Similarly to almost every single industry, the fashion industry has been stormed by the ongoing technological revolution. Recent evolution in disruptive technologies such as AI machine learning and others are leading us all towards the 4th Industrial Age.
In the fashion sector, what is mostly seen, is how fashion is being used to improve and personalize the relationship of the fashion industry with its users. AI is enabling brands to better personalize their offering to consumers, for example via recommendation engines showing certain kinds of styles and garments based on the user’s previous browsing. This is something that might by now, quite evident, to most of us, all the time glued to all kinds of screens.
Part of this sweeping change happening in the fashion industry is the example of Woodhouse Clothing, who recently announced how it has implemented a new AI-powered personalisation scheme. Woodhouse’s scheme is using Nosto’s artificial intelligence to personalise web and email experiences, thus enabling Fashion shoppers to make a purchase in quite a unique way.
According to their recent press release, the introduction of their AI-based personalisation means shoppers who visit this men’s online fashion retailer, Woodhouse Clothing, are now 44% more likely to make a purchase. The new technology, which works across both mobile and desktop, is also helping to increase the retailer’s average order value, which is up 7%. Abandoned shopping carts are also down by 3%.
Woodhouse technology was developed by Nosto which uses advanced AI machine learning algorithms and other statistical techniques to predict and automatically deliver the most relevant shopping experiences to its online visitors in real-time. Thanks to Nosto, Woodhouse, which sells fashion from over 50 leading brands including BOSS, Armani and McQ, is able to automatically display real-time personalised product recommendations and onsite pop-up messages based on visitors’ onsite browsing behaviour. It is also now able to deliver personalised email campaigns using Nosto’s platform.
“At Woodhouse we understand that all of our customers are different and unique – and we needed a way to personalise their experience by presenting the most relevant brands, products and messages to each individual,” said Sophie McFegan, Woodhouse Visual Merchandiser. “Nosto has allowed us to really dive into the personal approach of online shopping, creating unique offers and recommendations tailored specifically to our customers.”
Nosto enables personalised product recommendations
By analysing data it collects about which items are commonly bought or browsed together, Nosto’s platform helps Woodhouse to enhance the shopping experience on product pages – by automatically displaying the most relevant cross-selling recommendations. Individual visitors are recognised and presented with recommendations personalised to their brand, style and product preferences, while those who are completely new to the site are presented with recommendations based on real-time bestsellers.
Personalised recommendations have also been added to the shopping cart page to remind shoppers of items that had previously sparked their interest but were not added to the cart.
Personalised behavioural pop-ups are used in an appropriate and well-timed way to enhance the shopping experience while making sure visitors do not feel pestered by them. For example pop-ups offering discounts are only shown on the brands that shoppers have shown most interest in. Or they are used to provide key information such as the start and end of sales periods or the last ordering dates for Christmas.
Welcome pop-ups are displayed only to new site visitors after a couple of pages have been browsed to avoid them feeling harassed. And pop-ups for mobile and desktop often incorporate different images to prevent boredom or irritation among those who browse the site on multiple devices.
Woodhouse is also using Nosto to personalise its email campaigns to increase sales and customer loyalty. For example shoppers with abandoned shopping carts or browsing sessions are automatically retargeted with emails showing them products they had left in their cart or shown an interest in before leaving the site. This has helped to trigger an increase in email click through and conversion rates.
Transactional emails have also received the personalisation treatment by adding order related recommendations that suggest “complete-the-look” follow-up purchases. Nosto’s personalisation engine uses the power of big data to build a deep understanding of an online retailer’s store and every visitor interacting with it, allowing it to use machine learning to predict and automatically deliver the most relevant content to those visitors. It helps to maximise e-commerce conversions, average order value and customer retention.
Hernaldo Turrillo is a writer and author specialised in innovation, AI, DLT, SMEs, trading, investing and new trends in technology and business. He has been working for ztudium group since 2017. He is the editor of openbusinesscouncil.org, tradersdna.com, hedgethink.com, and writes regularly for intelligenthq.com, socialmediacouncil.eu. Hernaldo was born in Spain and finally settled in London, United Kingdom, after a few years of personal growth. Hernaldo finished his Journalism bachelor degree in the University of Seville, Spain, and began working as reporter in the newspaper, Europa Sur, writing about Politics and Society. He also worked as community manager and marketing advisor in Los Barrios, Spain. Innovation, technology, politics and economy are his main interests, with special focus on new trends and ethical projects. He enjoys finding himself getting lost in words, explaining what he understands from the world and helping others. Besides a journalist, he is also a thinker and proactive in digital transformation strategies. Knowledge and ideas have no limits.