In the world of eCommerce search, text search is at the heart of the discovery journey. Users intuitively gravitate towards text search when looking for their favorite brands, a specific product, or to begin a search query. 

Lost sales. More time spent searching. Missed products. Higher bounce rates.

All of these are the result of poor text search systems. But, in order to get it right, we need to break down the most important components: what is text search and how does it work?

What is eCommerce Search?

Simply put, eCommerce search is a method of searching for items on an eCommerce website. 

It uses text-based keywords to match customer queries with relevant products. Text search is often used on websites that offer a wide variety of products. 

With eCommerce search, customers can quickly and accurately find what they're looking for without having to click through multiple pages of search results.

There are two types of eCommerce search that we’d categorize as relevant in 2023: “traditional” and “enhanced.” In a traditional eCommerce site search experience (without any AI technology), a users’ keyword search is matched against a manually configured glossary of keywords. 

But, with the evolution of new technology like machine learning, we can also build enhanced text search that goes beyond the capabilities of traditional search.

How Does eCommerce Search Work?

eCommerce text search works by using a set of algorithms to match customer queries with relevant products. The algorithms are designed to take into account the customer's location, language, and search history. This information is used to generate a list of products that match the customer's query. The more accurate the algorithms, the better the results.

To further improve the accuracy of the search results, enhanced eCommerce search uses AI image tagging and machine learning.

 AI image tagging uses computer vision to detect objects in product images, which helps to quickly tag product catalogs, creating better matching text search results. 

Machine learning can analyze past customer inputs and interactions to provide the best possible search results for a particular customer. 

Additionally, enhanced text search can use fresh, updated keywords to keep search results relevant and up-to-date. This ensures that customers are always able to find what they're looking for.

Traditional vs. Enhanced Text Search: A Quick Overview

Benefits of Enhanced eCommerce Search 

Not all eCommerce text search systems are the same.

Some search systems are barebones, without any AI technology, and offer basic search capabilities without any customization. 

Other search systems like YesPlz AI are built specifically for fashion eCommerce sites and offer advanced features such as integrated side filters, AI fashion tagging, and autocomplete—specifically built for fashion eCommerce.

The benefits of using an enhanced eCommerce search system like YesPlz AI include:

• Lower bounce rates as shoppers are more engaged

• Increased number of higher matching search results

• Faster, more accurate searches leading to more conversions

• Improved shopper data that can be used to feed other product discovery tools, like recommendations 

Enhanced eCommerce search can be a powerful tool for fashion eCommerce businesses to stand out in a crowded, competitive playing field. 

Text search powered by AI helps customers find the exact item they’re looking for quickly and easily, and it also helps customers discover new items they might not have considered before. 

YesPlz Tip: Look for text search systems that include fashion tagging, UX elements like an integrated side filter, and fresh, popular keywords that are automatically updated. 

The Future of Text Search

By now, you’ve probably understood the value of implementing some kind of text search system–but we recommend that you ask yourself whether you’re getting the most out of your text search.

Does your current eCommerce site search:

Offer fashion tagging? Update to include the latest trending keywords? Show shoppers instant product previews? Guide shoppers along the search process with additional filters Autocomplete search query suggestions based on similarity and popularity?

Your text search could be doing so much more, with the power of machine learning and AI image tagging.

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