Machine Learning in Fashion
In modern times, fashion has evolved with the industry becoming more and more lucrative each year. In fact, the fashion industry is projected to grow by over $80 billion, a substantial 60% increase, from 2020 to 2024.
This rapid growth is fueled by growing demands for the constant production of new products in a term called ‘fast fashion.’ In order to keep up with these demands, major fashion retailers have turned to new technologies like artificial technology (AI) and machine learning (ML) to rise past their competitors.
What Companies are Leveraging AI and ML?
Popular retailers that utilize AI and machine learning include Zara, Tommy Hilfilger, H&M, Dior, and many more. However, a specific example of the successful incorporation of these technologies for growth can be observed in apparel retailer Zara, who adapted AI into its business strategy and supply chain in 2018 as a way to keep up with and beat its competitors. The following year, Zara experienced strong profit growth, partially attributed to its new use of AI technologies.
How Do Companies Leverage AI and ML?
Designing → In current times, many fast-fashion companies release a new collection of clothing a week. This rapid output of creative designs wouldn’t be possible without the help of technologies like “AI designers” that analyze popular styles and design elements to create completely new designs from scratch.
Manufacturing → As a result of the rapid output of new merchandise year-round, many retailers have trouble with estimating customer demand for their new line of products due to the limited amount of time they have between releases. Thus, retailers have turned to AI-driven demand forecasting in order to reduce forecasting errors by up to 50%.
Retail Strategy → One major issue that may happen to fashion retailers is ending up with a surplus of unsold inventory. However, in order to combat this problem, large retailers like H&M have turned to machine learning in order to align the inventory within each of its stores to customer preferences and demands.
Product Discovery → Multiple studies have proven that shoppers are less likely to purchase an item as they grow more weary spending more time browsing an online clothes store. Thus, fashion retailers have utilized AI and ML technologies to make product discovery easier by analyzing past purchases or search data to hint at certain products that a customer may be interested in.
Supply Chain Management → AI and Ml technologies allow fashion retailers to stop the production of unwanted items and instead, increase the production of products that are trending in real-time. This is yet another method by which companies can reduce the risk of having unsold inventory.
Conclusion
In the future, artificial intelligence and machine learning technologies are projected to grow even more powerful. Businesses in several industries like fashion must be able to utilize these growing tools to their advantage to keep up and stay ahead of the competition. After all, the businesses that choose not to utilize these technologies will undoubtedly be left behind.
