The world of fashion changes.
It is fast-moving and the people within – from designers to buyers – all need to make sure they look ahead to catch the latest changing trends.
The way we find and buy items has shifted dramatically. In the last few years, no other industry has apparently taken more of a hit than retail.
Of the list of emerging technologies (AI, blockchain, IoT, 3D printing, and AR/VR), artificial intelligence has been at the forefront of disruption for every industry. Perhaps one of the most prominent ways fashion and technology have been integrated is the ability to turn a diverse set of data into engaging, enriching information.
Some of the biggest names in the fashion industry – from H&M to Tommy Hilfiger – are now investing in algorithms that help suggest styles to their customers. A plethora of AI-based start-ups are also helping one end to the other – from retailers to consumers – take the guessing out of the game.
Based on a report by Tractica, the global AI software market is expected to grow massively in the next few years, with revenues increasing from around 9.5 billion to 118.6 billion USD by 2025. Also, according to a study by Juniper Research, global retail spending on AI will grow to $7.3 billion per year by 2022. This is up by 5 billion, from an estimated $2 billion in 2018. Moreover, recent research has found that in the next five years, retailers will also be heavily investing in other related technologies like blockchain and the Internet of Things.
The many benefits of AI in fashion
There is no denying that artificial intelligence has been dramatically shifting the way business is done. From the use of predictive analytics in business to computer vision in identifying product attributes, there are a myriad ways AI has been benefiting the field of fashion. Some of the ways down below illustrate just how powerful applying AI for fashion is.
- Customization – Just as how Netflix, YouTube or Amazon has the ability to suggest similar shows or products, AI in the fashion industry can do just the same. With e-commerce becoming a central way that people shop, there is more data about the consumer being tracked than ever before. Many successful fashion websites are able to keep a log of the browsing patterns of their customers, and in turn suggest similar items based on color, style, and design.
- Improved customer service & communication – Calling and emailing, while still prevalent amongst many businesses, are slowly becoming a thing of the past. In the last few years, the emergence of chat-bot technology has significantly increased conversion and communication between the customer and fashion brands. From IBM Watson to Hubspot Chatbot, there are a multitude of solutions that help track leads, answer questions, and even give product recommendations.
- Better buying and planning – For many fashion buyers and planners, a difficulty that is commonly faced is knowing exactly which material to buy for designers. Ordering too much of one thing might be detrimental to the business, especially if that product does not sell as well as they hoped. Yet, with advanced predictive analytics, buyers can effectively learn from customer behavior, and in turn plan with greater accuracy. By knowing which items are best and worst sellers, you can buy and plan with precision.
- Automating operations – One of the greatest benefits in using artificial intelligence is the ability to automate mundane tasks. A majority of company working time is used for menial data entry, calculations, and other efforts that can easily be run by artificial intelligence alone. This is a huge asset to fashion brands, as they can assess margins with greater accuracy and organization using AI, requiring less man-power. This frees up many retailers to focus on more important matters like strategy and execution.
- Managing inventory – A huge problem that retailers face is over-ordering and losing out on profit due to the unsold product. It has always been quite tricky to keep business moving, yet not hold too much that you are left with wasted items. Today, companies like Chain of Demand use machine learning algorithms to make more accurate predictions and choices. While demand forecasting techniques have been around for years, traditional methods only used historical sales data. The majority of calculative work needed to be done by humans and with limitations when the data sets go over 10,000. Yet, with machine learning, you can reduce forecasting errors by up to 50%, and are not restricted to how many data points and sources are used, thereby making more precise predictions.
- Reduced returns – Apparel returns take approximately 3x longer to inspect than other verticals. This makes operational costs quite high. However, with the help of AI, retailers can help customers to make more informed purchase decisions (as described above). This increase in customization and improved communication prevents dissatisfaction, and in turn reduces the return rate. Retailers lose about $642.6 billion every year from preventable returns, which is why the use of AI would be incredible.
- Improved product discovery – With the help of computer vision – an extension of machine learning – shoppers are now able to upload a photo of a product that they desire and get instant feedback on whether that item exists in the specified stores. There are also solutions that help scan the photo to give recommendations of where they can buy said product and at what retailer. One great example of this is Google Lens, which allows mobile users to snap a photo of a product, then find and buy similar styles right from their smartphone. In the same way, Pinterest’s Lens uses AI technology to search for visually similar pins across their database.
Major fashion retailers using AI
Even though AI has been around for several years now, the technologies that are currently being applied to fashion is still in its early days. While there is still a long way to go until in-store artificial intelligence is fully realized, the following companies are just a few examples of those that are leading the way.
Alibaba
Since 2018, the Chinese retail and technology multinational, Alibaba Group, announced the idea of “new retail.” It was the idea that they would revolutionize the way we shop completely, with the notion of e-commerce and data boom changing our consumer behaviors. It was during this year that they opened their first “FashionAI” store as a means to simplify the shopping experience for customers.
The key features for the store include intelligent garment tags, smart mirrors, and omnichannel integration. For the first, every product in the store contain special RFID (radio-frequency identification) tags and Bluetooth chips which carried specialized information within them. This can help give greater information on what items (based on color and size) are being sold the most and other deeper insights about the customers. In addition, the garments also contain what are known as gyro-sensors, which help to determine how an item is being touched or moved.
Smart mirrors (the second feature) are said to be located on every sales and changing room floor. Not only will they have touch screens that relay information on whether or not a person is inside, they will also help give information about the item the customer has brought into the store. These mirrors can also suggest other items that may go well with their item, which allows customers to fully customize and try on a multitude of items from the mirror alone, without having to carry every single piece of clothing they desire.
Finally, omnichannel integration will allow FashionAI to be connected to the Mobile Taobao app, which also contains a virtual wardrobe allowing customers to view the clothes they tried on. This way, consumers are able to continue shopping for styles they were recommended or that fitted in the store.
Amazon
With Amazon being the tech powerhouse that it is, growing into a titan through its recommendation systems, it is not a surprise to see that they are also involved in using AI for fashion. Amazon has developed an algorithm that is capable of designing clothes through the analysis of many images. It copies the styles and applies it to a new item from scratch.
It also has what is known as Amazon’s Echo Look, an Alexa fashion assistant that keeps track of what is in your wardrobe, and in turn gives recommendations on what to include in your outfit. Using machine intelligence, the technology here can help you stylize better.
H&M
Although the company is one of thousands that have been affected by the retail apocalypse, H&M continues to hold on and thrive by investing in the big data boom. One interesting way they are doing so is through the analysis of receipts and loyalty card data. This information helps them customize and tailor the merchandise for each specific store by analyzing the returns, receipts and loyalty card data to tailor the merchandise for each store.
The retailer has also started to offer personalized recommendations for online shoppers, with plans to bring over similar technology into its bricks-and-mortar stores with the implementation of RFID.
Moreover, with Google, they have also created Coded Couture, a technology that allows people to create one of a kind designs based on their lifestyle. As they write on their website, Coded Couture is where, “Art and code work together. Simply install our app on your phone which translates a week of your life into a one-of-a-kind design. Creating a dress with your unique personal story to it.”
Tommy Hilfiger
IBM has teamed up with Tommy Hilfiger and the Fashion Institute of Technology (FIT) Infor Design and Tech Lab for a project called ‘Reimagine Retail’ – a way to help give retailers an edge by equipping them with skills in AI design.
Students of FIT were given access to IBM’s AI research, from computer vision to natural language processing, and used the plethora of data to design better personalized outfits. They found that the use of AI allowed design teams to reduce lead times and generally increase their creativity. The ability to analyze and learn from thousands of images and videos quickly using the power of AI gave the designers greater insight into creating the right product, for the right person.
ASOS
The company is another retailer that integrated AI into its system, where they introduced a new tool to enhance the shopping experience. This new technology helped consumers determine the right size, allowing them to make greater informed purchases. The technology, known as ‘Fit Assistant’ combines a platform that goes through a database of garment information and purchase histories to correctly adjust the right fit.
Final thoughts
There is no doubt that AI is revolutionizing the fashion industry in ways no one would’ve imagined. In this rapid change retailers, manufacturers, designers, and managers alike are learning to benefit greatly by harnessing the underlying power of AI: machine learning.
Companies like Chain of Demand are some of the several start-ups that are standing at the forefront of this disruption. Through the use of AI and big data, fashion retailers are able to use such solutions to predict best and worst sellers with better accuracy than ever before. Not only does this open a field of opportunity for growth in profit, it also leads the way to greater sustainability by reducing inventory waste.
