Makeup chemistries have evolved over the recent years and have become more long-wearing, waterproof and difficult to remove. Thus, many changes have occurred among products designed to remove makeup. Specifically, the facial cleansing/makeup remover wipes category is challenged to establish new strategies and adapt to the changing consumer needs and the evolving competitive landscape. A global product category review can provide the upfront understanding necessary to establish fundamental knowledge. That knowledge can in turn be leveraged when developing future products. A customized descriptive analysis method was applied to address the unique challenges of the category. The method leveraged existing methods and was augmented with new descriptive modalities, specific to the unique developments in the category. A total of seventy-one attributes were identified that spanned visual and tactile cues of the wipes, cleansing performance cues during use, as well as skin look and feel attributes after use. Thirteen facial cleansing/makeup remover wipes from global markets were selected for testing based on commercial and historical insights. Three sensorial perceptual maps were generated displaying the profiles of the thirteen products in three areas of product properties—visual and tactile, cleaning performance, and skin look and feel. These study results combined with existing consumer insights helped the R&D team to establish strategies to guide product development for this category.

To stay ahead of the competition companies often look at the product category for optimization. A consumer design of experiments study was conducted with various analyses to understand the best product feature combinations for maximizing consumer acceptance and purchase intent (PI) for makeup remover wipes. A blind, sequential monadic, 6-weeks home use test with a balanced incomplete block design was conducted with 963 consumers in the United States and United Kingdom.Eighteen prototypes were selected with different combinations of four factors (formula, thickness, weight, and lotion add-on). Each participant evaluated six of the 18 prototypes. Weekly online questionnaires were used to capture questions covering overall liking (OL), PI, skin feel, texture of the fabric, and so on. A simulation model was generated to identify the best factor combination with highest PI and OL for product optimization. Driver's analysis; sensitivity analysis, a new method not often used in the sensory and consumer research; and penalty analysis provided more in-depth understanding of product performance. The learning from this study guided the product development team to determine the factor combination for the product optimization and provide direction on future planning for the category. Practical applicationsThe use of multiple analyses with studies such as a design of experiment or other category appraisal type studies can provide additional information to researchers and help to identify both those aspects that drive acceptance or purchase intent as well as those factors that could reduce consumer interest. Although the information sometimes may appear "at odds with each other," careful study often provides insights that may have been lost without the additional analyses.

Product development teams frequently develop many prototypes for screening before launching into the marketplace. Gaining customer feedback on each prototype is impossible because of constraints, such as tight timelines, budget, etc. For innovation in facial cleansing/makeup remover wipes, a design of experiments study was conducted to help the team optimize the product based on consumer feedback of prototypes. A predictive model based on consumer results and in vitro lab measurements for the makeup remover wipes was developed that could aid in future reformulation efforts of the textile base as well as the “juice” or lotion add-on. A consumer design of experiments study was conducted on 18 prototypes to help optimize the variables. Makeup remover wipe users and wipe considerers ( n = 963) from the United States and the United Kingdom participated in the study. In vitro lab measurements were also conducted on the same 18 prototypes covering relevant attributes. Partial least square regression was applied with a cross-validation procedure to build a predictive model between the in vitro and consumer research results. Scatter plots between consumer and in vitro lab results showed good directional trends between consumer perception and lab method on cleansing properties, softness, and gentleness. Model equations were developed for those measures. Future validation is needed prior to implementation. The validated model will enable use of in vitro results to predict consumer ratings for prototype screening. The predictive model can provide a quick and efficient way for facial cleansing/makeup remover wipe prototype screening, which will conserve resources and improve efficiency for the business.