Big Data Lingerie Lines

Startup True & Co Uses Big Data to Help Women Locate the Perfect Bra Fit

A lingerie startup is using big data to help women find the perfect bra fit. True & Co is based out of San Francisco and is reinventing how personal shopping happens online. Through TrueSpectrum, the ecommerce company collected 7 million data points to help customers find the perfect bra fit for their body type.

Customers are asked to take a 2 minute survey covering topics like breast shape and bra slippage. This sort of information is fed through software that showed Founder and CEO Michelle Lam and her team that there are over 6,000 body types represented by their customers. Using the information they've discovered, True & Co is now designing their own bras that will ensure women of all shapes and sizes find the perfect bra fit.
Trend Themes
1. Big Data Analytics in Lingerie - Lingerie startups are leveraging big data analytics to help women find their perfect bra fit, revolutionizing the online personal shopping experience.
2. Personalized Ecommerce - The use of big data and customer surveys is paving the way for personalized ecommerce experiences, allowing companies like True & Co to tailor their products to individual body types.
3. Data-driven Product Design - By analyzing millions of data points, lingerie brands can now create bras that cater to the diverse body types of their customers, offering better fit and comfort.
Industry Implications
1. Lingerie - The lingerie industry is embracing big data analytics to enhance the bra shopping experience, providing women with more accurate sizing and fit recommendations.
2. Ecommerce - Ecommerce platforms are increasingly adopting data-driven approaches to provide customers with personalized shopping experiences, leading to higher customer satisfaction and loyalty.
3. Fashion Design - The fashion design industry is being disrupted by big data, enabling designers to create products that cater to diverse body shapes and sizes, promoting inclusivity and body positivity.

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