Artificial Intelligence’s impact within the apparel industry
Artificial Intelligence (AI) is making a transformative impact on the apparel and fashion industry by revolutionizing multiple facets of the value chain. From design and production – where AI predicts emerging trends and optimizes supply chains – to marketing and sales – where personalized recommendations and virtual fitting rooms enhance customer experiences – AI is transforming the way brands operate, ultimately driving efficiency, sustainability, and innovation throughout the industry.
Read on to discover some key examples of how AI is being leveraged in the apparel industry and its impact on brands, products, and shoppers.
How apparel brands and retailers are leveraging AI to achieve success
AI is being used to personalize customer experiences, improve product recommendations, and enhance customer engagement. Brands are wielding the power of AI chatbots and virtual assistants to provide personalized styling advice and recommendations to customers based on their preferences, body measurements, and purchase history. AI also analyzes customer feedback and sentiment data to improve product design and customer experience. H&M’s use of AI-powered chatbots to provide customers with personalized styling advice and recommendations has resulted in a 98% customer satisfaction rate.
Forward-thinking apparel businesses are assisting shoppers in determining their size through AI technology: by asking shoppers simple questions and applying in-depth data science to offer intelligent recommendations. Leveraging current technologies, such as machine learning (ML) algorithms, brands can help shoppers find the answers to their fit questions more easily and be more confident in their purchase decisions. According to a Forrester survey on eCommerce personalization, 77% of consumers said they chose, recommended, or paid more for a brand that provides a personalized service or experience, while research by CMO (Adobe) showed that 66% of consumers say encountering content that isn’t personalized would stop them from making a purchase.
Yet, while utilizing technology is great, it has to be easy to use and enhance the customer experience. Research has shown that taking webcam images or selfies to determine size is unpopular with consumers. It reduces adaptation, as it requires too much effort or elicits privacy concerns due to sharing a picture wearing tight-fitting clothing.
The use of AI in personalization and customer experience has led to improved customer engagement, increased sales, and higher customer satisfaction due to its ability to make recommendations based on a shopper’s actual interests or needs. According to a salesforce report, visits where the shopper clicked a recommendation comprise just 7% of all visits but 24% of orders and 26% of revenue - highlighting the power of AI-driven targeted recommendations. On the flip side, brands integrating these technologies must ensure that they are easy for customers to adopt and use or risk losing them.
Design and Production:
AI is used in apparel design to generate new designs, optimize patterns, and predict future trends. One example is the use of generative design algorithms, which use machine learning to analyze millions of design patterns and generate new, unique designs that are visually appealing and structurally sound. Adidas uses generative design algorithms to create new shoe designs through its collaboration with Carbon, a 3D-printing company. Together, they developed the Futurecraft 4D, a high-performance shoe with a 3D-printed midsole. The generative design algorithm analyzed millions of design patterns, considering factors like cushioning, support, and performance, to create an optimized lattice structure for the midsole, resulting in a 200% increase in design efficiency and a reduction in waste by 50%.
AI can also create 3D models of clothing designs and simulate how they will fit different body types. Bold Metrics goes a step further to provide designers with actual customer body data so they can base their technical designs on accurate customer body measurements that reflect their actual shoppers. By generating fit insights based on individual customer body data and how customers are wearing their clothes, Bold Metrics’ helps designers make more informed decisions about technical garment construction and actual garment fit versus intended fit.
The use of AI in design and production has resulted in faster and more efficient design and production processes, reduced waste, and improved product quality - empowering the apparel industry from the ground up.
Supply Chain Management:
AI is used to optimize the supply chain by predicting demand, reducing inventory, and improving logistics. For example, companies are using machine learning algorithms to analyze sales data and predict future demand for different products, allowing them to optimize inventory levels and reduce waste and improve logistics by predicting delivery times and coordinating routes for faster and more efficient delivery. PUMA has worked with mobile robotics firm, Magazino; software provider, Gigaton, and logistics specialist, ITG for its intelligent AI-powered warehouse robot - ‘TORU’, at its logistic center in Germany to increase efficiency. Nike, too has leveraged AI for logistics with a regional distribution network supported by advanced demand-sensing and inventory optimization technology platforms that use AI to help the brand predict and curate products based on one-to-one consumer demand.
Zara has optimized its inventory management with AI, which has resulted in a 2% increase in sales and a 10% reduction in inventory costs. Bold Metrics AI-powered Smart Size Chart includes advanced inventory algorithms that leverage real-time data to generate actionable insights. The Smart Inventory™ feature included in Bold Metrics Smart Size Chart helps brands address dynamic supply chain issues in today's challenging apparel retail environment by providing insights on size inventory in real-time when providing size recommendations.
Using AI in supply chain management has led to reduced inventory costs, improved delivery times, and a more sustainable supply chain. Upstream garment sizing insights can be leveraged to manufacture better-fitting clothing to demand and boost sustainable production methods.
The impact on sustainability that AI is having within the fashion and apparel industry extends beyond demand forecasting. AI-driven supply chain optimization streamlines production planning, reducing resource consumption and carbon emissions. Additionally, AI-powered virtual fitting rooms and personalized recommendations minimize returns, which in turn decreases packaging waste and the environmental footprint of reverse logistics. By enhancing efficiency, reducing waste, and promoting a circular economy, AI plays a crucial role in driving sustainability in the industry.
Stella McCartney, a luxury fashion brand known for its commitment to sustainability, partnered with Google to develop a pilot project called the "Environmental Data Platform." This AI-powered platform helps the brand assess the environmental impact of its supply chain by analyzing extensive data on raw materials, production processes, transportation, and more.
By leveraging AI, Stella McCartney can make informed decisions about sourcing materials and manufacturing processes, ensuring the brand remains true to its sustainable ethos.
Regarding post-purchase impact, Bold Metrics sizing solutions help connect customers to their best fit with an accuracy that has resulted in an average return rate reduction of 32%. In 2021, the total US eCommerce apparel returns due to fit resulted in approximately 1,043,481 tons of CO2 and 168,337 tons of landfill waste. If the entirety of the US Apparel Industry used a sizing solution like Bold Metrics... 53,868 tons of landfill waste would be diverted, which is the equivalent of around 344,754,841 shirts not ending up as trash. To further understand how improving sizing can benefit both brands and the environment, download our “Apparel Sizing Best Practices for Brands and Retailers” 2023 guide - an actionable outline around supercharging sizing, the steps to implement it, and the metrics for success, which include how to reduce returns and the carbon footprint that comes from processing returns.
AI-powered supply chain optimization leads to more eco-friendly production processes, minimizes carbon emissions, and streamlines logistics. Virtual fitting rooms and personalized recommendations driven by AI further contribute to sustainability by lowering return rates and reducing the environmental footprint of reverse logistics.
AI has a transformative impact on the apparel industry, from demand forecasting and supply chain optimization to virtual fitting rooms and personalized recommendations. AI-powered initiatives are revolutionizing how fashion brands operate, driving efficiency, enhancing customer experiences, and promoting sustainability.
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