Vufind offers two solutions:
a) Visual Recommendations: Vufind's patented computer vision engine pre-processes your catalogs to deliver amazing visual-similarity recommendations that boost engagement/CTR and conversion lift. For logged-in users, we offer combined visual+behavioral recommendations.
b) Image Recognition for mobile and cross-channel commerce: Integrate Vufind's mobile SDK into your app. Shoppers snap photos of products they like, and Vufind Recognizes the objects and refers aspiring shoppers to your product page, enabling "showrooming" and cross-channel smarter commerce.
Vufind offers an awesome solution for inspiring shoppers to create ensembles and quickly discovering items
that give their look extra oomph. vuStyle is your AI style assistant that uses visual intelligence to match design style across categories offering "complete the look" recommendations. For example matching a dress's design style and cut with a handbag, cardigan,
heels, or even sun-glasses taking into account numerous parameters to help shoppers get the look they'd love.
vuGraph: Personalized Commerce
Whether you've added social login or you'd like to mine native user activities, vuGraph personalization would boost your conversion. When a shopper interacts with your app/site, every user action and every datatype signifies persona attributes and informs likely intent. Vufind crunches these signals, including visual analytics, into predictive models to power immersive ecommerce experiences that delight shoppers and maximizes conversion.
vuPredict: Predictive Analytics
Build predictive intelligence, contextual and temporal relevance into your ecommerce experience.
Vufind analyzes aggregate profiles, product correlations, and weekly shopping trends, to deliver actionable insights that would inform your merchandizing decisions, product catalog image mix, brands, promotions, and real-time recommendations.
Join the aiCommerce Revolution!
eTail enterprise customers and developers use Vufind's APIs to get personalized behavioral recommendations, visual-similarity recommendations, likely intent scores, and a host of other combined contextual-behavioral analytics.