Fit is one of the biggest drivers of customer loyalty
Rakuten Fits Me provides a full product suite for ecommerce apparel retailers to take the guesswork out of sizing and to personalise the shopping experience. This gives shoppers the confidence to find, buy and keep clothes that fit and flatter their unique body shape. Vicky Zadeh, CEO, Rakuten Fits Me spills the beans on technologies that will shape the future of fashion retail and how sizing solutions are replacing sizing charts.
What is the market size of the global online apparel industry? What is the expected growth rate by 2020?
Ecommerce continues to play an incredibly important role in the retail industry. The performance in 2017 clearly shows this; retailers with strong ecommerce performance consistently outperformed average sector growth rates. Companies such as Amazon and Alibaba grew revenues by over 30 per cent in 2017, compared to the mid-single digit growth of the wider retail market. And, apparel mirrors this trend perfectly; we have seen significant growth in pure-play apparel retailers, such as Asos and Net-a-Porter, paired with the persistent decline of high street retailers. We don't expect the growth of the global online apparel industry to slow down any time soon. Generally, analysts expect the online apparel retail market will grow at 10-15 per cent globally over the next three years. And while the growth may start to plateau in markets such as the US and Europe, we expect the driving force of this growth to be in developing economies, in particular India and China, who are exhibiting significant ecommerce growth, and we are increasingly starting to work with brands from these countries.
How does Rakuten Fits Me work to solve fit-related issues? How is it different from other fitting solution providers?
Rakuten Fits Me is a fit-and-personalisation company, which enables leading apparel brands, retailers and merchants to engage with their shoppers, personalise their purchase journey, and enjoy valuable operational insight through a portfolio of solutions cantered on Rakuten Fits Me's expertise in fit preferences. Fit Origin, our core recommendation engine, is the only product in the market that combines shopper data with and retailer's garment data-resulting in a clear, easy-to-understand and unique recommendation every time. Fit Match, the first fit filter on the market, works in conjunction with any other existing site filters and only shows customers clothing that will fit and is in-stock in their recommended size; ensuring a friction-free and fun shopping experience.
Our products give shoppers confidence they are buying the right size that will flatter and fit them, increasing the likelihood of purchase, removing the need for multi-size purchases and driving customer loyalty (80 per cent of shoppers who return their first order, wouldn't shop again). For retailers, this means increased conversion rates (our clients typically see conversions rates jump 2-4x when shoppers use our tool), reduced returns and increased incremental revenue.
There are two other approaches that are fit recommendation providers take. The 'body double approach' uses a shopper's body data to pool it with a group of 'body doubles' that have already purchased with the brand. Based on that historical sales/returns data it will determine what size the customer is likely to keep. While this method can be quick to launch it requires high transaction volume (and reliable data) to offer a recommendation that can be trusted. It doesn't factor in shopper fit preferences or wearer intent.
An alternative approach is the size chart comparison; when the shopper is browsing a product (brand A) -a size chart comparison recommendation approach will ask them what size they bought and kept from a different brand (brand B). They will run size charts against each other and determine which size from brand A they will most likely fit. As size chart data is easy to obtain, this can be an easy integration method for brands who don't have garment data. However, the disadvantages are obvious; vendors that use this approach ask the shopper to consider other brands they have successfully shopped with before (not ideal if you're trying to keep people on a website!) and it isn't anywhere near as accurate.
There is increasing buzz around gender-neutral clothing among consumers. How does Fits Me accommodate fashion changes like these?
While we are familiar with the term 'unisex', the fashion world is now going beyond that and it's not just on the runway where Marc Jacobs and Gucci have combined their usually separate men and women's shows, or in progressive fashion nations such as Korea and Japan. UK high-street retailer John Lewis recently removed gender labels on their childrenswear and this trend is increasingly growing in adults clothing too, with Zara releasing an 'ungendered' collection and H&M selling a unisex denim line. At Rakuten Fits Me, we also don't believe in labels and that's why we are aiming to release a gender-neutral option for all our products in 2018. This would initially be via body shape selection and ultimately through non-binary gender algorithms that focus more on a shopper's shape than on their gender. We think a customer should wear whatever they want, with the best fit. We want everyone to feel comfortable and enjoy shopping for clothes.
How important is it to provide the right fit to shoppers at the first go?
We believe fit is one of the biggest drivers of customer loyalty. Recent research shows that 80-90 per cent of shoppers go back to a brand specifically because of how it fits them, and, therefore, it is incredibly important to ensure shoppers are shown the best size for them, the first time. We believe retailers often forget about the importance of fit. If online shoppers receive items that don't fit correctly, there's a reputational penalty; 85 per cent of women reporting disappointment when clothes don't fit, and 80 per cent of shoppers who have to return their first order, wouldn't shop again.
Who are your major clients? Which geographies do you see increasing potential in for such fashion technology?
Our largest and most well-known customers include Rakuten (Ichiba), QVC, Billabong and Asda George. While we continue to see demand for our fitting technology in the US and European markets, we are increasingly seeing demand from expanding markets, especially in the Asia-Pacific region. Our most recent customer acquisition carries primarily Indian and Pakistani designer fashion clothing. This significant growth in ecommerce, and therefore the growing interest in our products, is supported by research; the ecommerce share of total retail sales in Asia-Pacific is expected to double by 2021.
Which three major factors are shaping the future of fashion retail?
Awareness of fair and ethical practices: We've noticed an ongoing pressure and commitment to driving fair and ethical practices within the apparel retail industry -- whether it's the environmental impact of apparel manufacturing, the wellbeing of those involved in apparel production, or the impact of their every-day shopping habits. This is something we believe will shape the retail industry going forward and become an important driver of brand loyalty-as shoppers become more aware of these issues, they become more loyal to certain brands whose ethos resonates with them. Recent examples include Levi's Waterless Jeans, whereby a technique is used that reduces water use in the finishing process by up to 96 per cent, and the growth of Toms Shoes. Toms Shoes experienced 300 percent annual growth over five years, and they have given away over 70 million pairs of shoes since inception.
Investing in omni-channel: Data is key to delivering a seamless cross-channel experience to all customers. The polarisation in fashion retail between experiential and transactional continues to grow; Amazon are aggressively shifting their focus towards fashion channel and are offering best-in-class search, purchase and logistics. To compete with this, retailers must offer more engaging and interactive experiences in-store and online to keep direct relationships with their shoppers. Channel fluidity is key here-for example, shoppers want to access consistent product and size recommendations both in-store and online, receive relevant promotions and offers, real-time stock availability and the ability to shop online in-store. We believe if retailers can get this right, omni-channel will continue to play a vital role in retail, as retailers invest in ensuring shoppers have truly unique, engaging and enjoyable experiences both offline and online.
Delivering "hyperpersonalisation": As shopper expectations change, we expect retailers to continually invest in delivering "hyper-personalisation;" where data is continually used to provide more personalised and targeted products, services, and content (both online and offline). Online, one area we believe can be significantly improved is search functionality. Since 70 per cent of shoppers use on-site search when shopping online, it is one area which is already being utilised to make the shopping experience more personal. However, there is potential to further enhance this experience. Our recently-launched product, Fit Match, allows retailers to add fit filters to their on-site search functionality which allows customers to search and filter for clothes which will fit them.
AI has a big role to play in ecommerce. What kind of operational efficiency can AI bring about?
AI, once the stuff of science fiction, is already part of our everyday lives. If you use a smartphone or have Alexa in your home; if you use Google Maps or if Amazon suggests products for you to buy, you're a user of artificial intelligence. In ecommerce, AI is becoming increasingly common, even essential, in every part of the shopping experience.
Machine learning, a fundamental building block of artificial intelligence, is the process of having machines learn from data, to create intelligent behaviours such as reasoning, planning, recognising pictures and understanding speech and language. For a machine to learn in this way, it needs huge amounts of data as well as massive processing capabilities. With the continual decrease in cost of processing power and data storage, ecommerce companies have been able to collect and keep more and more data about their business, their products, their customers and their shopping behaviour. Enabled by these massive data streams and the ability of machines to find patterns within them, ecommerce examples of AI abound: customer re-targeting, virtual personal shopping assistants, intelligent search, product recommendations and much more have come to be expected by the internet shopper. Intelligent machines offer great opportunities for improvement in operational efficiency for ecommerce business, as well as technology partners like Rakuten Fits me. Here are a few examples:
Personalisation: Much of the AI employed in ecommerce is used to increase the level of personalisation for the shopper. By understanding customers and targeting them with carefully selected and individual products, it's possible to increase sales, reduce returns, improve stock management and much more. At Rakuten Fits me, we enhance personalisation, using our machine learning algorithms to help shoppers find clothing that fits and flatters their individual body shape and size.
Intelligent search algorithms: Personalised, intelligent search helps shoppers find the right products fast, leading to fewer product returns. At Rakuten Fits Me, we use machine learning to guide shoppers straight to the products that fit and flatter their individual body shape. The result is happy shoppers who keep what they buy.
Image recognition and classification: Machines can process and classify images much faster than humans, and deep learning algorithms enable them to "learn how to learn", giving better and better accuracy over time. To make our fit recommendations, we categorise garments to understand their cut, fit, fabric type, stretch and other properties. Automated image recognition massively improves the speed, throughput and accuracy of the categorisation process.
Analytics and data mining: Data mining algorithms examine and process the huge amounts of data captured every day to find new patterns and derive new information from old. Using data from product catalogues, shopper body data and shopper behaviours, we can show our clients how small changes in their design and manufacturing can increase their sales and reduce over-stocks and logistics costs.
Virtual shopping assistants and chatbots: Running customer service teams is expensive and complex. Automated chatbots and shopping assistants can resolve customer queries and help shoppers find their perfect products quickly. By training machines to help shoppers, the cost and complexity of a good customer service can be controlled.
What according to you would be major contributors to improve customer loyalty for an online clothing brand?
As I mentioned, we believe fit is one of the biggest drivers of customer loyalty; online shoppers need confidence that what they are ordering will fit them and that confidence results in larger order values and more frequent purchasing. Besides fit, we believe a significant contributor to driving customer loyalty is providing a truly personalised shopping experience. An example of this is only showing items of clothing that will fit and flatter the individual; our Fit Match product allows shoppers to only show those items that will fit and that are in stock. A third contributing factor to customer loyalty is providing a seamless omnichannel; shoppers are more loyal to brands that offer a consistent and engaging experience both in-store and online.
What are the top five ecommerce shoppers' trends of the future?
Here are five of the key trends that we think will influence shoppers in 2018:
1. Real People: It is becoming more common for brands to include 'real' people in their advertising campaigns, driven by the rise in bloggers and social influencers. British brands such as ASOS and Misguided have created campaigns specifically around celebrating the real consumer, which have been very positively received; more realistic advertising makes brands much more appealing to a wider audience.
2. Individualisation: About 78 per cent of shoppers are happy to provide personal data in return for a personalised shopping experience. Personalising the shopper journey no longer needs to be done in a divide and conquer way, with large buckets of consumer types being categories into sub-groups. In the data rich world we live in, retailers now have the opportunity to personalise at an individual level, making each shopper experience unique.
3. The always-on consumer: Shoppers are always online. It doesn't matter so much when certain marketing communications are sent out any more. A challenge here for retailers is that their messaging is consistent across all the channels that their customer base is interacting with. As previously discussed, offering a consistent and engaging omnichannel experience will become increasingly important.
4. Social shopping: This is something which has risen dramatically over the past few years and set to keep on growing. Brands now often work very closely with bloggers and influencers to help promote their items. It is now one of the most invested-in channels when promoting new ranges. Social channels are also set to introduce 'buy now' buttons, allowing consumers to purchase straight within applications.
5. Size and fit: About 85 per cent of shoppers say that they would remain loyal to a brand if they clothes fit them correctly. Brands can no longer afford to just offer an online size chart to consumers-technology, such as ours, needs to be implemented to accurately recommend customers which size they should purchase in their store.
Please share details of the last two fiscal years and your expectations from the next two.
In 2017, we launched our core recommendation product, Fit Origin, adding around 100 merchants (+175 per cent YoY), quickly gaining over 2 million first-time users. Over the next two years, we expect to continue to grow at more than 100 per cent YoY driven by launching new products, new major ecommerce platform plug-ins, our new partner programme and regional expansion. At the same time as developing and delivering a bespoke product to Rakuten's Global Marketplace (the 3rd largest marketplace in the world with over 40,000 apparel merchants), the last two years have seen major investment in re-engineering our core product to provide the most accurate, easy to use fit recommendation in the market, and revolutionising the customer experience with the our recently launched product, Fit Match. We launched our new pricing in 2017 with a hierarchy of editions to suit all sized retailers, while still allowing for customisability and flexibility.
What are the future plans?
Our focus in 2018 and beyond is on improving the shopper experience, both online and offline. We are motivated by providing tools that ensure consumers can shop with confidence and enjoy every interaction. We will continue to capture and share invaluable consumer and product insight with retailers, allowing them to build a relationship with every individual shopper and continually personalise, and improve, their shopping experience. (HO)