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We propose a machine learning based methodology to deal with data collected from a mobile application asking users their opinion regarding fashion products. Based on different machine learning techniques, the proposed approach relies on the data value chain principle to enrich data into knowledge, insights and learning experience.

Online interaction and the usage of social media have dramatically altered both consumers’ behaviors and business practices. Companies invest in social media platforms and digital marketing in order to increase their brand awareness and boost their sales. Especially for fashion retailers, understanding consumers’ behavior before launching a new collection is crucial to reduce overstock situations. In this study, we aim at providing retailers better understand consumers’ different assessments of newly introduced products.

By creating new product-related and user-related attributes, the proposed prediction model attends an average of 70.15% accuracy when evaluating the potential success of new future products during the design process of the collection. Results showed that by harnessing artificial intelligence techniques, along with social media data and mobile apps, new ways of interacting with clients and understanding their preferences are established.

From a practical point of view, the proposed approach helps businesses better target their marketing campaigns, localize their potential clients and adjust manufactured quantities.

The originality of the proposed approach lies in (1) the implementation of the data value chain principle to enhance the information of raw data collected from mobile apps and improve the prediction model performances, and (2) the combination consumer and product attributes to provide an accurate prediction of new fashion, products.

The increased importance of sports and athlete brands highlights the need for athletes to pay attention to branding as it has positive impacts. As athletes, Muslim women have not succeeded in building their brands. This study aims to understand the branding challenges facing Muslim female athletes and how to overcome them.

These branding obstacles and guidelines were explored using qualitative methods – specifically semi-structured interviews with Muslim female athletes and focus groups with experts. Data were analysed using open and axial coding to identify the codes.

The study identifies three major obstacles to branding by Muslim female athletes. Self-related obstacles, such as knowledge of brand building, social media, personal pressure and a lack of role models, impact the brand-building decision. Social-related (family and society) and sport-related obstacles (participation as women and as Muslims) further complicate this task. Experts provide additional insights regarding these obstacles, suggesting strategies to overcome them.

The research focuses on athletes from one geographical area and has limitations associated with using qualitative methods.

The study suggests how self-, social- and sport-related obstacles are faced by athletes. It provides suggestions for federations, sports codes and other stakeholders to support athletes to overcome these barriers.

This study expands the understanding of the struggles Muslim women face in building their brands as part of an under-represented group.