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2023-12-05 8:16 AM

Mastercard’s Shopping Muse: AI Revolutionizing Personalized Shopping in Trendy Style

  • Shopping Muse Unveiled: Mastercard launches AI tool for personalized shopping recommendations, understanding colloquial language, and modern trends.
  • Contextual Personalization: The tool analyzes user behavior, past purchases, and real-time preferences, transforming online shopping with tailored suggestions.
  • Beyond Fashion: Shopping Muse's image recognition extends beyond fashion, envisioning applications in furniture and groceries, reshaping the online retail landscape.
By Lethabo Ntsoane

In a move set to revolutionize the online shopping landscape, Mastercard has launched a groundbreaking generative AI shopping tool named “Shopping Muse.” The tool, powered by personalization company Dynamic Yield, promises to deliver highly personalized product recommendations based on users’ colloquial language and preferences.

Tailored Recommendations in Colloquial Language

Shopping Muse is designed to interpret colloquial language, enabling users to receive personalized product recommendations effortlessly. The tool can understand and respond to modern trends and phrases such as “cottagecore” or “beach formal.” Users can ask questions like “What should I wear for a summer wedding?” or request recommendations for a minimalist capsule wardrobe.

Contextual Understanding for Personalization

To provide tailored suggestions, Shopping Muse considers various factors, including the context of the user’s shopping experience, direct questions asked, and the content of the conversation. Algorithms analyze data from the retailer’s product catalog, on-site behavior, and real-time preferences demonstrated by the user. For logged-in users, past purchase and browsing history are also taken into account.

User-Driven Personalization

If a user is logged in, the algorithms may consider their past purchase and browsing history with that retailer, including any purchases made in-person that they connected to their account by providing the cashier their phone number or email, for example.

Beyond Fashion: Extending into Other Categories

While fashion is the initial focus, Mastercard envisions the technology expanding into other categories, such as furniture and groceries. The tool’s ability to use integrated advanced image recognition tools allows retailers to recommend relevant products based on visual similarities, even without the right technical tags.

Industry Trends: Generative AI on the Rise

Mastercard emphasizes the need for retailers to adapt to changing demands by embracing technology. The company notes that more than one in four retailers already use generative AI solutions, with another 13% planning to adopt them in the next year. This aligns with a recent report from Gartner, predicting that 80% of customer service and support organizations will apply generative AI technology in some form by 2025.

The Broader Trend: Rise of Generative AI Shopping Tools

Shopping Muse joins a growing list of generative AI shopping tools introduced in the past year. Notably, Google enables users to receive AI-generated gift recommendations on Search, while Microsoft’s Bing can automatically generate buying guides based on user queries.

Future Outlook

“Personalization gives people the shopping experiences they want, and AI-driven innovation is the key to unlocking immersive and tailored online shopping,” stated Ori Bauer, the CEO of Dynamic Yield by Mastercard. As generative AI technology continues to advance, we can expect more tools like Shopping Muse to redefine the online shopping landscape.

Mastercard’s Shopping Muse stands as a testament to the evolving nature of online retail, offering a glimpse into the future where personalized and seamless shopping experiences are driven by artificial intelligence. As South African retailers look to stay ahead in the digital age, embracing such innovative solutions could become a key differentiator in meeting the evolving expectations of online shoppers.

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Lethabo Ntsoane

Lethabo Ntsoane holds a Bachelors Degree in Accounting from the University of South Africa. He is a Financial Product commentator at Rateweb. He is an expect financial product analyst with years of experience in reviewing products and offering commentary. Lethabo majors in financial news, reviews and financial tips. He can be contacted: Email: lethabo@rateweb.co.za Twitter: @NtsoaneLethabo