AI in Fashion: Leading eComm Trends from Differio to Levis

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AI in Fashion: Leading eComm Trends from Differio to Levis

Over the last few years, artificial intelligence has transformed our everyday lives from driving assistance to real-time translation. As AI-powered tools and apps become more readily available, it’s reshaping the way we perform the most ordinary tasks, including shopping for clothes.

Fashion companies are now integrating AI technologies to improve supply chain operations, customer service, retail security, waste reduction, and so on–a list that only scratches the surface of its capabilities. 

Subscriber-based ecommerces like Stitch Fix are redefining personal styling through AI algorithms that curate custom clothing selections based on individual preferences.

Trendy menswear e-tailers like Differio are optimizing AI-driven solutions to target design and demand forecasting. Differio’s CEO further adds, “Even though AI technology can’t replicate genuine human creativity, it has the potential to steer fashionable men’s clothing online towards a more innovative future, devoid of overproduction and microtrends.”

Even old-school brands like Levis are testing AI-generated models to display more diversity and inclusivity on their product pages.

According to McKinsey consulting firm’s analysis, over the next three to five years, generative AI has the potential to add up to an estimated $275 billion in profits across the fashion, apparel, and luxury sectors. As we welcome generation AI into our wardrobes, let’s explore how today’s fashion e-tailers are integrating various AI-powered solutions into their own business models.

Personalized Shopping

Personalization is in demand more than ever now from custom-designed men’s clothing online to targeted product suggestions. 

In order to cater to this ecommerce trend, fashion companies are tapping into AI-powered technologies to create a more personable experience using customer segmentation. It’s one of the key applications where AI algorithms analyze vast amounts of consumer data to identify specific marketing campaigns and product offerings.

Product and size recommendations are another AI game-changer, which especially helps to reduce return rates. By analyzing a customer’s past purchases and browsing history, AI algorithms can suggest relevant products that match with a shopper’s preferences. It can also gather data on a customer’s body measurements to suggest sizes for virtually any clothing item from chino pants to graphic tees

Virtual Enhancements

There was once a time when real-time chatbots and virtual menswear models sounded like something from a sci-fi film. Thanks to AI systems and virtual reality, these futuristic tech ideas are not only becoming a reality, but also being implemented into today’s trendy clothing sites. 

Chatbots and virtual assistants reduce the need for a large customer service center while also addressing customer concerns by suggesting products and solving real-time inquiries. 

Similar to try-before-you-buy subscription boxes, virtual try-on tools allow customers to virtually “try on” stylish clothing items, which also helps to lower return rates.

Additionally, virtual models created through AI and VR technology can showcase stylish clothing, providing customers with realistic visuals on various skin tones and body types. 

Data-Driven Efficiency 

If you thought fast fashion was fast, AI solutions are only speeding up the market thanks to data-driven efficiency. Instead of spending time and energy on tedious tasks, it allows people in the workforce to reallocate their focus on more pressing issues, saving time and resources. 

With AI-generated content creation, fashion ecommerces can automatically generate product descriptions, social media posts, and marketing materials within seconds. 

Dynamic pricing algorithms are also being used to analyze market trends and customer behavior in real-time. Ultimately, this helps e-tailers act fast to increase profits and stay competitive in the market.

Additionally, AI-based demand forecasting models can predict consumer demand more accurately by analyzing factors such as order history and SKU data, improving overall inventory management and minimizing stock issues.

Fraud Prevention & Cybersecurity

Fashion ecommerces still need to be on guard when it comes to theft and loss prevention, usually caused by identity fraud or a data breach. Fortunately, it’s becoming easier than ever to detect and block suspicious activity.

One way to do this is by implementing AI-powered Web Application Firewalls (WAFs). WAFs are used for advanced protection against online threats and vulnerabilities by learning algorithms that analyze incoming web traffic in real-time. 

By quickly analyzing large volumes of real-time data, AI systems can identify potential threats and unauthorized access attempts, allowing online businesses to mitigate risks in a matter of minutes. 

AI Forecast: What to Expect in Fashion’s Future?

Fast fashion works at lightning speed, but AI might be even speedier in changing the course of fashion’s future. 

There are simply no signs of AI slowing down in the coming decade. According to Statista, AI technology’s market spanned around 200 billion U.S. dollars in 2023 and is anticipated to exceed 1.8 trillion U.S. dollars by the year 2030, signaling remarkable growth. 

With AI’s imminent success, the only downfall is its potential to replace a variety of jobs in the future, such as trendy men’s clothing analysts and customer service representatives. 

AI in Fashion: Leading eComm Trends from Differio to Levis
Brian Wallace

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