You can’t run and definitely cannot hide from the fact that Artificial Intelligence is taking over the fashion world by storm. With yearly Artificial Intelligence spends predicted to reach a record high of $7.3Bn by 2022, data is governing decisions in all aspects of the industry. A sector with an astonishing amount of consumer and market data, Artificial Intelligence is enabling businesses to not only amp up their go-to-market speed but also lowering costs at each stage of the logistics chain. Technology has the potential to drastically improve forecasting, inventory management, production planning, merchandising, warehouse automation and even impact delivery models. In this post, we’ll take a look at some of the ways Artificial Intelligence is transforming the fashion sector.
1. Personal styling at its best
Inherently, fashion is all about personalisation. The industry has realised the opportunity in the “styling” aspect in 2 parts- new product items and styling the existing customer wardrobe. According to a report, 73% of customers prefer to shop with brands that recommend by taking their personal preferences into account. Levi’s launched a “Virtual Stylist” recently which delivers recommendations by experts 24/7/365 via a chatbot in Facebook Messenger. The AI algorithm helps consumers find the right fit with questions such as hip/thigh fit with True Fit and gives recommendations by scanning their entire product range. Amazon’s Echo Look camera is a personal stylist that uses Artificial Intelligence to give “opinions” on user clothing trends, fit and styling. Its Stylecheck feature can choose the better outfit between two options and even recommend options to complete a look from Amazon.
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2. Inventory management gets predictable
Inventory management is primarily driven by demand prediction. Retailers need to keep enough stock for the optimum business functioning, but also keep the cash reserves and unsold product in check. With AI and machine learning algorithms, historical data is analysed to forecast and reduce errors by up to 50%. With warehouse automation, delivery times are getting shorter by analysing route data to give customers “same-day” delivery. Artificial Intelligence-powered inventory management is providing efficiency while reducing costs from excessive inventory in unproductive locations and slow-moving products. One of the biggest benefit AI provides – an extensive insight into customer demand which can guide new strategies and customer acquisition.
3. Dynamic Pricing is here to save the day
Historically, pricing has always been determined by analysing warehouse costs, internal sales and customer data, apparel buying trends and own inventory management. Manually, this is a tedious process and companies find it difficult to keep it in check with changing trends. With AI, Dynamic Pricing is being embraced by retailers today. It’s a flexible pricing strategy that works on pricing products based on analysing customer data, competitor pricing data along with internal sales numbers. The more the data analysed, the optimal the prices are. Companies are no longer dependant on stocking and inventory management and are able to determine the best price at any given time. AI can also analyse customer patterns and buying behaviour dynamically to alter prices based on current behaviour. It is truly making eCommerce pricing flexible, scalable and automated.
4. Fashion photography gets the Artificial Intelligence push too
Photography is a major driver in the customer buying journey in fashion. Customers want to see their clothing in the highest quality possible and make a purchase decision. Model photography is popularly used by retailers as it allows brands to deliver a rich and alluring shopping experience. With over 52 micro seasons to cater to in a yearly calendar, it leaves most businesses with a massive supply chain to optimise, logistical and post-production budgets to bear. But companies such as FlixStock and FlixLook are changing the game with Artificial Intelligence-powered model imagery that can produce images at a fraction of the time and cost. It creates consistent and high quality dynamic and versatile images, perfectly suited for fast fashion. Everything from makeup, styling to edit is taken care of, and retailers get perfectly created model photography for their product catalogues. Flixstock and FlixLook can also pair accessories using AI recommendations and even create entire lookbooks for product collections.
5. Not just online, offline retail gets AI-fied
London based retailer Farfetch is testing what it calls “the store of the future” complete with automatic customer recognition, RFID racks to track inventory management and purchasing trends, digital mirrors that give customers opinions about sizes, looks, clothing combinations of different colours and styles. The company is developing its own technical OS to improve retail productivity by capturing customer data to enhance interactions and ultimately shorten the acquisition cycle. Chinese eCommerce giant Alibaba is also testing a similar concept in partnership with fashion brand Guess in Hong Kong. Customers can add products to their online cart via QR codes in the store and even try out different sizes in the smart mirror without even leaving the fitting room! The mirror provides suggestions based on previous purchases and browsing data and customers can checkout their items via the online app.
6. AI designers are here!
Artificial intelligence and machine learning algorithms could never replace the creativity and technique of a designer- that’s always been the fashion industry’s central thought. It can never take over the expertise that a human mind has. But ventures such as Coded Couture and Moda Rapido are proving the fashion industry wrong. Coded Couture- a label powered by Google and Ivyrevel designs a “Data Dress” for users after learning about their personality, habits, use case scenarios, expectations for a week via an app. The app ( released later this year) tracks daily activities to create a unique dress for each customer using AI and machine learning. Indian fashion giant Myntra already has an entire line of AI-generated designs called “Moda Rapido” which has reduced their lead time to just 7 days in some collections!
7. Return rate reduced- a multi-billion dollar save
Clothing returns are one of the biggest and most expensive problems plaguing the apparel industry. An estimated $642 billion is lost by retailers annually from preventable returns. Add to the 3x longer inspection timeline and operational cost skyrocket. One of the primary reasons contributing to this loss – customers often return clothes due to wrong size and fit. Companies such as Asos, Myntra and Intellistyle are using AI to predict the right fit by getting customers to answer a series of detailed questions and combine them with previous buying data. Stitch Fix- another player uses AI to make personalised recommendations based on trends data to create unique experiences for customers, thereby reducing returns significantly. AI is helping customers to make more informed decisions thereby decreasing return rates.
AI is influencing every part of the fashion ecosystem and retailers will continue to leverage its advancements to increase efficiency, save expenditure, customer satisfaction and finally give the users – the best shopping experience. Ultimately, the customer benefits the most from AI!
Have more to add to our list? Hit us up in the comments!