Mastercard Unveils Generative AI Retail Tool Shopping Muse
Mastercard has introduced a new generative AI commerce tool named Shopping Muse, created under its Dynamic Yield subsidiary. Shopping Muse is designed to mimic the human experience in retail by understanding and responding to consumers’ colloquial language, thus offering tailored product recommendations and suggestions for coordinating items.
Shopping Muse
Generative AI commerce tools are beginning to proliferate, with major brands like Walmart, Shopify, and Newegg all incorporating the technology in various ways. Mastercard hopes to make Shopping Muse stand out with its ability to interpret modern aesthetics and trending styles, even accommodating unconventional search terms like ‘cottagecore’ or ‘beach formal.’ The tool is designed to adapt to an individual consumer’s unique profile, intentions, and preferences, refining its suggestions over time to align perfectly with the user’s requirements.
The solution’s underlying technology leverages Dynamic Yield’s expertise in deep personalization, combining contextual and behavioral insights. This approach ensures that recommendations are not only relevant but also aligned with the retailer’s keywords and visual cues, as well as the consumer’s personal affinity.
“Solutions like Shopping Muse are the next natural step in the retail revolution and are core to putting the consumer back at the center of the journey,” Mastercard president of data and services Raj Seshadri explained in a statement. “At Mastercard, we’re putting technology and machine learning to work to deliver better outcomes for both brand and consumer.”
Shopping Muse also tries to address a common online shopping challenge: finding the right product when the consumer cannot precisely describe it. The tool integrates advanced image recognition capabilities, allowing retailers to suggest products based on visual similarities, even in the absence of accurate technical tags. This feature, coupled with an understanding of the shopper’s past behaviors and purchases, aims to predict future buying intentions more accurately, ensuring that suggestions are complementary and relevant.
In addition to helping shoppers search by phrase, Shopping Muse can reduce frustration by helping consumers find the perfect item even when they don’t know how to properly describe it in words. Using integrated advanced image recognition tools, retailers can recommend relevant products based on visual similarities to others, even if they lack the right technical tags. The tool also takes into account the shopper’s affinity, based on session browsing history or past purchases, to better estimate future buying intent. With an understanding of the consumer’s affinity and the context of broader collective behavior, the retailer can ensure the suggested items are complementary, not redundant.
“Personalization gives people the shopping experiences they want, and AI-driven innovation is the key to unlocking immersive and tailored online shopping,” said Dynamic Yield by Mastercard CEO Ori Bauer. “By harnessing the power of generative AI in Shopping Muse, we’re meeting the consumer’s standards and making shopping smarter and more seamless than ever.”
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