Two-year-old MTailor has garnered millions in sales for its custom-made shirts, all via its app.
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At Atlanta-based Underneath.com, repeat customers constitute “a healthy volume,” says Mike Waters, vice president of accounting and operations. Underneath.com gathers such information from customers at check-out. Like many web retailers, the site encourages repeat business with an e-mail list customers can join to receive a monthly newsletter alerting them to sales and promotions.
The company hopes to offer automated replenishment this year. “It’s our goal to be more automated on the backend so we can say by e-mail, ‘You ordered a three-pack of briefs on June 23rd, do you need more now?’” Waters says. Kenosha, Wis.-based underwear manufacturer Jockey International already offers automated order replenishment direct to consumers through its Here’s Jockey program on Jockey.com. Registered online shoppers can request automatic shipment of favorite items on a three-month or six-month schedule; shipping, credit card and preference information is securely stored so shoppers don’t have to re-register or even go through the re-order process. An automated replenishment feature is also on the radar screen of competitors including OneHanesPlace.com, the outlet web site of hosiery, athletic clothes and underwear manufacturer Hanes, as well as Undergear.com.
Replenishment of staples also helps drive sales of menswear at LandsEnd.com. The ongoing demand for basic men’s dress shirts, socks, underwear and jeans online is about 40% higher than for other apparel on the site. There’s no similar pattern of higher demand online for any items of women’s apparel-yet. Lands’ End has just started selling women’s intimate apparel on its web site and believes that could become a popular replenishment item for women.
The tech issue
As is the case with other product categories on the web, success with apparel sales will depend increasingly on how effective retailers can be in stratifying their customer bases and coming up with marketing approaches that are on target. Apparel, however, carries some singular challenges in the form of data-dense image files that can be slow to download and color depiction that may be off the mark. Then there’s the remote sizing issue-the standard sizing options offered online may be hit or miss. And so many are wondering to what extent web site performance issues are impeding the growth of apparel shopping online, and whether technology can solve those issues.
The answer depends on whom you ask. Several technology developers have become ASPs, with branded offerings for web sites that tackle the issues they see as major impediments to buying apparel online. “The average return rate for women’s apparel purchased online is about 35%-more for some high-fashion items,” says Ernesto Aguirre, CEO at technology vendor The Right Size. “About 50% of the returns are attributed to size. That represents an incredible financial burden to a web retailers.” Not only does it cost the e-retailer from $10 to $15 to ship, reverse ship, receive and restock each returned item, but the process puts the product out of circulation for two to four weeks-a heavy burden when the seasonal shelf life of an apparel item may be only 12 weeks.
The Burlingame, Calif.-based company offers search engine technology that makes apparel selection recommendations which go beyond size and style guidance to incorporate fit preference. How? It’s actually two search engines-one that generates style and fashion recommendations the shopper might enjoy based on preference information he supplies, and another that sizes the clothing item based on the user’s fit preference.
“If the shopper is 18 years old, 150 pounds, has a 28 inch waist but wears his pants around his hips, a normal search engine is going to recommend size 28 pants. But they won’t fit him in the way he likes,” Aguirre explains. “But if he tells me he owns a pair of Tommy Hilfiger jeans in size 32 and he likes the way they fit, we’d recommend something that fits similarly.”
Aguirre’s patent-pending search engine contains data on the fits of 4,500 apparel brands and some 13,000 styles, gathered from the reports of real-life models hired by the company to try on clothing, as well as input from its industry expert advisory board. “We’ve trained our database with specific information from multiple sizes, cuts and fits. We then use the data to map product recommendation tools,” Aguirre says. “If we just have the shoppers’ dimensions, we can’t determine how they like their clothes to fit, just what size they are. We take it a step further.”
Recommendations using the database are currently available at the company’s own web site. Aguirre is hoping to license the technology for use by e-retailers as well as by manufacturers who don’t transact consumer sales on their own sites but want to link visitors to their products at web stores.
Over the rainbow
Color correction technology vendors have marshaled myriad data to support the notion that color depiction is a major barrier to apparel buying online. A commissioned study by InfoTrends, for example, revealed that 81% of consumers have concerns about inaccurate color depiction, affecting their decisions to purchase color-dependent items via the web. A total of 60% of online consumers in a CyberDialogue study don’t trust the colors viewed on their monitors, while 30% have abandoned shopping carts due to uncertainty about an item’s color.
Pantone, the provider of color services, is developing a set of standards for e-retailers to use on web products to ensure that the consumer knows the exact color of a product. Under the Pantone plan, retailers can call a color any name they want, but the consumer will have the option of checking on the Pantone number, then comparing that number to a book of color samples that retailers will distribute to consumers. In that way, consumers will know exactly which color they are viewing.