Did you know that poor search experience is the reason 80% of consumers leave websites?

We are here to help you avoid this frustrating situation.

Let’s delve into the top 8 best practices for eCommerce search, and we won’t stop at theory alone. We’ll back these practices with practical examples. Whether running a small boutique or managing a sprawling online marketplace, these best practices are the compass points to help you win your customers’ hearts and boost sales.

Implement Autocomplete and Suggestions

This feature can offer your customers a list of popular searches they can select from while typing into the search box. They don’t have to finish typing the entire query; the system understands their intent and guides them accordingly. This saves time and reduces the chances of spelling errors or typos derailing the search.

However, pay attention to the number of autocomplete suggestions so that users can view the list at a glance. The number of autocompletion suggestions on the desktop should not exceed 10, while 4 to 8 is acceptable for mobile users. (Source: Amazon)

We suggest highlighting the predictive aspect of the query suggestions, like using a bold style. This will draw users’ attention to the most relevant terms to complete their queries.

You can suggest more than just search queries. The instant suggestions can include products, collections, pages, and even blog articles. Your customers may want to know about the shipping and returning policy or product manuals, so pages and articles will be useful in these cases.

A great site search should instantly suggest products, popular search terms, and other necessary information as users are typing. (Source: Healthy Options)

Use Semantic Search for Contextual Matching

Semantic search is not just a strange term nowadays; it’s a revolution in how we interact with digital information. 

Unlike traditional keyword-based search, which matches queries to specific words or phrases, semantic search aims to understand the context, intent, and meaning behind the user’s query. It’s like having a conversation with a search engine that comprehends your language, not just your words. 

At its core, semantic search relies on Natural Language Processing (NLP) and machine learning algorithms to decipher the nuances of human language. To provide more accurate and contextually relevant results, it takes into account synonyms, related concepts, and even user search history.

This ultimately improves search results and shopping experience.

You can see the difference in the effectiveness between the two types of search. Compared to search based on keywords, semantic search can understand user intent better and return relevant results (Source: Boost AI Search & Discovery)

Make Your Search Mobile-Friendly

We can all see that many people search for and buy products on their phones. The proof is that 73% of all online shopping occurs on mobile devices. 

But what contributes to a good mobile search experience? It is more than ensuring that your website fits on a smaller screen. Regardless of the screen size, search results should load quickly and be easily accessible; search buttons should be easy to use.

To make the search bar outstanding but still in harmony with the overall design, consider choosing a white background color for the search field and a thin border with low opacity. The magnifying glass icon needs highlighting, too.

You can also add placeholder text to convey a conversational message, like Fenton & Fenton using the “What are you looking for” phrase. (Source: Fenton & Fenton)

Try Visual Search

Visual search can transform the shopping journey into a visually intuitive process. Your customers can simply snap a photo or upload an image of a product they like, and the search engine instantly returns items from your inventory. This streamlines the search process and provides a more engaging and user-friendly experience.

With most online shopping happening on mobile devices, visual search caters to the needs of mobile users and eliminates the need for typing queries on small screens.

Of course, successfully implementing visual search requires technical assistance. You can choose from existing visual search platforms, such as Google Cloud Vision or Clarifai, or use ML frameworks to build custom models. 

Enable Product Search on Collection Pages

Another spot you can try putting a search bar is the collection page. In-collection Search is the best approach to quickly return the desired items within a collection without scrolling too much through the page.

Another search bar is implemented on the left to empower users to find specific items within a collection quickly. (Source: Nuts.com) 

This feature will come in handy when you have a large collection with huge amounts of SKUs. 

If not, carefully consider whether you should place another search bar. The key is that this enhancement needs to align with the overall user experience. If enabling in-collection product search doesn’t disrupt your eCommerce page’s visual harmony and provides users with clear value, it can be a beneficial addition.

Integrate Filter into Search Result Page

You already know that customer needs are different. When users enter a search query, filter trees complement their search by providing instant options for refining results.

Filter trees can be tailored to match your product categories and attributes, allowing you to curate personalized shopping journeys without navigating off the site.

Esports Gear set up various options for their filter tree on the search results page for the “mouse” search term, like the delivery option, availability, brand, and price. This will save Esports Gear valuable time in customer service and keep the customer engaged and in “purchase mode.” (Source: Esports Gear)

YOU MIGHT ALSO LIKE: TOP 7+ Shopify Filter Apps For Boosting Sales 

Showing Alternative Product Suggestions To Boost Conversion

About 56% of consumers will likely continue shopping in an online store if an alternate product is suggested instead of no search results. Sadly, this feature is available to only 34% of brands. They’ll abandon your website if you leave them with the “No search results” page.

Here are some things you can do to avoid the “no search results” situation:

• Suggest similar search queries that return results 
• Suggest similar or related products to what users are searching for
• Suggest trending keywords or products in your store
• Offer personalized results based on their search history 

Don’t leave your customers with a “No search results” notification. Suggest other keywords with the “Did you mean” phrase and other related items to keep them on your site longer. (Search: Boost demo site)

Analyze Site Search Data

You will lose your chance to win over customers if you don’t understand their search behaviors and patterns. Ensure that the search solution you’ve selected comes with a report on searching behavior. 

Some important metrics are high-traffic search terms, low-performing keywords, common misspellings, and detailed sales metrics like revenue, order count, CVR, etc.

Attain powerful numbers that help you define suitable merchandising and product recommendation strategies to convert more with search.

With the detailed report of search functions, you’ll know which items customers are looking for and which ones you don’t have on your site search results. (Source: Boost AI Search & Discovery)

To sum up

Search is an essential function on your eCommerce website to enhance product discovery, drive engagement, and ultimately boost conversion rate. In the competitive eCommerce landscape, where user experience is paramount, optimizing the product search isn’t just an option; it’s a strategic advantage and a must-have for any online store looking to thrive. 

We hope you will successfully guide your customers through the aisles of your digital store with precision and help them find the products that resonate with them.