moda operandi
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“When Aslaug Magnusdottir cofounded the luxury fashion e-retailer Moda Operandi in 2010, the timing was perfect. Even though Net a Porter—another full-price fashion e-retailer with a decade’s head start on Moda—was gaining traction, Magnusdottir says the luxury customer was still being underserved online.”

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Decoded Fashion - Fashion Tech Daily -  Moda Operandi
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“The Internet age has bred some really high spenders — and Moda Operandi just raised another $60 million to service them.”

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Decoded Fashion - Fashion Tech Daily -  Moda Operandi

Decoded Fashion - News - Discovery Apps

Over the last year two distinct groups of fashion apps have emerged, and both use the element of discovery. Up first, the app that uses the intuitive ‘like’/dislike’ method and secondly, the image recognition app used to eliminate the need for semantic word searches. See if you’d like to get more closely acquainted with some of these:

Tinder-inspired browsing apps

Fashion startups have tried to leverage the intuitive game features of the hugely popular Tinder, whose concept was derived from ‘Hot or Not.’ The result: a new kind of product browsing and discovery experience.

Stylect: The self-proclaimed ‘Tinder for shoes.’ Users can browse through a wide array of shoes, having to decide whether they ‘like’ or ‘dislike’ the shoe before the next pair flashes up. Push notifications then indicate when ‘liked’ items go on sale (more about the app here).

Mallzee: This app also requires users to ‘accept or reject’ apparel. It then uses this information to construct a customer profile and recommend other items. A social voting system which only lets the user purchase an item if it is approved by their friends can also be put into place (read more about it here).

Moda Operandi app: The runway pre-order service makes it possible to ‘like’ or ‘dislike’ items straight off the runway. Push notifications then inform users if outfits they ‘liked’ become available for pre-order (read more about this here).

Visual discovery apps

Customers upload photographs of products they’ve seen, the app waves it’s “magic wand” using image recognition software to suggest an array of similar product.

Snap Fashion: Customers can upload an image of a piece of clothing and then browse similar items according to colour or brand. Partners include high street and luxury brands such as Forever21, Asos, Ted Baker and Net-A-Porter.

ASAP54: Again, users can take a picture of an item to find something similar. The visual search combs through over a million products from 150 different retailers. If the right item still isn’t found, a real-life in-house stylist can be called upon, who will then send five product suggestions within 24 hours (read more about the app here).

Style-Eyes: This app works with over 400 high street brands and retailers, allowing for the discovery of “real-girl budget” versions of designer pieces. Search results can be filtered by brand or price, and push notifications are sent when favourite pieces go on sale.

A challenge that all of these apps face is that different users have different motivations for using them. Whilst some want exact results, others might just be browsing; high accuracy may ruin the fun element of discovery. This leaves space for further diversification and specialisation.

As AKQA’s Ben Jones mentioned at Decoded Fashion London, “maybe [the key to success in mobile] is thinking about what people do on the phone, the context of what they’re doing on their phone and the context they are in when taking their phone out to access the brand; defining that experience in a completely different way.”

Reported by Anna Abrell

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