In Brief

Whether designing a personal wardrobe or pairing previously purchased pieces together to form a stylish ensemble, brands are using AI-enabled technology to provide their customers with personalized shopping and styling

Retailers like Amazon, Farfetch and Perry Ellis are leveraging mobile and artificial intelligence to deliver custom shopping and styling experiences as well as tailored product recommendations to core consumers as they move between in-store and online purchasing channels.

In particular, retailers are aggregating customers’ purchase data to help them manage their wardrobes and inspire potential outfits. Here’s how five brands are providing their customers with seamless shopping experience:

Farfetch
Online fashion retailer Farfetch’s “Store of the Future” OS captures customers’ online and offline data to elevate the shopping experience and facilitate the creation of wishlists. The operating system detects what a shopper is eyeing in store and automatically populates an online wishlist, which shoppers can then view through a digital dressing room mirror and their mobile devices.

Hanger
Hanger is a personal wardrobe app that lets customers create outfits and share them with friends. Users upload photos of their clothes or search Hanger’s digital catalogue to populate their Hanger virtual wardrobes. They can then connect with friends to see their wardrobes, creating outfits for themselves and friends using the real clothes from any of their connected closets. The app also allows users to plan their wardrobes for the week and organize their closets with tags like season, weather, pattern, fabric and more.

Perry Ellis
Menswear retailer Perry Ellis developed a skill for Amazon’s Alexa that provides men with outfit suggestions based on specific situations or occasions, such as a beach wedding or job interview. The Ask Perry Ellis style recommendations are drawn from the retailer’s own catalogue of clothing, which can be purchased through Alexa as well. Perry Ellis says that the skill has given them a better gauge of their consumer’s needs. Wedding style advice has been the most popular category, with 38% of users requesting it.

Finery
Finery is a personal wardrobe app that helps users organize and style their wardrobes. It scans users’ email accounts for shopping receipts in order to automatically populate their wardrobes on the Finery app. The app then allows users to virtually plan outfits, sharing styling ideas and wishlist picks to help users fill in any gaps in their wardrobes.

Amazon Echo Look
Amazon Echo Look, the hands-free camera and style assistant from e-commerce giant Amazon, analyzes users’ clothing style and uses machine learning to make outfit recommendations. Users can take head-to-toe photos or short videos of their outfits in order to see a 360-degree view of their outfit. They can then use the app to create a personal lookbook, browse outfits and see personalized styling ideas. Using the Style Check feature, users can submit two photos of different outfits to get a second opinion on which one looks better and why, based on fit, color, styling and current fashion trends. Through user feedback, the advice improves over time.

These are just a few ways that retailers are providing their customers with more personalized and useful assistance when it comes to shopping, styling and wardrobe organization. For more ideas, see PSFK’s report Applying Connected Technologies To Augmented Fashion.

Retailers like Amazon, Farfetch and Perry Ellis are leveraging mobile and artificial intelligence to deliver custom shopping and styling experiences as well as tailored product recommendations to core consumers as they move between in-store and online purchasing channels.

In particular, retailers are aggregating customers’ purchase data to help them manage their wardrobes and inspire potential outfits. Here’s how five brands are providing their customers with seamless shopping experience: