Not so Clueless, thanks to data

Rinat Perry doesn’t smile, she beams. Beneath that head of generous brown curls is someone who knows what she wants and has been working hard at it. As a former fashion designer and stylist, the Israeli businesswoman chats enthusiastically about how attending a She Loves Data workshop has helped with her start-up StyleClueless.

A few years ago, while watching the American coming-of-age romantic comedy, Clueless, Perry had an epiphany. She realised no one was yet offering a comprehensive tool which fashion brands can use to help their customers understand their collections. For example, if they had bought an item or two, they may not necessarily know how best to maximise their purchase by creating different combinations of outfits they liked based on their styling preferences. More often than not, the case was that someone saw their favourite Instagram influencer wearing an incredible outfit and loved it but it just did not match her body type. As Perry explained, “You hear this all the time: I love the jacket, so how do I wear that?”

Rinat Perry, Founder of StyleClueless and a fan of machine learning.

While the idea is to offer consumers the possibility of visualising themselves in a complete look by creating outfit suggestions, StyleClueless also helps brands be more sustainable as many are stuck in inventories -items that are not bought simply because people do not know how to wear them or combine them with what they already own. Most ordinary folks certainly do not have personal stylists. Ecologically, StyleClueless makes sense as well. Now, each purchase can be worn much more often and even more purposefully.

At the end of the day, Perry loves it that machine learning teaches the retail business so much more about the purchased item journey when what was offered not too long ago online were just basic shopper demographics. The potential for different fashion brands to cross promote is also endless.

The big challenge for Perry was learning to communicate with the data scientists she works with. She shares her experience after the free She Loves Data workshop on data analytics, “When you haven’t learnt Computer Science and you don’t come from that world, it’s very intimidating. Most of the time the people in this industry are not so keen about explaining and they are not patient at all. So when you come to this event and instructor Quinn Pham gives the right explanations and compares it to things we can relate to, it’s easier to understand. Suddenly, it makes sense.”

Whatever your background, wherever you are on your career journey, you too can reap the benefits of data and machine learning. Join us for our next She Loves Data event in Singapore on 30 July: Machine Learning and you.


Soo Sien Tay

Soo Sien gets a high talking to strangers and enjoys being exposed to new voices.
Her jet fuel includes spin, hot yoga and stand-up paddling.
At She Loves Data, she is doing what she loves with people she loves.

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Soo Sien Tay