Improve Product Discovery: 3 Ways eCommerce Search Enrichment Can Help

Jess Erdman

Jess Erdman, March 2023

Ecommerce search enrichment is the process of enhancing product data with additional rich information.

 

But, where does that information come from? One obvious answer is from product descriptions–but there are actually more ways to enable it.

 

eCommerce search enrichment enablers can include:

 

  • Rich product tagging

 

  • Product recommendations

 

Ecommerce enhancement data can be used to build multiple “style with” product recommendations, as well as even more recommendations below based on neck-type and dress style.

 

  • Product search

 

  • Product filters

 

  • Valuable user data to enhance the shopping experience

 

How should your team approach eCommmerce search enrichment?

 

The value of eCommerce search enrichment cannot be understated–from a better search experience to the ability to easily create new, trendy product filters.

 

An example of eCommerce enhancement is filtering by the color “red” in the above image.
AI can easily tag new products with color, and update according to the appropriate filter.

 

 

But, who exactly is going to create eCommerce search enrichment?

 

Is your engineering team tied up in the mundane task of tagging new incoming products, developing search filters that need to constantly be updated, and well, essentially reinventing the wheel for what could be considered already existing technology?

 

Maximize your eCommerce engineering team’s potential by freeing up their time.

 

With the unique needs of your eCommerce, it can be hard to believe that an already existing technology can meet your needs.

 

But, we’re here to tell you that through fashion artificial intelligence, there are better, faster, and pre-existing solutions.

 

Wouldn’t it be better to utilize your engineering team for higher-value tasks, maximizing their potential to work on more strategic customization projects?

 

The YesPlz Virtual Mannequin Filter automatically pulls relevant search results based on product attributes,using fashion AI.

 

How eCommerce search enrichment can unlock the potential of your engineering team

 

An outcome of successful eCommerce search enrichment are robust product filters, text search, and recommendations.

 

Mother Denim specializes in denim, and has specific product attributes for type of jean (bootcut, straight, flaire).
Instead of manually tagging, 
Mother Denim could enhance their search filters by utilizing auto-product tagging, which easily updates filters.
This is another example of how eCommerce search enrichment can lead to better, more effective search.

 

When shoppers can’t find the products they’re looking for, the problem beneath the surface lies with lack of eCommerce search enrichment, which results in missing product attributes and inaccurate search.

 

Your team can either work to fix this internally, or utilize a third-party solution.

 

When eCommerce engineering teams are stuck working on the minute details of search enrichment, they lose valuable time working to personalize the data even further.

 

With expert, AI-powered eCommerce search enrichment, there’s no need to try to solve the problem on your own when pre-existing integrations exist.

 

Building Hyper-Personalization with eCommerce Search Enrichment

 

A filter, search, and product recommendation system creates the infrastructure necessary to get valuable user data, which can then be used to make eCommerce enrichment even more effective.

 

Automatically enabled, robust filters allow shoppers to filter by size, occasion, style, and more at Ralph Lauren.

 

 

But, building search and discovery from scratch can be a time-consuming and laborious process. And third-party solutions are fragmented, leaving eCommerce brands with multiple vendors to manage, multiple integrations to oversee, and an incomplete product discovery ecosystem.

 

There’s no need to waste time working with multiple vendors when all search and discovery tools to enable eCommerce enrichment are available with a single integration at YesPlz.

 

When your eCommerce partners with YesPlz AI, your eCommerce receives access to AI-powered product tagging, smart filters, product recommendations, and enhanced text search. 

 

Then, using the eCommerce search enrichment data that the YesPlz product discovery system provides, product discovery and recommendations are improved even further.

 

The Result of AI-Powered eCommerce Search Enrichment For W Concept

 

W Concept is a leading fashion retailer, with a large and beautiful catalog of the latest independent designers. After working with W Concept, YesPlz worked to provide eCommere search enrichment through smart product filters, product recommendations, enhanced text search, and AI tagging.

 

The end result? An average increased cart size of 1.7x and search exit 3x higher than the industry standard. 

 

And the best part–W Concept engineers can focus on what they do best, leaving YesPlz to create AI-powered product discovery and recommendations that lead to eCommerce search enrichment.

 

You Might Also Like Recommendations, built for W Concept by YesPlz AI, uses rich product data to make suggestions based on similar attributes.

 

Ultimately, eCommerce search enrichment enables eCommerce businesses to create product discovery and recommendations that engage shoppers, convert them, and provide a superior shopping experience. And, with AI, the process can easily be automated.

 

 Ask YesPlz about how AI is enabling better, more effective eCommerce search enrichment. 

 

by Jess Erdman Jess Erdman
Content Marketing Lead

I'm passionate about creating cool content. The best part? I get to learn new things about fashion tech and ecommerce everyday. Have an idea or opinion about this article? Reach out at jess@yesplz.ai

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