Fashion 2.0 | Commerce That’s Curated Just for You

Looklab Screenshot | Source: Looklab.com
NEW YORK, United States — Finding fashion products online that fit personal parameters like taste, style, size, body shape, eye colour, hair colour and skin tone; are right for a particular mood or upcoming event; and can be nicely mixed-and-matched with the existing contents of a user’s closet, all while quickening the pulse and providing a feeling of discovery, is a problem that offers tremendous opportunity for would-be innovators.
In a detailed blog post last month, leading movie subscription service Netflix, known for having one of the world’s most effective personal recommendation engines, revealed a remarkable statistic. “We have adapted our personalisation algorithms… in such a way that now 75 percent of what people watch is from some sort of recommendation,” wrote Xavier Amatriain and Justin Basilico, who work in the company’s personalisation science and engineering department. But in the complex market for fashion, with its subjective tastes, trend cycles and gatekeepers, many debate whether Netflix-style recommendation algorithms are the answer.
The failure, last September, of Google’s Boutiques.com — a fashion site that promised perfectly personalised product selections powered by “machine learning” — seemed to sound something of a death knell for purely algorithmic recommendations in fashion. And yet, despite the spectacular rise of social curation sites like Pinterest, which features thousands of fashion products hand-picked by humans, simply presenting users with items shared by the people they follow is also an imperfect solution to the personal relevance problem.
Now, a number of ambitious start-ups are aiming to offer consumers more sophisticated personalised product selections and styling advice by building expert curation into their online business models.









Made in America | The False Choice





