What does your company do & what is your USP?
Rakuten Fits Me offers a suite of personalisation software centred around fit which works to remove barriers to conversion giving shoppers confidence that garments they are purchasing will fit them well. With clothing sizes differing across fashion retailers and brands and even across ranges, a size Medium in one product line may not be the same as a Medium size in a different range.
People are different too with body shapes and measurements varying between individuals. Two people who are the same clothes size may be completely different heights with different body shapes. Fits Me offers a bridge between a garment’s actual size and the individual consumer by giving each shopper unique recommendations based on their individual measurements and body shape matching them with garment sizes from the retailer or brand whose site they are browsing. This results in a true one-to-one personalised experience for the shopper which makes online shopping quicker, easier and more fun.
How does your solution work?
The core Fits Me fit recommendation algorithm combines expertise gathered from categorising garment types, attribute mapping, data science algorithms and historical consumer data to create a deep understanding of body shapes, measurements and preferences. It also supports global differences in shopper shape, preference and build, with data collected from over 30 million unique profiles to create accurate recommendations.
When a shopper enters their personal measurements into one of the Fits Me solutions integrated into a retailer’s website, the algorithm analyses the customer’s unique information and compares it to the actual sizes of garments sold by the retailer to give personal recommendations on whether individual items are a good or bad fit. Data collected from the shopper includes age, height, weight and bra size or neck measurement. The solution also asks them to identify their body shape from a selection of images.
This gives a better match between the garment and customer than the shopper looking at the retailer’s generic size guide and returns a true one-to-one personalised offer for the consumer showing them how well each item will fit them at each of the key measurement points entered.
What unique offering does fit match bring to retailers?
The company’s latest solution is Fit Mach, a fit and size recommendation system which integrates within a retailer’s search and product listing page capabilities. When a shopper searches for a blue dress, for example, a fashion or department store site can return multiple options in the search rankings. By giving the customer the option of filtering the results by their measurements and combining the results with stock information, the solution can reduce the product listing to a more manageable choice for the shopper, first ranking the items that are the best fit for them as well as being available in their size. Garments which are out of stock or not the best fit can be listed further on in the search ranking.
The shopper can also use the retailer’s existing search filters, such as style, length or price, to reduce the options further. They then just have to decide which item they like the most rather than having to worry about whether it will fit them or if it’s in stock in their size.
The shopper also has the option of Fit Match remembering their measurements so that they can be automatically entered next time they go to the search filter on that retailer’s site or anywhere else that Fit Match is integrated. The ease of integration is a massive benefit to retailers and it looks and acts like it is part of the search bar, giving shoppers a completely native experience; reducing down clicks to basket and relieving the headache of trying to match up sizes from consumer POV.
Why is the right fit data vital for retailers?
Getting the fit right not only reduces returns but gives shoppers more confidence in a retailer’s garments so that they buy more frequently and thus become more loyal to the brand. In converse, sending out a garment which won’t fit can lose a retailer customers since 80% of consumers won’t shop with a retailer again if they return their first order.
Fits Me also helps retailers to gain a better understanding of their customers. While retailers track their customer behaviour they don’t know what consumers actually look like and they cannot be sure about fit satisfaction and how happy an individual shopper is with their purchase. All they know is that the garment wasn’t returned. Fits Me shows what shoppers look like and this insight can inform conversations with manufacturers around fit, size guide and how actual garments fit with the core customer base or consumers browsing a retail or brand site.
For global retailers, Fits Me analytics also help with information on shoppers in different regions providing insight into body shapes, fit and style preferences. The Fashion IQ dashboard, for example, overlays this insight with conversion data and garment attributes to provide actionable insights to improve design and retailer’s purchasing decisions.
Who are your customers?
Fit Me has solutions for all sizes of retailer, ranging from a 30-day free trial to an integrated solution with full dashboards returning shopper insights and analytics. Customers include athleisure brands Rhone, J.Lindeberg and Peak Performance as well as luxury and fashion retailers Lux Fix and Mud Jeans and larger retailers including George at Asda and QVC. New clients include Billabong and G-Star.
What plans do you have for the future?
The company has an extensive roadmap to develop Fit Match further in 2018. This includes taking personalisation to the next level by expanding the solution to include preferences and styling information for individual shoppers. This could include length, such as maxi dresses over mini, or loose fit jackets rather than tailored if the shopper has shown a preference for that styling in the past.
More dashboards and insight to help retailers understand their shoppers and make better informed decisions with manufacturers or when entering a new market will also be added.
Customer Case Study
Rhone is a premium, men’s active wear brand which was founded in 2014. Its success led to its customer service team soon being overwhelmed with size and fit related queries, particularly through online chat.
“It was clear that our customers needed more support than our size chart to find the right fit online,” says Adam Bridegan, SVP of Advertising, Digital and eCommerce, Rhone.
In order to help its shoppers make the right decisions when choosing what products to buy online, and in what size, Rhone started researching the various size and fit technology options available to retailers in 2015. Accuracy of the size recommendation and fit advice was a top priority, and the company wanted to work with a vendor which would use their own product data rather than inferring a recommendation based on purchase and/or returns data (the latter is known as collaborative filtering).
In the first month of implementing Rakuten’s Fits Me Fit Origin, the solution was able to prove its value. The conversion rate of Rakuten Fits Me users on Rhone’s website was 9.8% versus non-users who converted at just 3.7%.
A year later, Rakuten Fits Me user conversion rates were still triple and some months even quadruple to non-user conversions. Additionally, analytics show that Fit Origin has delivered an impressive +20.4% in incremental revenue to Rhone’s website. This is a natural testament to the confidence Fit Origin gives shoppers to convert and buy with the brand. Not only do conversions increase, Rakuten Fits Me’s solutions have been proven to increase average order size – rather than having to buy two of the same item in different sizes (with the knowledge they’d have to return one), shoppers can simply buy more.
Rhone is now upgrading to Fits Me’s new Fit Match solution.
This Company Spotlight was produced by InternetRetailing and sponsored by Rakuten Fits Me. Funding articles in this way allows us to explore topics and present relevant services and information that we believe our readers will find of interest.