With summer adventures and wedding season on the horizon, Michael Kors’ Shopping Muse integration comes at just the right time. Shopping Muse recreates the in-store experience by translating consumers’ colloquial language into tailored product recommendations, meaning fashionable consumers can quickly find the perfect look that matches their inquiry as well as their demonstrated behavior and preferences. This type of personalized approach can boost shopper satisfaction and increase revenue; in initial tests, Shopping Muse generated around a 15-20% higher conversion rate than traditional search queries.
Dynamic Yield CEO Ori Bauer adds, “As a trailblazer in ready-to-wear fashion, Michael Kors is a perfect example of how to put our ready-to-use technology to use. Shopping Muse is helping translate the signature Michael Kors service to the digital world, delivering a satisfying shopping experience as singular and impactful as the brand’s aesthetic.”
Michael Kors is the first to adopt Shopping Muse, an AI retail assistant from Dynamic Yield, a Mastercard company, enhancing its US website shopping experience.
The tool translates colloquial consumer language into tailored recommendations, boosting conversion rates by 15-20 per cent.
This launch aligns perfectly with the summer and wedding season.
Following its launch in late 2023, early access to Shopping Muse was extended to fashion retailers, including Michael Kors. Shopping Muse is now also available to furniture retailers, soon making the shopping experience smarter and more seamless for an expanding range of customers. Mastercard embeds best-in-class privacy safeguards into all of its products and services, adhering to a robust Privacy by Design framework while applying effective and responsible AI principles and standards. This commitment ensures that Shopping Muse enhances the shopping experience with the highest level of privacy and security for consumers.
Note: The content of this press release has not been edited by Fibre2Fashion staff.
Fibre2Fashion News Desk (RM)