An In-Depth Look at Fashion Artificial Intelligence
Jess Erdman, June 2021
Fashion artificial intelligence is taking the world by storm. Some of the biggest brands worldwide are implementing fashion AI to transform their businesses, whether that’s better demand forecasting, elevating the search and discovery experience, or re-thinking the fitting room experience. In the blink of an eye, the industry is adapting and adopting new technologies.
In this guide, we’ll give you a complete overview of the retail industry’s relationship with fashion AI, including:
Let’s dive into the guide.
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The uses of AI in fashion have changed drastically from early days when AI was limited to chatbots. Now, fashion brands have discovered far more practical uses for AI in fashion--in fact, the value of artificial intelligence in fashion is expected to grow over 35% in the next few years.
The adoption of artificial intelligence in fashion has grown in the past few years, as retailers look to make more informed decisions, and think of ways to engage customers in an online-shopping dominated world.
That answer depends on the goal of the business. Some retailers are choosing to implement the predictive analytics component of fashion AI, while others are getting more creative, and choosing a fashion-forward approach. We’ll break down the difference using our own terms:
Predictive analytics: When retailers use fashion artificial intelligence to forecast seasonal demand of products, or better manage inventory levels. When combined with human knowledge of fashion trends and cycles, the AI-powered predictive analytics can give retailers a heads-up to trends they may otherwise miss.
Fashion-forward AI: Retailers that are using fashion artificial intelligence to rethink the customer journey. For example, at YesPlz AI, we created a Style Filter that uses AI to pull relevant clothing options when customers search for a particular product.
Fashion artificial intelligence can produce a variety of benefits, including:
1. Higher rates of customer satisfaction
When customers are able to easily navigate to products they’re looking for, retailers see higher rates of customer satisfaction and return rates
2. Easy-to-navigate search tools
With fashion AI, retailers are offering customers an easier way to search for items. In return, customers receive more accurate search results from fashion-trained algorithms
More accurate product recommendations
3. AI in fashion can produce more accurate product recommendations
Customers are no longer recommended random product categories after viewing an item, as algorithms can be trained to recognize which products to show a customer browsing. For example, customers browsing a running shoe are unlikely to purchase a cocktail dress--and fashion AI can recognize these patterns.
4. Automatic tagging of new product SKUs
One of the biggest problems that can overwhelm retailers is the constant need to manually add product tags as new items come into the store. By using fashion AI, retailers can save time and tag more accurately.
Nearly every major retailer has implemented fashion artificial intelligence in some form, whether in predictive analytics or fashion-forward AI. Take a look below to see a snapshot of retailers:
We expect that by the end of 2021, there will be even more adoption of fashion artificial intelligence by retailers both big and small. As fashion AI begins to get integrated into product strategies, all figures point to retailers continuing to adopt AI tools to improve business outcomes.
Who is the new customer, post-COVID? Undeniably, the pandemic has changed the way that we shop.
According to Vogue Business, COVID-19 has pushed the customer ahead by 5 years.
Due to increased time spent at home, customers in 2020 became more digitally-savvy--even customers that normally would have preferred an in-store experience were forced to learn to navigate eCommerce.
With the loss of brick and mortar stores in 2020, fashion AI stepped in to replace in-store sales associates, impacting the way that customers can discover and interact with products.
For example, eCommerce companies were pushed to be more creative than ever to provide a superior online experience. By integrating fashion AI that can provide a virtual-fitting room experience, or AI-powered product recommendations, AI became synonymous with the online shopping experience.
The most important fact to know about the post-COVID customer is that she is more digitally sophisticated and therefore, demands more from online shopping. Therefore, she can be easily frustrated by confusing search systems, and prefers to seamlessly move through her shopping experience. Through fashion AI, retailers can meet the rising needs of customers without over-extending themselves.
To learn more about how COVID changed the customer, check out the in-depth analysis here.
Ready to implement fashion AI into your business? Take these tips, from Eva Ross of Farfetch, to help guide the process:
1. AI in fashion has the potential to help companies arrange and analyze large data sets in areas such as search, AR/VR, chatbots, inventory management, and demand planning. But, it can be difficult to derive actionable insights from the data.
2. Put the correct internal systems in place first that can facilitate the movement of data and prevent data silo.
3. Remember that identifying patterns in data can take significant time, because fashion AI algorithms need time to learn. Be patient.
If you follow retail news, you’ve likely heard doomsday statements predicting that more advanced AI means the beginning of the end of the fashion industry as we know it. Of course, those statements are shock-statements meant to gain page-views--but what will the future of AI be?
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