Analytics Dashboard Helps Fashion Brands Forecast Sales
Online fashion styling community Polyvore today released an experimental analytics dashboard designed to help brands keep track of how their goods are performing on the site over time, revealing what’s popular with consumers before said goods even hit the stores.
For those unfamiliar, Polyyore e-year-old online community where more than 2 million registered users create sets using product shots of clothing and accessories. These are often accompanied by other elements that help express a certain theme or lifestyle, such as iPhones, Starbucks coffee cups, and book and movie covers.
Although 2 million registered users may not seem like much, the site attracts more than 7 million unique visitors and 140 million page views per month, making it one of the largest fashion destinations on the web. One million fashion sets are created each month.
The dashboard enables designers — and anyone else — to see what other brands their items are often styled with. They can also see how individual products are performing day to day (and season to season) based upon how frequently they are used in fashion collages (sets), “liked” and bookmarked for future reference. Brands will be given an overall rank reflecting these criteria.
This kind of data was previously only available to companies that ran contests on the site, in which users were encouraged to explore and interact with a set of products for a chance at various prizes, such as trips and shopping sprees. Brands were then able to use that data to predict what items would sell best.
This spring, for instance, Diane von Furstenberg ran a styling contest in which a certain wedge shoe that proved to be overwhelmingly popular on Polyvore went on to become a bestseller in stores. Co-founder and Head of Product Management Jess Lee claims that given the shoe’s success in the Polyvore campaign, Furstenberg decided to order more inventory, which proved to be a profitable decision. Now, all brands have access to that kind of valuable data, enabling them to make similar decisions.
The dashboard should also offer brands ideas for new items to create. For instance, if users frequently style a given designer’s tees and jeans with leather jackets from another brand, said designer might consider including leather jackets in future collections.
Polyvore plans to make more of its data available in future iterations, helping brands and merchandisers track the rise and fall of certain trends, and other tools to help predict what items will sell best in stores.
“With the rise of social media, there’s an enormous amount of customer feedback
for companies to digest,” Lee says. “Our goal is to provide brands, large and small, with a simple tool that can help them make decisions about merchandising and marketing.”