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Exploring artificial intelligence and its impact on customer engagement, retail operations and production.
Technology in Fashion
16 August, 2024
Table of contents
Artificial Intelligence (AI) refers to the simulation of human intelligence by machines, particularly computer systems. It involves creating algorithms and models that allow computers to perform tasks that typically require human intelligence, such as recognizing patterns, learning from data, making decisions, and understanding natural language.
Amazon and Google were pioneers in integrating AI into their products and services. Amazon introduced its recommendation engine in the late 1990s, which uses machine learning (a subset of AI) to suggest products to customers based on their browsing and purchasing histories. Google has been using AI since the early 2000s to improve its search algorithms and later developed other AI-driven products such as Google Photos and Google Assistant.
Today AI is transforming the fashion industry in various ways, helping brands and retailers streamline operations, enhance customer experiences, and drive innovation. Here are some key applications:
Predictive Analytics: AI can analyze vast amounts of data from social media, runway shows, and retail sales to identify emerging fashion trends. This enables designers and retailers to stay ahead of trends and make informed decisions about future collections.
Image Recognition: By scanning and analyzing images, AI can identify popular styles, colors, and patterns, helping brands understand what’s trending and adjust their offerings accordingly. Cartier has introduced a collaboration with Google to develop a visual product search system utilizing Google Cloud AI Platform services to identify watches' colors and materials, allowing it to determine which collection a watch belongs to
New Market Identification: AI algorithms can analyze customer data and behavior to identify potential customers in new markets.
AI-Driven Design: Designers can use AI tools to generate new patterns, styles, and designs. AI can also help in creating custom designs based on individual customer preferences. SHEIN utilizes AI customer-oriented design to accelerate the growth of its business.
3D Modeling and Virtual Prototyping: AI can assist in creating 3D models of garments, allowing designers to visualize and test designs before production. This reduces waste and speeds up the development process.
Waste Reduction: AI can help in reducing fabric waste by optimizing pattern cutting and production processes. It can also assist in predicting demand more accurately, leading to more sustainable production runs.
Materials Research: AI can analyze data to identify and suggest sustainable materials and alternatives, helping brands make more eco-friendly choices.
Smart Inventory: AI can optimize inventory levels by predicting demand for specific products based on historical data, trends, and external factors like weather or events. This reduces overstock and understock situations, improving efficiency and reducing costs. Zara has integrated AI into its trend forecasting and inventory management processes.
Automated Replenishment: AI systems can automatically reorder items when stock levels are low, ensuring that popular products are always available. MAC with the help of the Coveo system tracks the average lifetime of a product and individuals' average replenishment time to send automated reminders to the customers.
Recommendation Systems: AI algorithms analyze customer behavior, purchase history, and preferences to suggest products that match individual tastes. This enhances the shopping experience and increases sales by promoting items that customers are more likely to buy. H&M analyses customer data to recommend products that match individual style and preferences, both on their website and through email marketing.
Virtual Assistance: AI-powered chatbots and virtual stylists can interact with customers, helping them find outfits, answering questions, and providing style advice in real-time. Cartier uses AI-driven chatbots and virtual assistants on their website to offer personalized customer service. These AI tools can help customers find specific products, answer questions about items, and provide recommendations based on browsing history and preferences.
Immersive Experience: Via generative artificial intelligence Bulgari created a synesthetic experience for its Allegra fragrance pop-up at the Istanbul airport.
Virtual Try-Ons: AI-driven AR allows customers to virtually try on clothes through apps or in-store mirrors, enhancing the shopping experience and reducing the rate of returns. l-oreal-paris and Chanel are one of the few companies that bring AI-powered virtual makeup try-on. While Dior and Gucci experimented with virtual fittings for accessories and footwear.
Size FInding and Body Scanning: AI can help customers to choose their ideal size. Sandro is collaborating with Fringuant, a body scanning technology tool, that helps to identify the right size with a customer's photo.
Targeted Advertising: AI can analyze customer data to create personalized marketing campaigns, delivering targeted ads that resonate with individual shoppers.
Content Creation: AI tools can generate marketing content, including product descriptions, social media posts, and even visual content like photos and videos. Etro and Giorgio Armani have launched advertising campaigns with a usage of AI.
Custmer Support: Shiseido has launched a Beuty AR Navigation system to support customers with their beauty routine. Via AI-driven motion recognition technology that captures detailed hand movements Shiseido provides customers an easy-to-understand skincare steps via video and narration.
Cover Image Courtesy: Shiseido Website
The article is written with the support of ChatGpt