You send a stylist to measure a person to find out their exact clothing sizes, show them some different clothing styles, and then provide them with outfits that fit perfectly — they’ll be your customer for life. It sounds like a really solid business idea, right?
Actually, investors are skeptical of the stylist model in fashion– they think it’s labor intensive and not scalable. And as it turns out, the model is a lot harder to replicate for women’s fashion than for men’s.
But fashion retailer J. Hilburn is aiming to prove the skeptics wrong, doing custom clothes for men since it was founded in 2007. The company has been building on its basic proposition that by measuring each of its customers to find out their exact body size, it can then produce high-quality clothes at a lower price by cutting out the traditional department store or boutique.
And unlike other e-commerce companies, (many of which are built on that premise), J. Hilburn has such a wide range of customer data that it can use that information to make more precise bets in producing and selling merchandise — and hopefully higher profits. The company said it expects to do $55 million in sales this year, and that revenue from the first two quarters are more than 100 percent higher than the same quarters last year.
I sat down with CEO Hil Davis, who talked about how the company is using data to make these bets. The basic idea with J. Hilburn is that the company employs thousands of stylists across the country, primarily women between the ages of 35 and 55, who meet with customers, take their measurements, and then show them different items for sale (they take a commission on sales). Once a customer has his measurements on file, he can order custom-made items off the site whenever he wants, or meet with a stylist to get ideas for clothes to buy.
Davis said investors have been skeptical of the stylist model in the past, but that there’s actually a huge upside. Once the customer gets measured, they’re typically a more loyal customer, and they spend more than casual customers do at some competing brands, he said. Plus, the acquisition cost isn’t as high as you might imagine, when the average stylist has 30 customers and costs just $165 to train.
Here are three ways the company is using this customer data to its advantage:
1. Owning your customers’ data lets you manage risk
The majority of stores are limited by producing for the average person in a standard set of sizes, and they can make educated guesses about what will sell and what’s most popular. So stores are less likely to carry uncommon sizes, because you have limited floor space in a brick-and-mortar store, or a more uncertain, fickle customer base online.
But by owning all your customer’s data, you might know, for example, that one-third of your customers are really tall, so you could create a sweater with longer arms specifically to fit them, and it’s much less of a risk. You can also gauge interest through email marketing or stylist outreach before you even produce the item.
“In three years, we’ll have 50 sizes in every category,” Davis told me, which could mean dozens of different cuts for a single type of shirt.
2. Knowing what someone has purchased lets you influence what they buy
It’s one thing to know generally what your customers are buying, or which items do well, but carefully tracking every item a customer buys and analyzing their purchase patterns provides a whole new set of opportunities. Davis said the company has recently hired a data science team whose entire job is to crunch numbers and figure out patterns so the company can adjust accordingly. They’ve divided all of their customers into 22 different profiles, and know how each group will respond to specific marketing tactics.
For instance, Davis said they learned that customers who re-order an item (maybe they had a shirt custom-made, and want to order a second one) in a shorter amount of time are more likely to spend more in their lifetime with the company. So they now focus their marketing efforts on getting customers to reorder within four months, because they know that customer’s lifetime value will be two to three times higher.
And it’s not just marketing — one customer might have an entirely different experience than another based on his past habits.
“We can give one customer a different sale price than another,” Davis said. “If you’ve never bought a sport coat before, we can put it on sale just for you, whereas someone who buys them all the time might not see that.”
3. Why this works better for men than women
Why not apply the same custom-fit idea to women’s fashion, which is a much more lucrative market?
As it turns out, there are several reasons why the data-driven approach works better with men’s clothes, according to Davis. For one, the sizing tends to be more predictable in men’s clothing. A size-four dress at one women’s retailer could differ dramatically from a size four at another, but men’s clothes are sized by inseams and waistbands, which don’t change as much.
The men’s fashion space has been heating up recently. While men spend less than women do, a number of startups, including Bonobos, Trunk Club, and Tie Society, have been trying to figure out how to cater specifically to male customers and the way they shop. Davis said they did an experiment selling women’s shirts, but quickly found that women had far more specifications in how an item fit than its male customers did. “Women have a very different set of expectations,” he said.
While 3 percent of male customers typically ask for custom shirts to be remade for sizing issues, a short test in women’s shirts saw a 28 percent remake rate.
“We saw that number and it’s like, run.”