Site Search 101: What is Autocomplete Search and Why Do You Need It?

The text auto-completion feature is omnipresent now. You are likely to use it every day without knowing a proper name for it. Every time you show up on Google or Amazon and start typing into the search bar, the search dropdown offers you suggestions on what you might be looking for. In short, this is what "autocomplete" is. But except for the obvious benefits of saving web users' time and effort of typing, the autocomplete has a lot more to it.

This article will take a deeper dive into the user experience of autocomplete and how you can benefit from implementing this feature on your eCommerce site.

What are Autocomplete and Predictive Search?

Autocomplete displays search query suggestions as you type in the search bar. Right from the first typed characters, the search engine algorithm will generate a list of predictions of how your query could be completed. For example, in the car electronics store, if you type in "moun", the engine would suggest "windshield mount kit" or "phone car holder mount."

Below is a visual example of autocomplete:
Autocomplete search widget on Target.com
Target.com search autocomplete
The autocomplete feature is also known as "search-as-you-type," "autosuggest," or "predictive search." These terms are often used interchangeably.

The beauty of the search autocomplete is that the predictions change with each keystroke to provide increasingly accurate suggestions.

Why Do You Need an Autocomplete Feature?

Autocomplete has been with us for more than 15 years since Google introduced it in 2004. The practice of predictive search has quickly become a welcome part of our daily internet usage, helping us discover answers to questions before we even complete the questions themselves.

Interestingly enough, though some say quite predictably, as search is becoming more advanced, the users' search skills and ability to implement different search strategies to solve problems are getting weaker. This is perfectly illustrated in the research published by Nielsen Norman Group.

It was a matter of time before users started having certain expectations of the search performance on eCommerce sites as well. And as of today, 96% of major eCommerce websites offer the search autocomplete experience to their shoppers to meet those expectations.

Having said that, it is worth pointing out that even the most popular platforms used for creating eCommerce sites, like Shopify, Magento, and WooCommerce, do not have the search autocomplete feature by default. Their native search functionality is super basic and is unable to give instant results of high relevance to the input query.

The absence of autocomplete can be especially painful for mobile users. With the limited screen, it is harder for them to type. However, when the search autocomplete is there, the shoppers have to type fewer characters to see the relevant search suggestions. That means greater user experience and translates into customer loyalty. After all, who would want to repeat the experience of searching in an online store on mobile when the search took too much time and effort to use?

Integrating autocomplete functionality into a website has become a necessary component of building an online store. Autocomplete helps the user in more ways than just saving the effort of typing. The other key benefits:

Avoids zero results page. When configured right, autocomplete suggestions almost eliminate the chances of a no results page. Primarily, it does so by suggesting users' most popular queries related to the input one that are guaranteed to retrieve results. Next, autocomplete is typo tolerant, preventing showing no results because of an accidentally misspelled word in the search box. This is critical for products like, say, print cartridges that are typically searched by quite specific names: Epson 603, or HP 304.

Engages users with more content. Autocomplete suggestions are, by definition, highly interactive. If the autocomplete widget is designed well, it articulates the search query better, navigating through the site, and shows non-product educational content. For this reason, the widget can be broken into sections and provide "Products," "Categories," "Blog articles," and other suggestions.

Reduces in-store friction in the customer journey. Search suggestions provide instant smooth navigation to the products shoppers are looking for. Thus, they shorten the customer journey to the shopping cart. For repeat customers, AI and machine learning are applied to offer more personalized search suggestions based on the previous product view history, which shortens time on searching and increases conversion chances.

Improves user experience. Assisting site visitors to find what they came for faster and simpler provides customer satisfaction with your service and on-site experience. This contributes to the brand image-building and can lead to a growing number of repeat customers.


We have a whole article dedicated to the website and customer journey optimization through site search. Read it if you want to learn more about your opportunities with the improved site search.

Autocomplete in Action: World's Best Practices

At the end of last year, the Baymard institute published the results of their latest eCommerce website usability testings. The findings revealed that 27% of top-grossing eCommerce sites have severe autocomplete usability issues. They also give side-to-side examples of good and bad autocomplete implementations.

In this part of the article, we would like to highlight the key features that, in our opinion, should absolutely be present in the search autocomplete of every eCommerce website:

Typo-tolerance. Showing a user a "no results" page because of an accidental misspell in the query is not an example of a good user experience. So, spell check and automatic typo correction are a must.
Search suggestions on Amazon
Amazon.com handles a miss-spelled brand name perfectly
Instant results. The speed the autocomplete is expected to perform is lightning-fast - search as you type speed. If it feels slow to the user, it indicates poor performance - the idea of autocomplete implementation is to speed up the search process and not just follow the latest design trends.

The differences are highlighted. The predictive portion of the auto-suggestions should be in a bold style, making it easy for a user to distinguish between the exact match of the typed query and the predictive suggestions.
Highlights on Amazon.com search
Amazon.com draws attention to the search predictions by highlighting them
Visual hints. The autocomplete dropdown should be visually organized into sections by suggestions type. For example, "Products', "Categories," "Pages" allow the user to quickly scan the results and help orient themselves within the site. The autocomplete should be able to display thumbnails of product images, assisting visitors to reach the desired product directly from the search box, skipping the search results page.

Below are a few inspiring examples from our clients:
Autocomplete search on Sandler Boot Shop
Sandler.com.au autocomplete
Kentbrushes Search with autocomplete feature
Kentbrushes.com autocomplete

How Сan You Implement Autocomplete?

There are several ways to implement autocomplete on your eCommerce website. The one easy and low-cost way would be using the "out of the box" site search solution.

The Searchanise Instant Search is installed in one click with no tech knowledge required. The plugin will add the search dropdown menu to your search box and display the automatically generated search suggestions starting from the first typed character. The Searchanise Instant Search was designed with the world's best practices in mind, but you can always customize the look and feel of the search drop-down widget as much as you want to.

And the best part of it all - Searchanise monthly plans start at the cost of two Starbucks lattes!
Want to explore your opportunities with Searchanise? Select your platform from the list below, and you will have a 14-day trial period to appreciate the new power your store can have:
API integration
Can't find yours on the list?
Searchanise advanced API and API docs will help you handle any integration.
Contact us for more info.


Ekaterina Kopylova - Marketing Manager
Ekaterina Kopylova
Marketing Manager at Searchanise
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