To unify the methodology of Virtual Fit platforms and allowing cross platform integration of 3D Body Scanning, the current Virtual Fit platforms need to be assessed in terms of their size recommendation approach and user interaction. Digital data, interactivity, and internet technology are changing the ways we interact in online shopping, with the Virtual Fit platforms having great potential to increase retail engagement and market share. This will support online purchasing activities while minimising the perceived risk in garment returns due to the poor sizing fit information. Current research has focused on the analysis of computer modelling techniques, avatars, cloth, fabric draping simulations, and customer behaviour / aesthetic impact in the online domain. From a technical perspective, these investigations offer an interesting insight, although do not address issues of implementation or customer attitude. Therefore, to judge the current and potential impact of such technologies, it is important to understand 1) how they are being enacted online, 2) the Interaction Design elements of the user journey, 3) the application (or lack thereof) of mathematical models, and 4) how such interfaces are embedded within websites. Once these four key questions have been answered a greater understanding of how 3D Body Scanning and Technologies integrated into eCommerce and Virtual Fit platforms in the consumer market may be reached. Through analysis of nine leading Virtual Fit platforms, the persona of a single female dress form was used to work through the customer journey. Through this, screen shot data captured along each stage in relation to the four research questions listed above. Following this, the study utilised content analysis structure with NVivo as a qualitative thematic analysis tool. This study found that despite a large number of platforms using virtual fit technology, only a handful companies exist that provide such technology and interfaces; often based upon subjective ‘previous purchases’ rather than scientific prediction. This issue is made more complicated in how subjective measures such as personal perception of one’s body is required (e.g. what size are you), besides body shape; a concept shown to be ‘broken’ and not fit-for-purpose. In addition, many of the technologies use limited and often misinterpreted body measurements, the impact of which is explored in greater detail within the paper. This study contributes to the understanding of the information required from users by virtual fit platforms, and the understanding of the output as presented by virtual fit platforms. The research goal is to contribute to knowledge as a potential guideline for any future projects in virtual fit and to help direct body scanning developments to better support these platforms
