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How Big Data Finds The Perfect Bra Fit

How Big Data Finds The Perfect Bra Fit
Retail

Lingerie startup True&Co is using data-powered insights to get the right products to their customers.

Lara Piras
  • 16 june 2014

As opposed to standard lingerie promotions of models in suggestive poses, this San Francisco-based e-commerce startup is taking product matching to a whole new level.

True&Co; have reinvented the term personal shopping. By using data science, Michelle Lam, the founder and CEO, has figured out a way to help women find the perfect bra for their body type. Lam and her team collected 7 million data points from their customers including breast shape and the percentage of strap slippage. Their proprietary software has also discovered that there are over 6,000 different body types within the customers who’ve bought from them.

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They use a big data solution called TrueSpectrum that asks customers to take part in a two-minute questionnaire about their body shape. It works similarly to how Netflix recommends TV and movies, providing the shopper with bra options from an array of brands that are deemed a perfect fit.

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Now, using all the data they’ve collected, True&Co; is creating their own bras. Designs are based on whether the woman’s breasts are full or shallow, high or low, wide-set or even a combination of any of these. The bras take into account the complaints that cropped up the most throughout the quizzes, for example 62% of women hate when they “bust out,” most notably in their underarms. To overcome this, True&Co; created a bra with a high-cut spandex band to rule out that ever occurring.

The collection of data to ensure something fits seems like a sure method to make customers feel like the brand cares and feel happier about the product. It shouldn’t be long before other apparel brands follow suit.

True&Co;

[h/t] True&Co;, Wired

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