Site Search

Site search is an eCommerce tool that allows shoppers to search a brand catalogue for matches to what they type into a search bar. It is often a built-in feature that retrieves relevant results based on product tags.

Standard site search includes the indexing of product titles and descriptions. An effective, augmented site search goes even further and can detect spelling mistakes, synonyms, and human intent to surface product results that are either an exact match or extremely close to the search term.

Why It Matters

Site search matters in eCommerce because it is the primary method for online product discovery. The sophistication level of your site search impacts the customer experience. When the search returns highly relevant results, customers will feel that you understand their unique preferences — and this opens opportunities to further engage, increase basket size, and eventually, complete a purchase.

Moreover, a robust eCommerce search engine allows you to tailor recommendations based on what customers are searching for in real time. This way, they continuously find items that meet the inspiration they have in mind, allowing for an engaging shopping experience that is worth remembering and repeating.

Ultimately, an effective site search strategy earns more revenue by connecting customers to the products they are looking for with a frictionless experience.

A screenshot of user-friendly site search functionality on an eCommerce brand
Shein’s user-friendly site search offers possible categories straight from the search bar as shoppers type.

How Does It Work?

Simply put, site search works by exploring your entire inventory for results that match a customer’s query. It retrieves and surfaces products based on product tags.

Traditional eCommerce search engines are now being improved using the latest technologies to enhance the search experience of users. For example, visual AI augments the search by enriching product attributes with more detailed, accurate, and organized tags. The automatic product tagging process is powered by artificial intelligence. Online search is also made better with natural language processing which translates and contextualizes the language that customers use to match your existing product tags. This way, shoppers do not have to type the exact keywords of your tags to find matching products.

Site Search Best Practices

Here are some best practices that brands and retailers can use to improve eCommerce search:

  • Enable auto-complete and auto-suggest – Not all shoppers have the time to sift through your menu and categories. You can help these customers save even more time with automated, relevant suggestions that appear even before they complete a text query. You can also add product images to the auto-suggestions so that shoppers know that they are searching for the right term.
  • Use ‘no results’ pages to recommend related products – While blank pages are not ideal, they can’t always be avoided. Offering product recommendations on zero search results or 404 pages makes sure that the customer journey continues.
  • Offer visual search – Powered by visual AI, this option allows customers to upload an image and search for visually similar items in your catalogue. Visual search analyzes the image in question right down to the granular details and surfaces all relevant products in your catalogue.

Here’s a complete list of site search strategies. If you are looking for a more comprehensive guide to eCommerce search, check this out.

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