Today’s young shoppers increasingly want personalized goods. According to an IBM study, 52% of Gen Z females would like to see tools that allow them to customize products for themselves.
Fashion industry is reigning among females from ancient history and prolonging that popularity today also among Gen Z females. As fashion is constantly wavering in trends, it has become a dominant factor to alter the technologies for faster customization.
According to an Forbes study, The fashion industry did $3 trillion in business, 2% of global GDP in 2018; e-commerce fashion amounted to $520 billion in 2019.
Capgemini, the French multinational company, estimated that global annual spending on AI by retailers is projected to hit $7.3 billion by 2020, and AI could help retailers save a potential $340 billion annually by optimizing processes and operations
There are many factors in which AI is booming in fashion area and they are:
AI to be part of designer :
In 2016,Project Muze, an experiment from online fashion platform Zalando and Google, explored the creative use of machine learning in the field of fashion. It’s like being the muse for clothing exploring the customer's personality and interests.
The design and patterns with the right color combination are the key point to design a costume to make it attractive among the customers. Trends in the fashion industry change very fast with new designs or patterns come every day in the market. Designers need to keep pacing with new styles and AI algorithms can analyze designs through images to model popular styles.
How AI is influencing Brands :
In 2018, Tommy Hilfiger announced a project, known as “Reimagine Retail,”partnership with IBM and the Fashion Institute of Technology(FIT).
IBM’s AI research tools were used to analyze customer sentiment with each clothing item and runway images as well as to identify key themes in patterns, silhouettes, colours and styles. AI perpetuated the quick analysis of a large database of both text and visual data, something that would be difficult or impossible for any designer to do so in an objective and precise manner.
Instead of manually scanning Instagram and Pinterest, we’re pulling insights that brands can use again and again, from massive data pools,
Global Cognitive Offerings Lead at IBM.
The AI tools looked at 15,000 images of Tommy Hilfiger products and 600,000 runway images that were publicly available and 100,000 patterns from fabric sites.
According to Tommy Hilfiger’s Chief Brand Officer the project was a “successful integration of fashion, technology and science”.
The purpose isn’t to replace the creative process, that gut feeling, human eye or impulse with a series of objective 0s and 1s. The purpose is to reduce the “brain clutter”- the laborious tasks that delay the creative process said Chris Palmer, the global cognitive offerings lead at IBM
Another example is Stitch Fix,
Stitch Fix, an online apparel retailer, thinks algorithms are the future of designing garments and has begun to bring those in market.
Using all that data, an algorithm then mines Stitch Fix’s inventory to find pieces that match their profile.After the algorithms do their work, human stylists take over.
As the market is total online,Almost every quarter, the company announces improvements to its algorithm. In July, for example, the company introduced a new recommendation engine for its Direct Buy program, which delivered promising results. Management said, "Compared to our prior Fix-based recommendations, clients purchased more items on average, bought products with higher average prices, and converted at higher rates."
Stitch Fix meticulously catalogs all of its inventory and breaks down each garment into anywhere between 30 and 80 granular characteristics, such as color, length, how many buttons it has, what shape its hem has, what fabric it’s made from, what type of pattern it has, sleeve opening, collar type, and so on. Because so many theoretical combinations can exist, an algorithm is needed to analyze them.
AI-intensify fashion design & manufacturing :
There can be up to 52 seasons for clothing and constantly contouring in fashion and design, it is difficult for retailers to consistently keep up with the most current trends and predict consumer preferences for next season.Traditionally, retailers base their estimate of current year’s sales on data from the prior year. But this is not always accurate because sales can be influenced by many factors that are hard to predict, such as changing trends.Therefore, AI-based approaches for demand projection, however, can reduce forecasting error by as much as 50 percent.
Once the clothes are designed, AI technologies can also play a role in textile manufacturing. Fashion manufacturers are innovating the use of AI to help improve efficiency of manufacturing processes and augment human textile employees.
AI-enabled machines and robots can easily stitch the fabrics with perfection while at the same time it can also detect faults in fabric and offer quality assurance to ensure that the actual design shades will suit the new colors.
AI in inventory and supply chain management:
AI is facilitating speed-up by improving routes, cutting the logistic supply and shipping cost.Using the automate logistics and supply chain processes for the faster delivery or finding alternate routes for vehicles derailed by unforeseen circumstances such as bad weather or road construction.
Machine learning algorithms are being used to make more accurate predictions of inventory demand and therefore reduce wastage or eliminate last minute purchases to meet unexpected spikes in demand.
Chatbots/AI assistants :
The AI chatbot communicates with users, initially greeting them by name and through a series of questions proceeds to determine what types of products they are interested in within the company
The chatbots are mainly used for :
- Responding to customer service inquiries and providing suggestions related to product searches through a social media messaging platform
- Helping users navigate products online and/or in-store and routing customers to sales representatives
- Virtual assistant to encourage exercise/behavior adherence
AI Fashion Visual Trial:
AI-enabled clothes and outfits are not only tailored for different occasions and weather, but also to the user’s style, body type, colours, and the latest fashion trends.
Van Heusen created a retail environment complete with a “Virtual Trial” mirror which lets users see how outfits would look on them by simply scanning the item’s barcode and standing in front of the mirror as virtual garments are projected onto their reflection.
AI in Online Fashion with Recommendation in Ecommerce :
AI is also playing a game-changer role in online shopping and Ecommerce business. While browsing or searching the fashion items on e-commerce sites, AI recommends the other similar items, as per your color preference, budget and other attributes.
Machine learning algorithms are analyzing the data of your filtering behavior and what kind of products you are looking for. Analyzing your search history data it recommends the other suitable items you probably should check.
As machine learning is innovating its algorithm in terms of neural networks and deep learning, there are a plethora of innovations in fashion which are yet to be seen.