Face value? Proving Metail’s look-alike models boost customer engagement

For many online shoppers the option to return items of clothing that don’t fit is an essential part of their decision to purchase.

So much so that many online stores allow customers to ‘try before they buy’ in the hope they will place more items in their shopping basket and end up keeping some of them.

But operating a super-flexible returns policy is expensive business for retailers - delaying profits and making stock predictions much more difficult.

Metail is a pioneering Cambridge tech business hoping to take the guesswork out of buying and selling clothes online.

Face off

Their software digitises a retailer’s clothing inventory and allows budding fashionistas to assemble outfits on a 3D avatar of themselves. The result is a photo-realistic visualisation of how the clothes will look and fit.

The cutting edge technology is the result of over 10 years’ heavy - and mostly top secret - R&D investment in 3D visualisation.

During this time, Metail created the algorithm which creates a 3D face model from a mobile phone photograph and then uses the 3D face model to generate a personalised 3D avatar for the user.

When they were ready to demonstrate the end-to-end process to investors, they asked Fluent to embed their model into a custom-built iOS proof-of-concept app.

3D avatars and digital changing rooms are small but important components of a much bigger Metail system, which aims to make ‘clothing fit for all.’

The wider system is able to learn from the choices you make. It’s like having a personal shopper who knows your style and measurements so well, it can recommend available items in your size. Metail’s data shows that improving customer experience in this way can increase spending by an average 22% and reduce returns by 5%.

It’s a transformative time for the online fashion industry. We’re excited to be working with one of its brightest disruptors.