Wednesday, July 09, 2014

Rank and Style: Using Big Data To Turn Browsers into Buyers

Rank and Style is shopping recommendation service that uses an algorithm and market research to publish regular "top ten" lists of popular fashion and accessories items, promising unbiased advice to shoppers looking to buy the most top item available in a sea of choice online. The ultimate aim is to up the conversion rate of shoppers, who the founder say can take up to two weeks to decide on their final purchase (yes, that’s a lot of browsing!)

So how exactly does it work?

In the words of Rank & Style: "Using our algorithm to crawl the internet (so you don’t have to!) and obsessively, compulsively and, most importantly, objectively, searching for user reviews, bloggers’ tips, best-seller lists, editors’ picks, celebrity favorites, and industry recommendations, Rank & Style collects all the relevant information for your seemingly impossible mission of finding the *best*. After all these “ingredients” are gathered, our algorithm further aggregates, weighs and cross-references the data to identify the ten best items.”



The lists are published through their app and web platform and sent out as emails, and shoppers then click through the the retailer’s websites to buy the item, generating revenue for Rank & Style as an affiliate advertiser. Brands cannot pay to have their products featured, but there is uncertainty around whether the ‘market research’ aspect of the ranking might be biased by towards certain advertisers on their site.

Rank & Style was co-founded by Sarika Doshi, Pooja Badlani and Sonal Gupta and the team were recently awarded the ‘Founders of the Future’ award at New York’s first Fashion Tech Forum, which is where i came across the company. The award included a $50,000 grant and mentorship from among the judges, who included Nasty Gal’s Sophia Amoruso, GAP’s Creative Director Rebekah Bay and Coach Executive Chairman Lew Frankfort. 

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