It’s incredibly common to hear people say that “big data is disrupting every industry”- yet, in many respects, the fashion industry is still playing catch up. Although data science has been used to optimise delivery logistics, recommend products and target customers, it’s yet to disrupt actual fashion products in a profound way. This is where Fashion Metric come in- their SaaS helps businesses gain better bodily measurements from their customers, decreasing returns and increasing customer satisfaction. We recently spoke to FashionMetric CEO & Co-Founder Daina Burnes Linton about the past, present and future of the fashion industry- and where data science comes in.
Briefly introduce yourself and your product.
My name is Daina Linton and I am the co-founder and CEO of Fashion Metric, a SaaS company that builds technologies for apparel brands and retailers to make it easy for shoppers to buy better fitting clothes both in-store and online.
I grew up in a family that has a history in master tailoring dating back to the early 1900’s with tailor shops in Lithuania, Germany and eventually Canada. I was inspired by my family craft and wanted to find a way to evolve traditional tailoring concepts and attentiveness to body measurements into modern times.
The core of our technology is the Virtual Tailor API, which provides more measurements than a typical tailor would measure in person without actually requiring a person to be physically measured. One of the hardest things to do is to make something very complex look easy to the end-user. While our technology is driven by mathematical algorithms and complex datasets under-the-hood, a shopper only has to answer a few simple questions for our technology to predict over 50 discrete body measurements. This data can be passed through to the retailer to not only better understand their customers but to also leverage the information for a variety of purposes such as making better inventory management decisions.
You started off as a consumer-facing ecommerce store; talk us through your journey, and why you decided to move towards proprietary tech.
The problem all consumers face when shopping for clothes both in-store and online is determining what size they should buy. In a brick and mortar store shoppers solve this problem by taking a few different sizes into a dressing room. Online they’re forced to either take a risk by buying only one size or pay more upfront to buy multiple sizes and return the size that doesn’t fit.
We initially released the Fashion Metric technology on our own consumer-facing eCommerce apparel store. Instead of selecting a size, shoppers would simply browse based on style and our technology would ascertain the correct size to ship to the customer. Along with off-the-rack sizes (i.e. S, M, L, XL) we also sold custom clothing, all exclusively fitted by the output of our technology.
The results were very encouraging and soon other retailers reached-out requesting access to our technology for use in their stores. The demand grew a lot faster than we had expected and we quickly realized there was a huge opportunity to license our technology rather than using it exclusively on our store.
Your website claims 28% of apparel bought online is returned- this high number is often linked with poor sizing. Historically speaking, how did off-the-rack sizing get so out of kilter?
The mass production of clothing based on a standard sizing system began to accelerate by the mid 19th century, mainly driven by the military uniform requirements from the American Civil War and Crimean War. Governments became involved in measuring body dimensions of thousands of recruits to discover body measurement patterns to form the basis of a set of standard sizes that fit most soldiers. This general concept was soon translated to civilian clothing for both men and women by the turn of the century. This era was a transformative time for the apparel industry, where access to garments had been traditionally bespoke or homemade toward the mass production of ready-to-wear sizes that could be purchased and worn straight off the rack.
Over time various sizing standardization systems developed to serve different populations while managing the delicate balance between mass production requirements and customer satisfaction around fit. It became increasingly common for manufacturers to assign their own sizing system resulting in the non-standardized system of ready-to-wear sizing that we know today. This has led to an incredible amount of consumer confusion around ready-to-wear sizing, since a Medium in one brand could be a Small in another. The problem is amplified online, with consumer’s left to puzzle over size charts.
Another (much less tech-centric) to the sizing problem is the rise of the “One Size Fits All” store- what are your thoughts on this?
While it would be great to think that there is one specific body type that is similar to everyone this just isn’t realistic. It doesn’t take mathematical algorithms to realize that with billions of people on this planet there is an incredibly diversity in body types, shapes, and sizes, not just one.
In many cases the idea of “One Size Fits All” ends-up being offensive as it can easily make people feel like there is something wrong with them when statistically speaking they are more normal than the model they are comparing themselves to.
We are at such an incredible time in our history, hyper-personalization is finally possible and it’s technologies like the ones we work on every single day that we hope will show people that they are fine just they way they are. Forget one-size-fits-all, let’s talk about appreciating how unique each of us is and how we can find clothes that allows us to be proud and express who we are as individuals.
Big data and ecommerce is a match made in Heaven, but big data and fashion is a pairing we hear a lot less about. Why do you think this is?
Physical stores have seen massive disruption over the last decade with companies like Amazon.com and Netflix catalyzing major consumer habit changes. Walk down the main street of any major city now and you’ll find lots of restaurants and clothing stores but less and less bookstores and video rental stores.
The shift from physical to digital has swept through entire industries but left apparel relatively untouched. Amazon tipped the scales with books when they introduced the “Look Inside” feature, making it possible for consumers to virtually browse books like they would in a bookstore. Netflix moved people from physical disks to streaming, allowing instant access to content. These were disruptive forces that made it easier for people to do something they had done the same way for a long time.
In the apparel space “fit” has always been the limiting factor, just like people want to browse a book or watch a movie preview, they still want to try clothes on. Despite the growth of technology and access to huge amounts of data, the apparel industry is challenged with providing a compelling experience for consumers so that they can buy clothes without trying them on.
Can you name any other companies at the intersection between fashion and tech whose work particularly excites you?
I’m particularly excited about the 3D Printing industry and its potential to drastically impact the way clothing is made. It’s still early so it’s hard to name a single leader in the space but the idea of seeing something online and printing it in your living room is likely a closer reality than we might think. Couple this with companies like Oculus that are making it possible to re-create experiences that could normally only happen in a shopping mall and it’s clear we are entering a new era. We are continuously evaluating how our technology can be leveraged not just for where the industry is today but where it is heading.
What’s in the roadmap for the future of Fashion Metric?
We see a future where apparel brands and retailers know more about their shoppers than ever before. To power these experiences we are always looking for ways to collect more data and algorithms to help make this data more meaningful and actionable.
You can expect to see Fashion Metric come out with products that run behind-the-scenes with retailers both in-store and online to enhance the end-to-end shopping experience. You might not know we are there, but that’s the beauty in what we do. Our goal is to build technologies that shoppers might not even know they are using but that personalizes their experience in a way that absolutely delights them.
What do you envision in the future of data science & ecommerce in general?
There is no doubt that mobile will be one of the single largest forces driving changes and innovation in the eCommerce world. This directly impacts data science as the medium that people use to shop moves from a personal computer to a personal phone. Your smartphone has a lot more data on it about you than your computer does and leveraging this data will change the data science world forever.
Back in the late 1990’s consumers were terrified of cookies. The idea that a website would track what they do was an uncomfortable and foreign concept. Now every single eCommerce website uses cookies to personalize the experience and consumers have become very comfortable with the concept after realizing and enjoying the benefits that it provides. The same thing is happening with smartphones and it’s happening at a fast pace. More apps than ever now ask for location data and consumers are getting more comfortable sharing this and more data to help provide a more personalized experience.
