Artificial intelligence (AI) has been a very hot topic lately, and there’s no denying it has game-changing applications in almost every industry, including the fashion industry. AI can significantly benefit all parties involved in the fashion industry, in countless ways, whether it’s the consumer, designer, manufacturer or retailer.
While there are tons of ways AI can be used in the fashion industry, the six major applications we’ll focus on in this article include:
- Trend forecasting
- Achieving a better fit
- Optimizing manufacturing processes
- Personalizing the shopping experience
- Managing inventory
- Reducing returns
Trend Forecasting
Trend forecasting is a strategy used to predict future fashion trends, like patterns, colors, fabrics, styles, and more. Brands produce new styles more rapidly than ever before, while consumer preferences shift just as rapidly. You can imagine how challenging it is to keep up with these rapidly changing trends.
Instead of spending countless hours collecting and analyzing data from multiple sources, such as, social media trends, runway shows, and historical data, AI can be implemented to quickly dissect this information much quicker than any human could manually. AI-driven trend forecasting enables businesses to gain significant insight into current and future market dynamics, consumer behavior and sentiment, and customer trends so that they can predict upcoming fashion trends and stay ahead in this ever-evolving market.
Achieving a Better Fit
Finding clothes that fit properly is one of the biggest challenges consumers face when shopping, especially when shopping online. This challenge is especially true for those who are petite or have a body type that doesn’t match the fashion industry’s “standard” size and shape.
AI can address size and fit issues through several innovative approaches, including virtual dressing rooms, body scanning, customer profiling, 3D modeling and simulation, feedback integration, size recommendation algorithms, and more. AI’s ability to process and analyze large amounts of data from several different sources enables more accurate size and fit solutions that are tailored to each individual customer.
Optimizing Manufacturing Processes
AI has the ability to drastically improve manufacturing processes in the fashion industry. There are many ways it can do this, including demand forecasting, supply chain optimization and transparency, quality control, process automation, and much more.
For example, AI-driven traceability systems can provide real-time information about when, where, and how garment materials are made, promoting transparency and ethical practices.
Quality control is another area where AI can optimize manufacturing processes in the fashion industry. AI-powered computer vision systems can quickly and easily identify defects across a large number of products to ensure consistent quality during production.
Furthermore, every garment can be compared to preset standards and specifications to make sure there are no variations or discrepancies between garments, and that they adhere to specific quality parameters. Human inspectors can easily miss defects, while AI-powered systems can reduce human error and provide more accurate and consistent results. This data can then be analyzed to identify trends, recurring issues, and potential causes. Companies can use this data to make informed decisions, implement appropriate changes/improvements, and produce higher quality products overall.
By leveraging AI’s capabilities in data analysis, prediction, and automation, manufacturers in the fashion industry can reduce costs, increase efficiency, improve quality, and become more “green” across the entire production process.
Personalizing the Shopping Experience
In order to offer a unique and enjoyable shopping experience for customers, retailers must consider innovative ways to go above and beyond the industry norm to distinguish themselves from other retailers, both online and in store. Hello, artificial intelligence! AI can be implemented to create a much more personalized shopping experience catered toward each customer individually. For instance, customer data can quickly be analyzed to provide personalized product recommendations and advice on size and fit.
More specifically, AI-driven wishlist alerts can be implemented so that customers are notified when items from their wishlist are low in stock, back in stock, or on sale, encouraging purchases at the most opportune times. Not only that, but AI can be used to send personalized follow-up emails or texts suggesting complementary products or offering styling tips after a purchase.
By leveraging AI’s ability to process mass amounts of data and provide real-time insights, retailers can offer a highly personalized shopping experience for customers, leading to increased customer engagement, more satisfied customers and less dissatisfied customers, and, ultimately, more sales.
Managing Inventory
AI-driven demand forecasting and inventory optimization can help brands manage their supply chain and inventory. It can do this by analyzing several variables, like market trends, historical sales data, holidays, etc. to create accurate forecasts about what styles will be in demand and when. Ultimately, this helps businesses to prevent overstocking and stockouts.
Reducing returns
Returns are a significant problem for retailers and very costly. But, AI can help! There are several ways AI can be implemented to reduce returns in the fashion industry.
One way this can be done is by implementing return forecasting models. AI can examine historical purchase and return data to create models that can accurately predict which items are likely to be returned. This kind of insight empowers brands to adjust their inventory and marketing strategies accordingly.
AI-driven customer support is another tool businesses can implement to reduce returns. Chatbots can provide immediate assistance to customers 24/7 by answering questions about product details, like size and fit, materials, and availability. This enables customers to make informed decisions and smarter purchases, minimizing customer confusion and returns.
Customer reviews provide businesses (and customers) with extremely useful insight on products and services. AI-driven customer review analysis is another tool businesses can implement to minimize returns. AI-powered sentiment analysis can examine customer reviews to pinpoint common issues that are contributing to returns. It can identify issues like poor quality, sizing discrepancies, design flaws, and many other product-related concerns. Brands can leverage this feedback to ensure issues are resolved accordingly.
Overall, there are countless ways the fashion industry can implement artificial intelligence (AI), and the results are invaluable. AI can be used to improve trend forecasting, help customers with size and fit, optimize manufacturing processes, personalize the shopping experience, manage inventory, and reduce returns. The fashion industry is constantly evolving at an increasingly rapid rate, especially now with artificial intelligence (AI) on the rise. AI is completely transforming the fashion industry by empowering businesses to innovate, increase efficiency and sustainability, cut costs, and increase profits.