Dynamic Yield by Mastercard has launched Shopping Muse, a generative AI tool poised to redefine how consumers explore and discover products within a retailer’s digital catalog.
This innovative tool aims to replicate the in-store shopping experience by interpreting consumer colloquial language into personalized product recommendations, inclusive of suggestions for complementary products and accessories.
Shopping Muse sets itself apart by accommodating modern aesthetics, trending looks, dress codes, and unconventional search terms like ‘cottagecore’ or ‘beach formal.’
According to the company, the tool’s recommendations are curated to match an individual’s profile, intent, and preferences. Moreover, it evolves with the conversation’s context over time, ensuring even the most unique queries receive perfectly tailored results.
Powered by Dynamic Yield’s personalization capabilities, Shopping Muse amalgamates contextual and behavioral insights to craft recommendations based on retailer keywords, visual cues, and consumer affinities.
Apart from assisting shoppers with phrase-based searches, Shopping Muse aids consumers in discovering products they might struggle to describe verbally.
Leveraging advanced image recognition tools, the tool suggests relevant products based on visual similarities, even without specific technical tags. It also accounts for the shopper’s preferences and past browsing history to predict future buying intent, ensuring recommended items complement rather than duplicate each other.
Amazon Launches Amazon Q
On another note, Amazon has also introduced Amazon Q, an innovative generative AI-powered assistant tailored explicitly for business applications.
As part of Amazon’s broader strategy to integrate generative AI across its consumer and private sector product spectrum, Amazon Q is designed to cater to an array of business requirements, offering a diverse suite of capabilities aimed at empowering employees.
The announcement heralds Amazon Q as an instant source of relevant information and guidance for employees, streamlining tasks, expediting decision-making, nurturing creativity, and fostering problem-solving within the workplace.
The AI assistant facilitates interactive conversations, problem resolution, content creation, insights generation, and easy action-taking by connecting to a company’s information repositories, code, data, and enterprise systems.
Amazon Q’s versatility extends to a myriad of functionalities, from aiding app development, bug fixing, and code analysis to content creation for social media, generating business-related stories and speeches, crafting unified customer profiles, and curating structured data for high-quality reports.
What sets Amazon Q apart in the business market is its personalized responses, which adapt to individual user identity, role, and permissions—a distinct feature directly competing against OpenAI’s recently unveiled “GPTs.”
It is worth noting that this move by Amazon follows a significant investment in Anthropic, an AI firm renowned for its Claude 2 chatbot.
Amazon’s substantial financial commitment not only provides Anthropic access to Amazon Web Services’ computational prowess but also positions Amazon as a contender in the AI landscape, challenging major players like Microsoft, Meta, Google, and Nvidia.
Additionally, Amazon’s plans to revamp its Alexa ecosystem, leveraging its AI and Large Language Models (LLMs), are aimed at enhancing Alexa’s capabilities, facilitating more natural voice interactions and smarter home functions.
As retailers navigate rapidly evolving trends and deep learning algorithms, adopting technology becomes essential to meeting heightened consumer expectations. In fact, more than a quarter of retailers currently utilize generative AI solutions, with an additional thirteen percent planning adoption within the coming year.