Fits.me provides fashion retailers with a virtual fitting room to help online customers understand how different branded clothes will fit their body shapes. Customers enter their height, age and weight and from that data the Fits.me algorithms are 80% accurate in determining the shopper's body shape and whether the clothes they are interested in buying will fit. If the customer chooses to share further measurements, the platform becomes more accurate.

Creating a relationship with the consumer

Speaking to Fits.me's CEO, Stuart Simms, he tells Essential eCommerce that his retail clients are seeing benefits including customer loyalty, retention, repeat purchases and increased order values after implementing the software-as-a-service (SaaS) platform.

"We feel we can really add value to the overall customer engagement," he says. "With most eCommerce businesses, they focus on the transaction, but we really focus on the brand loyalty and repeat purchase – a more relationship model."

While this clever tool reduces returns rates and increases sales conversations, retailers find most of the value from the Fits.me platform comes from the data customers end up sharing.

This is where Simms believes retailers are finally beginning to mature and where Fits.me's data can help to close the loop. "Traditionally retailers ran their eCommerce businesses as a silo almost like a spreadsheet – you know how much money you have to spend to get the unique visitors," he says. "But there's a move from a transaction-based model to a lot more relationship-based, where they continually engage with loyal customers to create more brand equity."

Simms believes retailers have been quite blind to who their customers are, but using the Fits.me platform fashion e-tailers can learn a lot more about the demographic of their customer and use this information to shape their business.

"We give retailers an accurate representation of everyone who is loyal to their brand," explains Simms. "We worked with one major high street retailer who focused on 18-24-year-olds and 90% of customers saw our button to 'try stuff on'. Those who did were more willing to actively share information than any other demographic, it seems like the younger generation are happy to share information if they trust the brand and realise they'll get some kind of benefit from doing so."

The perfect fit

The Fits.me platform is currently white-labelled by retailers – including Hugo Boss, Henry Lloyd and QVC – and is integrated towards the end of the online shopping journey when customers are looking to purchase items. They can enter further data including specific body measurements like hips and bust size to help the algorithms find the perfect fit.

Simms says retailers can then use this information to help in broader areas of business, such as design, inventory management and shallow stocking.

"Now eCommerce has become more broadly in line with the rest of the retail business, the data we sit on is valuable across the whole business value chain, whether it is in how they design against their loyal customers, how they bring out the new season sale and define the inventory profile, or how they market and sell to a different demographic because they might have a middle aged male customer who is slightly chubby, when they thought they were trying to target 30-year-olds, so then the marketing spend can be tuned."

Fits.me was founded in Estonia in 2010 where in three sites the company's intense R&D continues, but its commercial operations are now headquartered in London employing over 70 people. Over the summer, Fits.me was acquired by Rakuten in a bid for the international marketplace to capitalise on its visualisation and data expertise.

"We started off with robots and then realised we could capture consumer data at scale and work with retailers to capture their garment data, match it together and we realised we had become a data analytics company."

Fits.me's robots in Estonia

Simms says in the future the company is looking to move away from being a white-labelled product to a platform customers recognise and want to use wherever they shop.

"At the moment we come at the end of the transaction, but in the future we think we will be at the front, because if you think about the consumer you're engaging with you could provide better recommendations at the front."

Simms uses homepage recommendations as an example. If a shopper visits a site logged in with Fits.me the homepage could then recommend clothing which suits their body shape. This would require a passport-style piece of software which the customer takes ownership of.

"Where we feature at the moment is very session-based, but in the future I could see that changing," he adds, saying the retailer's goal is to eradicate the need for sized clothes.

"We want to change the way people search and discover clothing," he says. "We want to engage and encourage consumers to keep their own data and it will be across multiple different retailers. If we truly want to achieve our mission of removing the need to know your size when you go online, which is a key barrier to purchase, that's exactly what we would need to do."

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