (1) SkincareMirror outperforms the baseline shopping site in terms of perceived usability, usefulness, user satisfaction and helps users select products faster; (2) SkincareMirror is especially effective to males and users with limited product domain knowledge.