With AI tools playing a growing role in product discovery, it makes sense for brands to explore new opportunities on this front, which can utilize the strengths of AI to enhance the shopping experience.
Which is what Ralph Lauren has done with its latest AI element, with Microsoft’s AI tools powering a new product matching tool that can help users style their looks, based on Ralph Lauren items.
As explained by Microsoft:
“Ask Ralph is a conversational AI shopping experience built on Azure OpenAI, and available in the Ralph Lauren app in the U.S. You can interact with Ask Ralph just like you would a stylist in a Ralph Lauren store by asking simple, conversational questions or using prompts to find the perfect look for any occasion.”
So if you want to know what goes best with a pair of shoes that you like, or a specific color of shirt, “Ask Ralph” will be able to give you styling notes, based on commonly purchased items, curated looks, what other people have searched for in relation to each item, etc.
Which is kind of personalized, I guess, in that it’s an open prompt, and you can direct how it finds related products. But then again, depending on exactly how it determines product matches, maybe you’ll just end up looking more like a Ralph Lauren model, as opposed to having any individual style.
Though the market demand for that would be high either way, as a lot of people simply want to look their best, and are seeking guidance on how to do that.
In terms of specifics, Microsoft doesn’t provide a heap of insight into how the system determines relevant matches, only noting that:
“Ask Ralph delivers tailored responses to a user’s prompts, curating outfits and looks from across the Polo Ralph Lauren brand, with all items suggested from available inventory. Ask Ralph can also interpret tone, satisfaction, and intent to refine recommendations dynamically. It also adapts to contextual cues like location-based insights or event-driven needs.”
So there’s not a lot of info on how, exactly, the tool decides what fits best with each other item, but presumably, it’s being guided by the factors noted above.
And again, this is what AI is good for, cross-matching large datasets to find commonalities and correlations that are beyond the capacity of other systems. The capacity to translate natural language searches into complex queries for such purpose is a huge benefit, and there are a range of ways that this could help to streamline and improve various actions that relate to such functions.
Like showing you related products based on your specific query, like giving you a full listing of products you’ll need for a specific project, matching images to items, people to process, etc.
That could be a valuable consideration for your own brand use of such, leaning into AI tools to better upsell relevant products.
