Improving ecommerce data taxonomy can help your brand grow and keep customers shopping, but how exactly does refining ecommerce product taxonomy do this? Read on to find out.
It Enables You to Tune Product Recommendations to Customer Preferences
When the product attributes attached to each Stock Keeping Unit (SKU) in your catalog reflect searcher intent, it’s easier for you to connect shoppers with whatever they type into your search box, whether it’s vague or hyper-specific. But it will also help you make additional relevant recommendations to complete their look once they land on a specific product page and make it easier for shoppers to engage with your filters. Without in-depth product data and excellent ecommerce product taxonomy, it’s hard to do this well.
Product recommendations must reflect customers’ genuine preferences and affinities. Today’s ecommerce stack is starved of customer intent, with bad guesses about shoppers and inventory leading to low conversion rates, high return rates, and a high number of unsold inventory. This is where AI comes in. Lily AI can help you learn more about each customer based on how they engage with your website and the emotional context that drives their purchase. We create individual psychographic consumer profiles you can use to personalize their online shopping experience on a granular level. Shoppers don’t just want recommendations based on colors or sizes. They want to feel like you “get them.”
It Improves the “Just Browsing” Experience
While one shopper may arrive on your site looking for black high-top men’s sneakers — and your site should be able to deliver complete, accurate results — another shopper may simply want to browse the men’s sneaker category without sifting through all types of men’s shoes. Their browsing experience should feel intuitive, and that’s where having clearly defined categories is critical.
Additionally, research shows consumers love personalization, particularly when they have more control over the experience. You can give consumers more control by offering relevant filters and facets they can use to organize the results they see on the page — which is impossible without accurate product attribution and great ecommerce data taxonomy.
Complex navigation and jumbled or redundant categories aggravate your site visitors. And listing too many items under each broad category without any way to narrow down the selection can spike bounce rates. Shoppers are likely to become overwhelmed and exhausted browsing through pages of products with little control over their shopping experience.
It Helps Increase Sales
Customers can’t buy what they can’t find. Many visitors arrive on your site looking for a particular item. If they are flooded with hundreds of different options for a specific search — such as a party dress when they are looking for a casual dress — they will quickly become frustrated.
At Lily AI, we find that brands experience a 5% to 10% increase in revenue by merely enriching their product catalog with more attributes that enable shoppers to see more of what they love through accurate on-site search. We use advanced computer vision and AI to automatically identify every unique feature of an item, such as the specific hue, cut, fit, style, and any added embellishments. The result is an enriched product catalog that better serves your online customers.