As living proof of our purpose at The Greenhouse, Intelistyle unleashed their collective brilliance by collaborating with multiple startups and brands. They worked with Shopi – a clienteling startup from our FW18 – to provide a solution for D&G; Nobal by iMirror for Tryano; and built a curated solution for Wear That, an Ibtikar project.
We sat with Kostas Koukoravas (Intelistyle), Asli Kubilay (Shopi), Rema Nelson (D&G), Jonathan Guiffant (Tryano) and Heidi Armstrong (Wear That) to hear about the work they’ve done in just 3 months.
Kostas (Intelistyle): Intelistyle provides AI-styling solutions to fashion retailers by offering customers styling advice online and in-store. The solution allows retailers to scale their human styling services, and create personal online or in store experiences, at a fraction of the cost.
Our AI works with user generated photography, constantly learning from the latest trends, then tailors recommendations to each user’s body type and personal style – offering a personalized omnichannel experience. It will make the same choices as a human stylist more than 9 out of 10 times.
GH: Asli what are the use cases you developed for D&G?
Asli (Shopi): With the visionary approach of both Rema (D&G) and Dina Sidani (The Greenhouse), we collaborated with Intelistyle to enrich the product information catalog and enhance the customer experience; so sales associates can recommend alternative products with the help of Intelistyle’s AI.
GH: Rema tell us about the pain points you were looking to solve.
Rema (D&G): With Shopi’s clienteling solution, we were able to empower our front-liners with tools to elevate their work to the level of our top performers. Shopi & Intelistyle’s solution proved to be a good bridge before going online – giving customers access to our full catalog to browse on the shop floor.
Kostas: This is a good example of how we use AI to empower people as opposed to replace them. Eventually we will be able to use AI to consider what each customer bought previously and understand their style from that.
GH: Jonathan what are the pain points you were looking to solve?
Jonathan (Tryano): Our store is very large, and almost impossible to see all there is. So as part of the journey, we wanted to find a way to offer guests similar products to what they were either looking at or had tried. Rather than showing staff-made styles, Intelistyle provided styles using AI – with potential to save shop-floor time and increased accuracy.
GH: Kostas tell us about the use cases you developed for Tryano.
Kostas: For Tryano, we focused on both online and offline experiences. Online we show outfits for every single item on the website; and in-store, we provide similar experience to Dolce & Gabbana, and also allow staff to filter the store’s inventory depending on the user’s body type, skin tone and hair tone and occasion. Front-liners can provide an experience that a stylist would. Additionally, following customers on multiple touch-points, we can track the same customer across two different platforms and understand who they are and what they like.
GH: Heidi, tell us about Wear That and what pain point you were looking to solve.
Heidi (Wear That): Wear That is online styling platform that uses data to create looks based on your body shape, mood and occasion. Once a customer fills out a survey, stylists put together a curated box of clothes and deliver it to customers, they try and buy what they like, and return what they don't like.
When working with Intelistyle, we focused on the part of the process that would have the most impact on operational efficiency. We pulled feeds from different retailers, allowing our stylists to filter stock by attributes depending on each customer’s profile. This solution will reduce stylists’ time in putting the looks together, while also improving accuracy of boxes.
This is only the beginning of many impactful relationships between brands and startups – the results of the work are yet to be defined, but early indicators of success are already unraveling.