Cricket Lee’s Botasci Aims to Transform Fit

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Cricket Lee, who invented the Fitlogic technology, has cofounded a new company called Botasci, an acronym for Body Data Science, which when applied properly aims to fit 95 percent of women and reduce returns by 75 percent.

Lee’s philosophy is that patterns, grading and fit are wrong, and there’s a much better way to fit customers.

According to Mark Mendelson, an adviser to Botasci, women’s apparel companies are still using hourglass patterns. “In 1945, hourglass made sense. In 2020, it’s less than 40 percent of the customers,” he said. According to the executives, the main problem with fit is that fashion brands typically use a singular fit model and then grade their patterns up or down a half inch to achieve a range of sizes. They also inaccurately use data focused regionally, much like the fit standards that were built in 1952.

Lee, who is chief executive officer and cofounded the company with her daughter, Natasha, feels that the old fit paradigm doesn’t work anymore as a point of differentiation for fashion brands. The average woman today is size 16, and women are much more diverse.

Botasci said it reduces global carbon footprint sustainably by assigning a custom full-body shape code to each customer, eliminating serial returns from first purchase; reducing regular returns by 75 percent, fitting 95 percent of women, and offering a 98 percent accurate predictive demand inventory model by shape never before available to the fashion industry.

The company is talking to brands and retailers like Chico’s FAS, Ascena, Kohl’s Corp. and XCel Brands Inc. to license the software. “We can start with a couple of styles,” said Lee.

The company seeks to streamline the purchase of clothing by eliminating size choice for the customer, solving the pathogen problem of clothing in stores since no “try on” is required by purchase; enable focus on stockkeeping units on demographic and ethnic profiles desired, and provide shape style preferences to designers, eliminating waste from ill-fitting sleeves, styles, etc.

“We are a fit system that gives the companies blocks and we show them how to make three or four bottoms and three to four tops, based on a woman’s shape,” said Mendelson. “Once you have her shape, she never has to look at a size again. Once you have her in the database, she knows what she is,” he said. For example, they don’t offer one size four, but four different size fours. In bottoms, for example, they will offer four shapes: Apple, Rectangle, Hourglass and Pear, said Lee.

Earlier in her career Lee invented FitLogic. Asked how this differs, Lee said Fitlogic was more of a beta brand and was only three bottom shapes and an online tool. “Now we’re doing tops and bottoms and adding shapes and accessories,” she said. Fitlogic was tested in 2006 and adapted by companies such as Garfield Marks at Nordstrom, Jones New York at Macy’s and Jones Elements on QVC. Lee sold the Fitlogic business to a licensee in December.

Botasci is a universal standard by shape, meaning the brand is powered by the technology and shop by shape platform. A full-body shape series of algorithms is embedded in the garments and data profile so that the perfect shape match for the customer is always available through the profile from any brand that adopts it. The technology greatly reduces the planning processes and merchandise returns and improves customer satisfaction resulting in more efficient applications and high repeat purchases of apparel, according to Lee.

The online data profile holds the customer’s size and shape information, and the brands adopt her personal shape code to access her purchases. It’s the opposite of the current scenario, where the responsibility is on the woman to find something that fits.

As a new universal standard, brands and retailers can adopt the full spectrum of sizes, or choose a particular shape demographic, said Lee.

The company uses letters and numbers, instead of a size. Botasci specifies body-type shapes based on personal fit. Each woman finds her match using an online tool and special data profile on its shopping site.

“We want to drive it through e-commerce in the beginning, and do a pilot with brands to test one or two styles in bottoms, or one or two styles in tops, and then analyze the data so they can predict where they want to take it,” said Lee.

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