Machine Learning in Fashion Industry: Applications and Future

Machine Learning in Fashion Industry: Applications and Future

Shubham Anil Jain
Sr. Consultant
Cent Edge Solutions LLP, Bangalore, India
Email: shubhamajain125@gmail.com

Introduction:
It is the fact that, the pandemic has been destructive for an enormous majority of the industries in existence. And the fashion industry is not apart from this, but researchers are initiating that this is one of the many applications of important tool known as machine learning.

Machine learning is defined as a branch of artificial intelligence (AI) and computer science which highlights on the application of data and algorithms to copy the way that humans learn, step by step improving its accuracy. Currently, it is seen that the machine learning industry is powering many of the companies, and even we can observe that power in many new places. Machine learning application in retail industry is really doing well, and the fashion industry is doing a lot better due to this. There are lots of applications of this technology to the industry, and it is currently a important component of what a bright future looks like. It gives many advantages that make conducting business better and more opportunistic for these companies.

Applications of Machine Learning in Fashion Industry:
As we know that fashion, as like technology, never remains still. It constantly goes on changing evolves to serve the different tastes, global trends, and now in the way to inculcate the latest in technology such as Machine Learning for the improvement and better of the fashion industry. Below are some of the applications of machine learning fashion industry:

a) Supply Chain Management:
SCM is probably an overlooked aspect of the fashion industry. It’s complex in nature, with many steps starting from production to retail, each of the steps which can benefit greatly machine learning. Machine learning in fashion industry can help forecast the demand more accurately, which can help the organization to minimize overproduction, also for reducing the waste, and make fashion more sustainable in nature. ML can also benefit in identify potential issues in the supply chain before they become a huge problem in process, also helps to ensures the smooth operations and timely deliveries of the goods.

b) Designing and Manufacturing:
Nowadays, coming up with this many new and attractive apparel designs and then basically making them in a timely manner can be a very tough challenge for designers and manufacturers who are involved in the process. And when it comes retailers, due to trend-driven aspect of fashion, it can make estimating customer demand for their new line of products very tricky, to say the least. So here, with no surprise that, nowadays, huge number of fashion companies are taking and moving towards to AI and machine learning for help. Machine learning driven demand forecasting has been proved to minimize forecasting errors by up to 50%. Even machine learning in fashion industry has improved garment manufacturing leads to increase efficiency and time-to-shelf because of automated quality control as well as defect detection.

c) Retail Strategy:
One of the worst things that fashion retailer can experience is ending up with unsold stock. Unfortunately, this is a very common situation than most people may realize. As per the reports, in 2018 H&M’s big supply chain lead times coupled with the brand’s incapability to reach out consumer preferences, which results in $4 billion of unsold inventory. To overcome this problem, many of the multinational fashion retailers took the help of machine learning.

So, basically maintaining analyzed store purchase history at one of the stores in Stockholm, the company comes to understand regarding its inventory stocking strategy, which was severely lacking. For example, in this particular store, H&M was keeping basics for men, women, and children, even though their major customer crowd was mostly women. By eliminating its menswear line due to less walk in of men and instead paying more attention on stocking more trendy items for women, the store was in a position to reduce its stock by 40%. After that, H&M copied this same experiment across its other stores, too.

d) Personalized Recommendations:
Recommendation engines are being considered as a good tool for creating customized marketing for the retail customers, as per their past preferences and forecasted future behavior. For example,  customers who has buy a particular white shirt are also tends to purchase a jean jacket that fit well with it. In this case, that retailer might want to suggest that a customer who has either looked at or purchased the white shirt also look out the jean jacket by saying “customers who bought this white shirt also purchased this jean jacket.” So, this kind of methodology allows fashion retailers to personalize recommendations for individual consumers, rather than using more traditional manual or rules-based approaches to target clothing advertisements based on demographics. All this can be done through the application of machine learning tool.

e) Product Discovery:
Nowadays, the internet has provided customers with easily access to the thousands of e-commerce stores, and in consequence, millions of products and stuff available to them. As per the research it is  found that the most if the people search on an online clothes store, the more exhausted they happens, and then they decided to take a break from online shopping. So, machine learning is useful for fashion retailers, to help customers navigate their product category and surfacing the most relevant results. Machine learning technologies can make product discovery very smooth and easier is by augmenting search.

Future of Machine Learning in Fashion Industry:

1. Currently, seeing the craze and technology, it is being clearly visible that the future of machine learning in the fashion industry is going to be super amazing. Machine learning tool has the capacity to evolve the way we create, design, and shop for clothes.
2. With the help of machine learning algorithms, it can easily study huge amounts of fashion data, like different kinds of trends, customer preferences and taste, and social media posts, to provide valuable updates to designers and retailers. Because of this, it can define help them make more accurate and precise decisions about what styles and designs to create and stock.
3. One aspect where machine learning is already making an impact and going to evolve e more in future is in customized recommendations. By studying a customer’s browsing as well as purchase history, machine learning algorithms has the power to easily recommend dressing items that matches with their unique style and preferences. Due to this feature, it makes good shopping experience and make it more convenient and enjoyable for buyers, and helps retailers increase sales.
4. Another aspects of machine learning in fashion is virtual try-on application. With the help of computer vision algorithms, buyers can actually see how clothes would look on them without actually physically trying them on. This feature can save time as well as can make online shopping more exciting and interactive.
5. Even in future we can see that, machine learning can also help with sizing procedure. By studying the body measurements and fit priority, algorithms can easily provide proper and correct size recommendations, which will definitely reduces the need for returns and exchanges. This is a good feature for both customers and retailers.

Conclusion:
So, to summaries here, with the proper combination of Artificial Intelligence and Machine Learning, the fashion industry can be inevitable, very potential, and limitless. As we are moving towards the new era of fashion, one thing is very definite that machine learning fully ready to redefine the industry, offering a mixture of creativity, convenience, and more towards customer-centricity. This type of tool also provides the great opportunity for various brands and retailers to go ahead with good and better decisions which will be based on reliable forecasts, to get the correct inventory, in the right location, with the right price.

References:

1. September 27, 2023, The future of AI and Machine Learning in the fashion industry https://www.myhubble.money/blog/the-future-of-ai-and-machine-learning-in-the-fashion-industry
2. Fashion Machine Learning Applications and Examples https://intelistyle.com/fashion-machine-learning-applications-and-examples/
3. Aptean Staff Writer, Apr 3, 2023, How Machine Learning Is Shaping the Retail Fashion Industry https://www.aptean.com/en-US/insights/blog/machine-learning-in-fashion-industry
4. May 31, 2021, Key Applications of Machine Learning in the Fashion Industry https://blog.dataiku.com/key-applications-of-machine-learning-in-the-fashion-industry
5. January 20, 2022, Machine Learning Is Crucial to Improving the Fashion Industry https://xpresso.ai/resources/blogs/machine-learning-is-crucial-to-improving-the-fashion-industry/

FAQs:

Q1. How can machine learning be used in fashion?
Ans: Machine learning is being used in fashion for the activities like, product suggestions, shopping reminders to complete the transactions, changing addresses and arranging logistic vendors.

Q2. Is Zara using a machine learning?
Ans: Yes, Zara uses machine learning programs and algorithms to simply analyze sales data, to reach out social media trends and customer feedback regarding the products to forecast what products will be in demand in various regions.

Q3. Can we promote fashion brands with the help of machine learning? 
Ans: now-a-days, machine learning tool have the power to create and merge data from thousands of images, which can be used simply to figure out trends in such a accurate manner that would be bit difficult for a designer. Also, many fashion brands utilize this data as a base of inspiration, or even to suggest outfit designs.

Q4. Does Flipkart use machine learning?
Ans: The company basically tends to analyze the outcomes from customer reviews and users buying patterns to forecast or identify the market demand with the help of Artificial Intelligence and Machine Learning-based models. Even, Flipkart uses the technology of AI & ML to fast their delivery process also.

Q5. Is Nike uses machine learning?
Ans: Yes, Nike uses machine learning to basically gather user data with its apps, like NIKE SNEAKERS, Nike Training Club, and the Nike app. This data is being used to figure out important insights and help Nike in finalizing which designs to make and which products to fill up in which stores.

Q6. Which fashion brand uses AI?
Ans: The big fashion players who are using AI in their business models are Zara, H&M, Dior, Macy’s, and Nike.

Q7. How is AI used in fashion industry?
Ans: AI is used in aspects of design and product development. It is being used for trend forecasting for various elements like color, fabric, patterns and cut as well as analyzing past and future performance KPI.

Q8. What is an example of AI in fashion industry?
Ans: The simple examples of reactive AI in the fashion industry are visual search, customized product recommendations and importantly for price optimization.

Q9. How big is the AI in fashion market?
Ans: The global AI in fashion market size has grown to $0.91 billion in 2023 with a  compound annual growth rate (CAGR) of 40.0%.

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Mazharul Islam Kiron

Founder & Editor of Textile Learner. He is a Textile Consultant, Blogger & Entrepreneur. He is working as a textile consultant in several local and international companies. He is also a contributor of Wikipedia.

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