Boston, MA, October 24, 2007 --(PR.com
)-- StylePath.com today launched the first website that finds products for shoppers by learning their individual taste. StylePath’s patented technology simplifies online shopping by offering personalized product recommendations tailored to each user’s unique style profile.
StylePath features style-driven items that are difficult to search for online. StylePath’s CEO, David Hornstein, explains “Online search is fine for items like electronics or books, but does a poor job finding visually-determined products. We solve this problem by matching a shopper’s mental image of what they are looking for with actual products online. In this way, shoppers can search thousands of sites with one click and only see products they like.” The StylePath collection includes home décor, lighting, kitchen/bath fixtures, rugs, jewelry, watches, shoes and handbags. The site will soon add apparel, art and textiles.
StylePath’s key features include:
• Image-based search that displays product results customized to each user’s taste
• Artificial Intelligence that learns users’ aesthetic preferences to optimize product recommendations
• One-Stop comparison shopping from thousands of popular sites
• StyleSpace – The first style-based social network connecting users with similar taste to share ideas and discuss products
• 3D Decorator – An interactive application that allows shoppers to redecorate virtual rooms to help visualize products in their own homes
How it works:
Visit stylepath.com, choose a product category, and create a style profile by quickly rating a few test images. StylePath’s patented technology finds aesthetic patterns in your profile that match products with similar attributes from thousands of websites. Use the “more similar products” feature to both zero in on what you’re looking for and improve future searches by teaching the algorithm more about your style.
StylePath is a Boston-based personalized shopping website founded by architect David Hornstein. It is the only website that learns individual users’ sense of style to offer them better product matches. Hornstein initially developed the idea to gain a deeper understanding of his clients' aesthetic sensibilities. Through collaboration with double-PhD professor Dr. Dan Ariely from MIT, the artificial intelligence-based concept evolved into a way to leverage the web’s vast selection to match each individual’s taste. Hornstein received patent #7,228,283 for his invention, with two other patents pending. StylePath was selected as a semi-finalist in the TechCrunch40 “hottest new startup” competition.
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