Habitual shoppers across online platforms strive to find the perfect fashion piece. These shoppers are committed to hunting down a purchase that makes them proud and confident. Yet, the continual scrolling through endless products and comparison across brands becomes exhaustive. Then truly depicting a product’s tactile feel and quality of construction is difficult on an online platform. These inhibiting factors often lead to disappointing products and wasted time, ultimately decimating the thrill of the shopping hunt.
Sift is an app and desktop plug-in that assists with the user’s hunt of finding clothing by universally filtering, using 3-Dimensional interactive models, emphasizing transparency, and saving products to organized hauls. Users can set personalized filtering preferences that Sift applies across all brands, allowing users to compare fashion items more efficiently. Plus, by mimicking an in-person clothing rack, users can swipe through an interactive 3-D view of products to assess the product’s form and quality accurately. Within the specific product pages, there are curated reviews, material comparisons, and sizing assistance for a holistic understanding of the item before saving. These ‘saves’ are orted into hauls that are organized based on user curation. The products can also be prioritized and ranked within these hauls to encourage ‘round based’ decision making. Sift is here to help users search, save, and sort, for a seamless and exciting hunt.
Silver in Apps 2021, Student
Silver in Mobile App 2021, Student
Silver in Mobile Interaction & Experience 2021, Student
Silver in Interactive Design 2021, Student
Taylor Primuth Madeline Esper Edena Alvarado Abby Turner
Savannah College of Art and Design, US
Visual Design Lead: Taylor Primuth
Research Lead: Madeline Esper
Prototyping Lead: Abby Turner