Artificial Intelligence and Changing Fashion: How Artificial Intelligence Can Design Excellence for Retailers and Shoppers

There have long been some concerns about the application of artificial intelligence technology in the fashion industry, which is mainly guided by creativity and expression. Technological interventions are changing the way businesses operate today, and the fashion industry is no exception. Artificial intelligence has entered every aspect of the fashion and retail industries, from design and production to marketing and sales. This stems from the understanding that these technologies are not a hindrance to creativity, but a powerful tool to enhance creativity and customer appeal.

To thrive in a dynamic and fast-paced environment like the fashion retail industry, businesses need to remain agile and ready to take advantage of any potential opportunity. Artificial intelligence enables businesses to understand and act on consumer behavior. Hundreds of data points are taken into account, resulting in valuable insights that can guide retailers to better shape sales strategies and enhance customer experience.

Innovating Retail

Traditional performance analysis methods include reviewing product performance at the end of each quarter. With artificial intelligence, it is possible to access real-time data and observe changing trends and stock performance of businesses. This enables retailers to develop proactive strategies that capitalize on consumer sentiment and meet their needs without missing out on critical opportunities. To stay ahead of the industry segment, companies always need to stay relevant and work on innovation. What’s more, technologies like automated product labeling allow retailers to analyze market performance at an attribute level, taking into account detailed attributes such as color, print, sleeves, collars, and more.

Artificial intelligence-driven tools can help retailers identify best-selling and worst-selling items to effectively optimize inventory. Learning from current customer behavior and planning inventory accordingly can significantly reduce waste and unsold inventory costs. By identifying areas of high demand and emerging sales trends in real time, predictive analytics can take the guesswork out of inventory management and avoid the hassle of overstocked or understocked products. This gives them a better idea of ​​how well a product is selling and how long it takes to restock it. The technology takes into account seasonality, fashion trends, geography and the age of the customer base to predict demand for goods.

Predictive analytics can also make marketing campaigns more effective. A simple application is to use natural language processing to understand what a specific target audience is saying so that marketing campaigns and advertising can be tailored to that demographic.

Artificial intelligence helps retailers predict consumer responses to price changes based on historical sales data, thereby optimizing their pricing strategies. These predictions may not always be 100 percent accurate, but they can be very useful in understanding how customers are likely to react. Retailers can gain a competitive advantage by using AI to recommend optimal price points after monitoring competitors’ prices. They can also determine the best times in the season to maintain prices with the lowest profit margins, and when to increase prices slightly to maximize profits. This makes it easier for retailers to plan price cuts and promotion strategies to attract the right customers at the right time.

Putting customer experience at the core of retail services

Artificial intelligence provides more opportunities for businesses, and at the same time, consumers get a compelling shopping experience. Take visual search as an example. Through artificial intelligence's visual search, customers can easily search for products simply using pictures of the clothing they want to buy or the celebrity style they want to imitate. After identifying all the products in the image, the AI ​​returns the best match for each product from the retailer's inventory. This way, consumers can find what they want, even if they can't put into words what they want. On the other hand, retailers also have a deeper understanding of consumer tastes and preferences.

When customers want to buy an item that is out of stock, they will be redirected to a selection of related product recommendations to help them find what they want. These recommendations based on product similarity increase customer engagement and reduce lost sales opportunities to competitors.

Personalized recommendations make online shoppers' browsing experience more satisfying because they see the items they are most likely to buy, saving significant time and effort. This is enabled by artificial intelligence - careful analysis of previous orders can reveal customer preferences in terms of colour, style, size and more.

Speaking of personalization, virtual try-on solutions are growing in popularity among shoppers. Virtual fitting rooms allow customers to try on any garment from the online store from the comfort of their own home. When they are able to make more informed purchasing decisions, satisfied customers are likely to purchase more items in the future, which also reduces the chances of returns and exchanges. For example, the Looklet dressing room allows customers to style clothing for various body types and imagine how the clothes will look on them. By leveraging Looklet's core rendering technology along with their artificial intelligence and 3D systems, high-quality and color-accurate images can be created to deliver a realistic virtual fitting room experience. Shoppers can try on whatever they like and can pair multiple pieces together to create how they want to see themselves look.

Exciting Future Developments in Fashion Technology

What’s interesting to watch is how artificial intelligence can help retailers bridge the gap between the in-store experience and the online shopping experience to a large extent. Build customer trust. From shoppers hesitating to buy clothes online to regularly shopping from pure e-commerce brands, people have definitely come a long way. Shopping experiences online and offline are increasingly convenient, personalized and enjoyable. Thanks to the contributions of artificial intelligence and machine learning, the future of fashion and retail is indeed full of possibilities.

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