Fashion Tagging

What Is Fashion Tagging and How Does Lily AI Do It Differently?

Fashion tagging, or more broadly referred to as product tagging, can power your on-site search to deliver more accurate results to your customers, among other benefits. The problem? Until recently, product tagging has been a manual game, a time-consuming and imperfect process of attaching product attributes to each item in your catalog. It’s ripe with potential for human error and often results in many products that either don’t have enough tags or have inaccurate tags.

Fashion Tagging

What Is Fashion Tagging and How Does Lily AI Do It Differently?

Fashion tagging, or more broadly referred to as product tagging, can power your on-site search to deliver more accurate results to your customers, among other benefits. The problem? Until recently, product tagging has been a manual game, a time-consuming and imperfect process of attaching product attributes to each item in your catalog. It’s ripe with potential for human error and often results in many products that either don’t have enough tags or have inaccurate tags.

Enter automation and artificial intelligence, an industry that’s projected to be worth $16 billion by 2022. It’s creating a significant shift in how several other industries operate, and fashion e-commerce is no exception. Many online fashion retailers are gravitating toward automated product tagging to simplify and speed up the process, gaining access to more attributes in less time. It saves retailers time and reduces the risk of human error. But not all automated product tagging tech is created equal.

The Number of Trained Data Points Matters

Lily AI has more than 1 billion trained data points and over 15,000 product attributes, more than other AI tagging technologies. Our fashion tagging algorithm populates the richest set of attributes possible, going more in-depth than other AI platforms on the market. Why does the number of attributes matter? The better your products are tagged, the better and more specific your on-site search results can be, helping you connect your customers to the best products possible based on specific searches. You can also take that data and apply it to creating better filters and facets, improving your SEO, and more.

Connect Product Tags to Emotional Context

Improving your product tags to improve your on-site search is one thing, but the next step is to use them as a tool for analyzing customer behavior. The goal? Put your data to work. Lily AI takes it to the next level by helping brands leverage better product data and using that to compile more detailed customer data that powers true personalization. 


By continuously analyzing how customers engage with certain products and their attached attributes, our algorithm creates a psychographic profile for each customer. You’re able to gain insights into not just what they’re searching for but why they’re searching. Do they love boho chic? Do they have a short torso or long arms? Do they live for sequins? Learning this starts with better, more accurate fashion tagging.


Lily AI uses customer data to decipher the reasons for a customer’s search, and based on their individual psychographic profile, brands can continuously recommend the right products based on the shopper’s motives, emotions and perceptions of themselves. In other words, Lily AI helps e-commerce brands see customers as they see themselves

More Accurate AI-based Algorithms Builds Customer Engagement

Of course, all the fashion tagging in the world won’t make a difference if the tags don’t accurately describe your merchandise. Quantity is great, but accuracy and quality are most important. Lily AI’s advanced computer vision and sophisticated artificial intelligence algorithm has more trained data points than other fashion tagging tech. It recognizes attributes with 99% accuracy, identifying even the smallest details that set each article of clothing apart.

Get in touch to learn more about Lily AI’s fashion tagging capabilities and what makes us different. 

Dawn Allcot is a full-time freelance writer and content marketing specialist who frequently writes about finance, e-commerce, technology and marketing. Her work appears regularly on GoBankingRates, Yahoo!Finance and PocketSense. She is the owner and founder of GeekTravelGuide.net, a travel and entertainment website. 

References

https://blog.usejournal.com/automated-product-tagging-in-fashion-retail-the-ultimate-guide-4452351926ec

 https://www.apparelsearch.com/terms/f/fashion_tags.htm