An online service is helping brands and retailers provide a better shopping experience for their customers trying to find the correct clothing size online.
In preparation for the release of our upcoming Future Of Retail report, PSFK reached out to Clothes Horse, an online service helping clothing brands and retailers provide a better shopping experience for their customers shopping online. Using a data driven approach to recommending sizes based on a shopper’s body details and favorite styles, the algorithm underwriting Clothes Horse provides shoppers with tailored recommendations for properly fitting clothing so they can make more confident purchase decisions, leading to more sales, fewer returns, and increased customer loyalty. We caught up with co-founder Vik Venkatraman to get his thoughts.
Tell us a little about Clothes Horse. How does it work? What is the idea behind the service?
Clothes Horse is solving the problem of buying clothes that fit online. It works by taking a ton of data about shoppers and brands, expertise on production, fabric, and fit, and wrapping it up in an algorithm that is both accurate and simple to use. The single biggest hurdle that keeps the apparel industry from truly adopting the web in a big way is that it remains challenging to communicate fit to the shopper. Do you know how to read a size chart? What does “fits true to size” mean to you? By focusing on the shopper and the brand, Clothes Horse aims to transform an industry through technology — and we’re solving the fit problem first.
Are there any notable figures or statistics around customer engagement and usage?
We get a lot of usage, and our engagement is terrific — we put a lot of emphasis on the user experience and in understanding the shopper problem. Typically, 10-15%+ of people who come across our product will open it, and 90% of people who open our product will receive a recommendation. We deliver thousands of recommendations a week, creating confidence and trust for shoppers, and lifting the top and bottom lines for our retail partners.
We have have noticed that enhanced customer scanning software and algorithms are offering unprecedented ways for retailers to remotely tailor products for their customers, ensuring consumers reach a new level of comfort and satisfaction in their online shopping experience. Do you see this trend manifesting on a wider scale? How so?
We live in exciting times. There’s a perfect storm brewing between new capabilities in technology, an increasingly savvy shopper who expects the benefits of technology, and a retailer community who is now ready to adopt and experiment with much more openness than ever before. As a result, technology like ours, that allows the retailer to use real data and sophisticated algorithms to provide a smarter, more tailored experience is quickly going to change from something new and interesting to something expected and obvious to the shopper. I would predict that smart retailers are also going to be able to use the insights gained from better data and better interaction with the shopper to create a ton of efficiencies all the way up the value chain — which should result in better shopper experiences, better prices (or better margins), data-driven design and forecasting, and a ton of other benefits. The successful retailers of the future are going to be widely tech-enabled and operate very differently than they do today.
What are the opportunities for retailers utilizing Clothes Horse? How about consumers? Where do the personalized recommendations stem from?
Besides reaping the obvious benefits of increased conversion rate, enhanced shopper experience, reduced returns and other direct benefits, retailers using Clothes Horse take a huge step from a previous era where the shopper was just a blip on the page, to today’s world where the shopper wants to have a rich, personalized experience that uses the full breadth of data thats at their fingertips. Consumers who build Clothes Horse profiles will unlock the world of possibility that comes with always knowing the right size to buy, at any of our retail partners across the web.
The recommendations come from algorithms we run on both the human side and the wardrobe side of the shopper. We have a lot of data on the sizes and proportions based on real people that we’re able to use to drive a super-simple user experience. The shopper never needs to measure themselves, just answer easy questions. We then mix that with their preferences – the shopper simply tells us about at least one piece of clothing they have in that category. Then based on both of those bits of info as well as all the other shoppers and preferences on our system, we’re able to come up with the best size for the shopper, as well as some details on how it should fit.
Today, all the data that exists in your lifetime of experience and all the items in your closet lay dormant — we’re creating a future that uses these and more to build amazing experiences and better business for our shopper and our retail partners.