I recently attended Shop.org and heard Brian Spaly, speak about his company Trunk Club. I was impressed by his service and the obvious need he is filling for his customers but was left wondering how he can reasonably scale his service without hiring hundreds of stylists.
Ideally, Trunk Club Stylists should be able to enter information and feedback about products from their clients into a system that is used by all of the stylists. For example, the sleeves on this shirt run long, these jeans are tight in the legs etc. Other types of information that might be relevant could be regional preferences, popular outfits or unexpected combinations, returns and repeat purchases in multiple colors. With this information, a machine learning based personalization system can do some of the work for the stylist such as proposing items for a client based on his size, location, time of year, previous preferences and returns and building out 80% of the trunk. The combination of stylist insight and sophisticated modeling will systematically learn over time and will provide more and more valuable suggestions. The stylist could just add the final personal touch and focus her energy on clients that are willing to buy more expensive clothes or spend money on personal service.
Personalized E-Commerce is Now
The exciting thing is that we, as a personalization vendor, are moving in this direction with the platforms and the solutions we are building. With the sophisticated models we are building, it won’t be long before all consumers feel like they have a personal shopper hand-selecting items just for them.