Frank & Oak is making its online style advisor service more interactive, with a new option to have a stylist create and send a personalized basket of items for the shopper to try on.
The new service, called Select, is available to Frank & Oak Hunt Club members and visitors to its physical locations in Toronto and Montreal. Shoppers fill out a quick style profile and tell the advisor what specifically they’re looking for — whether they’re going to a wedding or they just want a comfortable pair of jeans. The advisor sends them an item or several that might suit their tastes, and if they don’t like it, they can send it back at no charge.
“We realize that especially when it comes to a young male customer, it’s not just the product, it’s how to get a better product, how do I find a product that’s more appropriate for me,” said Frank & Oak co-founder Ethan Song.
Select emulates personal stylist services available at high-end couture shops like Holt Renfrew, which Song said could be intimidating — and expensive — for young people.
“We wanted to make it more casual, and more on-demand, so if you don’t want it you can just shop naturally,” he said. “We’ve taken a concept that really makes sense, but made it a little simpler and more technologically driven for this generation of customers.”
Frank & Oak’s style advisors have always been a big part of its e-commerce formula. Anyone who visits the site has to make a profile, and once they do they’re assigned one of 12 advisors based on whether they’re looking for “preppy,” “classic” or “creative” looks. The shopper chats with the advisor while they shop, which Song said quickly became an avenue for shoppers to request recommendations. The Select service just formalized the process.
But unlike traditional salespeople, Frank & Oak’s advisors have a lot more data on what their customers are looking for. Song said before the stylist makes a selection, the inventory they can choose from is automatically narrowed down based on the shopper’s profile, plus data about their past purchases — and anything they’ve sent back from a previous Select request.
Ultimately though, the decision needs to be made by a human. Only a human can move beyond the data to figure out what’s actually important to the customer. “Just a digital recommendation was not enough — we needed to have an intuitive aspect,” he said. Once the decision of which product to recommend to the customer has been made, that final touch where I say, ‘I think this product is great for you because you told me you work in a casual environment,’ that makes it more powerful.”
