Search

The concept of hair transparency has been claimed widely in the Japan (and now it is spreading to Asian) hair color market. Despite the general use of this concept, to date, there is no clear and objective description to accurately explain what it is. In this work, we have decoded and gave clarity to the concept of hair transparency via a technical model (validated for both Japan and China markets) composed of measurable parameters of hair property using a single device.A comprehensive study composed of various tests was used, starting with a qualitative identification of key parameters via in-depth workshop discussions with over 40 Japanese stylists and a panel of 12 consumers. These identified parameters (luminosity, color visibility, and Shine) were then translated into technically measurable parameters of the hair fiber (Diffused light intensity, ratio of RGB channel intensities of Diffused light, and luster) via a single instrument-Hair SAMBA (a dual-polarized imaging system). Afterward, 10 carefully selected anchor shades were used as visual stimuli in an online pairwise comparison (PC) study with 100 Japanese stylists to generate quantitative transparency perception data of the swatches. Technical parameters of these swatches were measured by SAMBA and consolidated with the PC output, for the creation and validation of the mathematical model. After, with another PC study (N = 100) in China, with seven shades from Japan study and 6 additional Chinese market shades, the applicability of the model in China market was validated.We have clarified and quantified the concept of hair transparency through a consumer centric approach and with objective data. Our findings will enable the development of optimum transparent shades which better suits consumer needs. Lastly, we would like to highlight the beauty of digitalization in the study: The digital evaluation pathways chosen allowed us to collect quantitative consumer data from two countries for the creation of a robust model under the impact of COVID-19 and would definitely be the way to go for our future consumer evaluation studies.