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A global first with data: sizing up the childrenswear market

EDITED announce a world first: new software which allows retailers to accurately filter childrenswear data from around the globe.
A global first with data: sizing up the childrenswear market | EDITED

The thing about kids is — they grow. Look away for seven minutes and their wrists are springing out from long-sleeved tops and their pants are now capris.

While keeping these miniature growth rockets in clothes that actually fit is a seemingly endless task for parents, it’s a joyful thing for retailers — and aunts — around the world.

In fact, kids aren’t the only things growing. The childrenswear market has also been eating its spinach, closing 2015 with an estimated $156.8 billion in revenue. Our childrenswear data shows the top 20 biggest childrenswear retailers upped their offering by 8.6% in Q2 of this year compared to last year.

Retailers agree this market is a beast unto itself. “Children’s fashion has changed in terms of fast fashion and competitive pricing” says Maddy Zimmerman, Buyer for Toddler Boys at Gap, adding that it’s “changed the children’s fashion space dramatically”.

The sector is big business – but it’s also a tough one to crack. To start, the terminology is vast and labyrinthine and the sizes are all over the place. It’s enough to make a daunting task out of just establishing what the market is. And good luck finding the products if you do.

So why are we telling you this?

Because we knew that retailers using our data needed some hard-hitting tools to tackle the challenges childrenswear presents — and we decided to do something about that. So, we’ve built the world’s first data tool specifically aimed at bringing the global childrenswear market to life.


How’d we do it? We’re happy to explain.

Like we said above, childrenswear is an inherently tricky market to apply science to. Why? Well, back to that growing thing. There is no standardized way of referring to kids’ sizing, that means every brand or retailer basically has its own way of labeling childrenswear. So when you’re trying to get a computer to recognize all these different labels as the same thing and group them together, it takes more than a little ingenuity. For example, look at these: 2y, 24 months, 2-3 years, 2+, 2t and 2ans – they all refer to the same size: 2 years. And it’s just as convoluted for every age, and every size.

Right away we knew there was no way we’d be able to list every size our data collection software came across – there’d have been thousands of entries. It would have been too overwhelming for users and too segregated to give them an instant look at the entire market in one click. The only was around it was to unknot the many different naming conventions in girls’ and boys’ sizes, as well as footwear with linear and non-linear sizing scales.

So instead of simply recording size data, it was imperative that we would need to build something that could interpret and understand the data.

To do that, we built a complex normalization algorithm that takes a size from any retailer, market or brand and classifies it according to our own sizing standard, a predefined range of sizes based on extensive research into children’s apparel across millions of SKUs. That sizing standard includes months (0-24), years (2-18), non-numeric sizes (S, M, L, XL, etc.) and even footwear (UK, US, etc.). The algorithm then applies syntax and semantic analysis to every product we capture and correlates its size with our standard.

By doing that we’ve created a simple and usable filter that gives EDITED users the power to pivot on a wide range of data from 13 different regions across thousands of retailers and brands. It’s a world first, and we are immensely proud of our super smart data scientists — not just building it — but doing so without an existing blueprint or template. This one’s all theirs, and we’re excited to say that now it’s yours too. Assuming you use EDITED. If not, this would be a great time to change that!