Valued at over 3 trillion dollars, the global fashion industry contributes to a healthy 2% of the global GDP. Be it through the sewing machine or the eCommerce market, the fashion industry has always been the pioneers of technological innovation. In the 21st century, technology-driven innovations like artificial intelligence (AI) or machine learning in fashion industry are changing every aspect of this forward-looking business domain.

The use of AI in fashion industry of 2020 has become so well entrenched that 44% of the fashion retailers (who have not adopted AI) are today facing bankruptcy. As a result of this, global spending on AI technologies by the fashion & retail industry is expected to reach $7.3 billion each year by the year 2022.

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What is the relevance of technologies like AI and machine learning for fashion industry across the globe? In the following sections, we shall look at how popular fashion brands are utilizing these technologies along with some of industry use cases and benefits.

Artificial Intelligence & Machine Learning – Impact in the Fashion Industry

Supported by the easy availability of big data, customer personalization, and other services in fashion companies are simply no longer feasible without the use of AI in fashion. According to McKinsey, the leading 20% of the global fashion brands are generating 144% of the industry profits. This means that for any fashion brand, it needs to be in the top 20% to be a profitable business. Driven by this necessity, fashion brands are investing in AI and ML technologies to remain relevant in a highly competitive marketplace. 

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Now that we have understood the importance of AI and machine learning for the fashion industry, here are some of the ways in which these technologies are making an impact:

Apparel designing

With more sophisticated data collection, fashion brands are using technology to understand customer needs and design better apparel. For example, a Germany-based fashion platform, Zalando (in partnership with Google) is using AI-powered fashion designing that is based on the customer’s preferred colors, textures, and other style preferences.

Manufacturing process

Fashion brands using AI and ML tools are now able to identify fast-changing fashion trends and supply the latest fashion accessories to retail shelves faster than the “traditional” fashion retailer. As a result, leading fashion brands like Zara, Top Shop, and H&M are quicker in providing instant gratification to retail customers by recognizing seasonal demands and manufacturing the right supply of the latest clothing.

Virtual merchandising

AI-enabled technologies like augmented reality (AR) and virtual reality (VR) are now closing the gap between online and in-store shopping experience. For example, in-store AR allows shoppers to access any merchandise through digital media. Using VR technology, fashion brand, Tommy Hilfiger was able to create a virtual image of its pop-up retail store.

But how are fashion brands successful in implementing these technology-based capabilities? Using a variety of AI and ML algorithms. Let’s evaluate some of the popular algorithms in the next section.

How AI and ML Works For The Fashion Industry

Among the primary uses of AI and machine learning for fashion industry is through the deployment of chatbots using which fashion brands can gather information about customer desires and intended purchases. For example, an online shopper looking for a new shoe or dress can simply interact with an intelligent agent through a website or mobile app. Some of the popular fashion retailers using chatbots include Burberry, Tommy Hilfiger, and Levi’s. 

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Apart from large eCommerce retailers or brands like Amazon, even small-time fashion retailers are now using machine learning algorithms to understand fast-changing customer needs and expectations. For example, an online personal styling company, Stitch Fix is using ML algorithms to improve customer experiences along with supply chain management.

Among other applications, machine learning algorithms can accurately predict inventory demand thus reducing wastage and unsold inventory costs.

In short, AI for fashion is transforming how fashion companies are designing and manufacturing their products as well as how they are marketed and shipped to the customer.

Next, we shall look at how some of the key fashion players are utilizing AI and ML technologies with some notable use cases and case studies.

Fashion Brands Using AI and ML – Use Cases/ Case Studies

Be it machine learning or artificial intelligence, their impact on fashion styles and branding has been immense. Here are examples of four leading fashion brands that have and are leveraging from these technologies:

Alibaba

The China-based fashion retail giant, Alibaba have since 2018, adopted technologies that have revolutionized their shopping experience. With the launch of their first FashionAI store, the company introduced in-store features including smart garment tags, intelligent mirrors, along with Bluetooth chips embedded within every product.

Thanks to these technologies, customers benefited from AI-driven fashion recommendations catering to their style preferences. Additionally, omnichannel technology allows FashionAI data to be integrated with the company’s smartphone app, thus providing seamless and consistent user experience.

Tommy Hilfiger

In partnership with IBM, Tommy Hilfiger pioneered the “Reimagine Retail” project that equips fashion designers with AI skills for designing. As a result, fashion students could learn a plethora of technical skills like natural language processing (NLP) or computer vision to design personalized clothing.

With the use of AI, fashion students could learn from thousands of fashion-related images that enhanced their creativity and reduced lead times for the fashion brand.

Macy’s

Launched first in July 2016, Macy’s AI-powered shopping assistant was aimed at improving customer’s in-store shopping experience. Using NLP, Macy’s “On Call” tool is able to respond to common customer queries like “Where can I find women’s footwear” or navigate to the location of their retail stores in the U.S.

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Enabled by these technologies, this U.S. retail company has planned over 100 store closures that could save the company over $550 million in cost savings.

Amazon

With its AI-powered product recommendation system, this eCommerce giant has definitely revolutionized the online shopping experience. With its foray into using AI for fashion, Amazon is deploying an AI-enabled fashion designer algorithm that can design apparel by copying the design styles of many in-vogue clothes and applying them to a new clothing item.

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Amazon’s other use case is enabled by its Echo Look fashion assistant that can provide personalized recommendations driven by machine learning.

Finally, let’s take a look at a few benefits of AI and machine learning for the fashion industry in the next section.

Benefits of AI and ML for Fashion Industry

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Improved customer personalization

Be it the video streaming or the fashion industry, personalization is key to business success. Thanks to big data innovation, there is plenty of customer data waiting to be tapped and analyzed. Deep learning technologies like AI and ML along with business analytics is enabling fashion businesses to keep track of fashion trends and the purchasing behavior of individual customers.

Enhanced customer service

The emergence of intelligent chatbots and other assistive technologies has transformed customer service and the way shoppers interact with fashion brands. From tracking sales leads to recommending products, chatbots have improved conversions and the overall brand experience.

Improved inventory management

AI-based predictive analytics enable fashion retailers to learn from prevailing customer behavior and plan their inventory stocks accordingly. AI-powered tools can help the fashion business identify their best- (& worst-) selling items and plan their inventories accurately.

Lesser manpower through automation

Another key benefit of AI and ML technologies is that it enables fashion houses to automate repetitive or mundane tasks usually performed by human agents. Tasks like data entry and customer support can be handled now by AI, thus freeing human agents to focus on more strategic activities. 

Reduction in returned products

Return of sold items is a major bane for the entire fashion industry and can increase operational costs. Thanks to AI-enabled personalization and product information, today’s retail customers are more informed and are less likely to buy the wrong clothing item. This, in turn, does reduce returned products and also improves customer satisfaction.

Conclusion

Through product personalization or better designing, there are multiple ways in which AI and machine learning technologies are impacting the global fashion industry. The increasing investments by leading fashion brands in these technologies are proof of their immense business potential.

Through its customized solutions in AI and machine learning, Countants has enabled several companies leverage their investments in these technologies. Our machine learning tools have helped customers improve productivity and scale up their existing operations. Contact us now and leave behind your business queries. We would love to respond to you.