How Ecommerce Site Search Can Create a Competitive Advantage

How Ecommerce Site Search Drives Growth

Imagine: The greatest product selection you’ve ever seen. Or, could see, were it not hidden in the depths of some labyrinthian nightmare.

When you’re delivering a poor ecommerce site search experience, this is exactly the hellscape you’re delivering (Sans minotaur roaming the halls).

You can leave all the breadcrumbs or string you want, and oftentimes people might find what they want. But efficient ecommerce site search practically guarantees they find what they want.

And, it drives sales: those using site search have 1.8X the conversion rate of typical site traffic.

With the right approach, some AI-powered advanced semantic search functionality, and a little magic, you can make ecommerce site search a core part of product discovery, too. Before you start enhancing the user experience and dishing up search results and product recommendations on your online store, let’s take a look at the basics.

What is ecommerce site search and how does it work?

At the most basic level, ecommerce site search is a search engine solution you can integrate into your ecommerce store.

Thinking of site search as a barebones search tool for ecommerce platforms is selling it short. With natural language processing (NLP), ecommerce site search can deliver personalised recommendations based on search and purchase history, pull the right products with semantic search, and more accurately navigate your entire product catalogue.

“But how does this all work?” you might be wondering.

1. Site search solution features.

A number of site search features make today’s search sorcery possible.

Faceted search is a feature that allows users to refine their search once they have a listing of initial results. For example, if a user searches for a search term like “raincoat,” they can apply filters based on faceted classification to limit search results by colour (e.g., blue raincoats), size, brand and more.

Product ranking is another feature you might employ on site search, which allows you to give certain products more weight than others. But, this is quickly becoming obsolete, thanks to searchandising — the practise of using AI to automatically sort products based on inventory and margins.

Multimodal search and voice search are two increasingly common search types that you should offer in 2026. With multimodal search, users can search via image or picture, audio, or voice, and at the same time. Meanwhile, voice search is a straightforward product search done via voice.

Semantic search in ecommerce breaks apart the parts of a query to identify the difference between product categories and product attributes. Some search solutions use natural language processing (NLP), which helps search engines match not just keywords or structure but the intended meaning.

2. Types of search queries.

A search query is what the customer enters or speaks into the search tool. There are multiple types of queries, some of which require more advanced search functionalities (like those mentioned above).

Exact search: When a customer’s query matches a specific product name or model number exactly. For instance, searching “BigCommerce-Branded Leopard Parachute Pants,” which would pull up exactly those.

Product type search: A search for a category type, rather than specific product. For example, querying simply, ’Pants’ instead of the exact product name in the last example.

Problem-based search: When a problem is the focus of the query, rather than type or exact title, it’s a problem-based search. For instance, “Pants to help with my boring fashion” or “Relief for dry eyes.”

Guided discovery: A guided discovery search can take the form of a quiz or AI-powered form that helps a customer with product suggestions. For example, a “Parachute pants print match finder” quiz. Or, for something that actually exists, check out the ASICS Shoe Finder.

Non-product: A non-product search is done when someone needs help finding something else on your site, like information about your shipping policy, customer support, and so on.

3. Query qualifiers.

Customers use query qualifiers to further fine-tune a search, adding in anything from product details to specifying certain features they want surfaced products to have.

Qualifiers are generally lumped into several types:

• Compatibility: These qualifiers help surface only products that work with another, like “Screen protector for Samsung S25 Ultra” instead of “Screen protector.”

• Feature: A feature qualifier is used to show products with specific features, like “Glass screen protector” or “Privacy screen protector.”

• Use-case: A use-case qualifier is just as it sounds, prioritising products that fit a certain use. For instance, “Best case for throwing your phone off a mountain.”

It’s important to note that many barebones site search tools will fall short as queries become more specific. On the other hand, advanced search that utilises NLPs and the like will have a better time handling these queries.

Agentic AI, like Gemini and Perplexity, is also increasingly common in the product journey. Having product pages that are prepared for agentic AI is more important than ever, as these pages are more likely to show up when customers use their favourite AI tool to help their search, with queries like, “Help me find the best pair of pants to wear at an 80s-themed party taking place in July.”

The effectiveness of ecommerce site search

When someone simply lands on your site and pokes around, you don’t necessarily know their user intent. But, if someone shows up and starts engaging with the site search functionality? Oh, they lookin’ with some interest.

Consider this: 24% of ecommerce traffic is engaging in site search. That same group? 44% of ecommerce revenue.

Don’t forget that earlier stat either — site searchers have 1.8X the conversion rate of those aimless, non-searching wanderers. In other words, your ecommerce website needs to deliver a great site search experience. Otherwise, those high-intent users are heading to your competitors.

High-impact benefits of ecommerce site search

Imagine walking into your favourite local retailer of books. You can find the bestsellers right there on the end cap. But, what about those deep cut SKUs? That niche horror about the possessed family hamster?

Without a helpful employee or a search kiosk, you could wander that bookstore for hours trying to find what you’re looking for. If that same store made it easy to find what you wanted and delivered it at a great price? You’re going back again and again.

No, that scratching sound isn’t the hamster. It’s the benefits of ecommerce site search, cause we’re just scratching the surface.

1. Dramatically higher conversion rates.

Remember: Searchers have 1.8X the conversion rate of average site traffic.

The opposite is also true for a poor search experience, which will only hurt your bounce rate. So much so that 66% of shoppers say they run to Amazon if they can’t find what they’re looking for on a site.

There’s also an argument to be made that great site search can increase average order value (AOV). It would be an argument because honestly, there aren’t any credible stats out there. HOWEVER, there is proof that searchers are converting more often than those who don’t, so there’s always the chance some of those people are buying more than they planned to because of your great site search functionality.

2. Frictionless customer experience (CX).

Reducing friction and quality customer service go hand in hand. Great site search is part of this. Think of your online store as a brick-and-mortar. If you help people find what they want, they’re far more likely to come back than if you leave them to fend for themselves.

3. Actionable zero-result analytics.

Customer data is a precious resource in the ecommerce world. Site search? There’s gold in them there hills.

First off, zero-result analytics help you determine where searches are coming up with nothing. If a certain query is commonly searched, yet no products come up, you can dig into this and figure out why. Do you not offer this product? Or is one of your products not named or labelled in a way that would better resonate with customers?

When you’re providing a great search solution that people want to use, you open the door to rich historical data, real-time search analytics, and an overall more complete picture of what your customers want.

4. Reduced support overhead.

Back in the day, when stores had yet to replace humans with touchscreens, a big role of support was helping customers find things. The same is true for site search, which can help customers find not just products, but also departments and pages within your site.

If people can’t find what they need on your site, like your return policy, they’ll wind up talking to your chatbot. If that doesn’t pan out, a real human could get looped in, all so they can point the person to a page.

Great site search can and should serve up exactly what the customer is looking for, reducing support overhead.

10 best practises for optimised ecommerce site search

Ecommerce search engines can be a boon to your site, helping direct traffic, surfacing relevant results and recommended products, and ultimately saving the day. But, you can’t just throw a site search tool on your site and call it a day. Well, you could, but that’d be silly.

These 10 best practises can help you deliver an ecommerce site search experience that’s optimised, effective, and brings people back.

1. Allow for errors and utilise autocorrect.

What’s the most-difficult-to-spell product you carry? Skin care products with niacinamide, perhaps, or maybe headphones with noise-cancelling (or is it cancelling?).

Even if all your products are easy to spell, you’ll still need to account for typos and autocorrect — especially considering the percentage of consumers who shop on mobile devices. (That’s 59% of worldwide ecommerce purchases, by the way.)

Make sure your site search is optimised to understand phonetic misspellings and typos so simple mistakes don’t return an empty results page. An NLP-based search tool can boost search effectiveness by enabling interpretation of a query’s intended meaning and helping to parse the meaning of long, complex search queries.

On the AuthenTEAK Outdoor Living shop, Adirondack chairs are a prominent category — and their on-site search engine helps direct you there even if you’re not sure how to spell “Adirondack.” Which, who is? It’s chaos.

2. Provide synonym results.

Ensuring your search engine understands synonyms will help people find the products they’re looking for. In some search solutions, this is something you’ll need to add manually based on your needs; in others, these synonym libraries are built automatically using NLPs.

3. Make the search box visible.

This should go without saying, but make sure users can see your search box.

There are several usability-related best practises around search bars you can stick to to help. Above all, though, this isn’t a place to get creative. Place it where people are accustomed to looking for it, and make it very easy for users to discern exactly what it is and how to use it — e.g., by including a visual icon of a magnifying glass, which is widely understood to refer to search.

4. Don’t allow site search to end with nothing.

If you have a high-intent shopper on your site, the last thing you want is to send the message that you don’t have an item for them. That’s why it’s important to make sure common searches return some kind of results.

If you don’t have relevant products to return, set up your solution so that it can recommend related products instead of returning an empty screen. People have plenty of time to stare into the void, they don’t need your ecommerce site to help.

5. Rely on data to refine future site search parameters.

The analytics from your search solution can give you a wealth of insight into what your customers want and how they think and shop. Once you have enough data to draw conclusions, you’ll be able to see if customer vocabulary aligns with what’s on your product pages and, if not, take steps to connect them. 

A few search parameters to start with are:

• Percentage of searches with AI attribution: This is a friendly reminder to optimise product pages for agentic AI so your brand shows up when people chat with Gemini, GPT, etc.

• Searches that are image-based: Make sure your product pages have high-quality images and great alt text to support them.

• Zero-click percentages: If people aren’t clicking, check for whether results are relevant to the queries.

Don’t be afraid to make tweaks as you monitor search performance. Just be mindful of making too many changes at once, as it’ll be difficult to determine what made an impact.

6. Configure mobile search functions.

Just as you should have a great mobile site, you should also ensure site search works well on mobile devices.

As mentioned earlier, allowing for typos and including autocorrect or autocomplete suggestions is huge here. People can and will make typos on their mobile devices. (I promise you, I brew it all the rhyme.)

Part of this overall great mobile site search experience is making sure people can find your search bar on the mobile site. Test it and make sure it’s easy to find and navigate, and that results are also easy to parse through.

7. Use machine learning to deliver personalised results.

A search solution with strong machine learning capabilities can aggregate information on products and individual shopper behaviour, understand product and attribute relationships and identify complex patterns to return highly personalised results.

8. Incorporate visual search.

Google Lens continues to grow in popularity, making it easy for people to run visual searches through their phone’s camera. As of May 2025, Google’s Sundar Pichai said the tool had already been used to run 100 billion searches that year.

Visual search is likely to continue this forward trajectory, so incorporating it is a must.

There are numerous third-party tools and integrations that can make this possible, as well as custom API development. For example, BigCommerce has more than 30 search integrations right on our marketplace.

9. Utilise voice search and discovery.

There’s no single agreed upon (Read: credible) stat on voice search use, but, like image search it’s a good idea to implement it as well. And, just like visual-based searches, this can be accomplished using third-party tools or custom APIs.

10. Embrace searchandising.

With all the advanced search tools available, you can searchandise like there’s no tomorrow. This means:

• Optimising relevance to ensure results are consistently meeting query expectations.

• Moving certain terms up in the search results during campaigns or promo periods.

• Featuring great alternative products when a no-results situation occurs.

• Including quality visuals in search results.

• A/B testing search performance over time.

Think of searchandising as an extension of your ecommerce merchandising efforts. Your goal is for the great product presentation one would expect on your homepage or product pages to carry right over to search results.

Popular ecommerce site search providers.

You can only do so much yourself when improving ecommerce site search. You can choose where the search bar appears, whether it looks like a text box or a giant hoagie customers carve into. But, a trusted search provider is how you make the real, advanced, algorithmic magic happen.

Algolia.

Algolia is one of the most recognised names in AI-powered search and discovery, serving more than 18,000 businesses and 500,000 developers globally, while processing upwards of 1.75 trillion searches per year.

Algolia was built API-first, which makes it possible for developers to have more control over search and behaviour. With in-depth analytics, merchandising functionality, and AI-powered algorithms, it offers both functionality and depth.

Best for: If you’ve got a developer-savvy team and are mid-market or large/enterprise-level, Algolia is a great potential candidate.

Constructor.

Constructor is an AI-native search and product discovery platform built with enterprise ecommerce in mind. With clients like Sephora, Petco, The Very Group, and Fisheries Supply, Constructor is no stranger to big companies.

Constructor runs on first-party behavioural data, catalogue data, and inventory data to personalise results for users. The platform’s unified approach allows one touchpoint to influence another, making it great for companies with large customer bases, spread across a number of channels.

Best for: Large ecommerce brands wanting a search engine that’s optimised for revenue, conversions, and profit over search relevance.

Elasticsearch.

Elasticsearch, powered by Elastic, provides search functionality for more than 34,000 companies around the globe.

Elasticsearch supports faceted product search, semantic vector search, real-time catalogue indexing, and even custom relevance tuning. All of this makes for a search platform that can adapt on the fly.

Best for: Companies needing highly customisable search, technically mature organisations with the engineering teams to support customisation, and those requiring extreme scalability.

Yext.

Yext offers a cloud-based platform, which goes beyond basic search to provide an AI-powered, agentic marketing solution, serving more than 2,500 enterprise clients.

Yext has their own unique offering, the Knowledge Graph, which visualises the relationship between customers, products, and locations. With the Knowledge Graph, you can go beyond basic search analytics and focus more on the holistic customer experience.

Best for: Large brands with multiple locations, numerous channels, and equally distributed customer bases can benefit from the unique approach of Yext.

Nosto.

Nosto is similar to Yext in that the platform isn’t just a site search tool, but an entire experience platform, focusing on everything from site search to post-purchasing and upsells and beyond.

Nosto offers advanced, personalised search, powered by AI. On top of this, the platform makes it possible for brands to segment searches, surfacing different results to different customer segments. And, with integrations to platforms like Klaviyo, Nosto can pull from email behavioural data to shape results.

Best for: Mid-market to enterprise retailers who want to unify search, personalisation, and merchandising under a single platform with minimal reliance on developer resources can benefit from Nosto.

Bloomreach Discovery.

Bloomreach Discovery is the search and merchandising product within the broader Bloomreach Commerce Experience Cloud, serving more than 1,400 brands from around the world.

Bloomreach uses a proprietary AI that’s been trained on historical ecommerce behavioural data from across their platform, allowing for powerful search and merchandising personalisation. This includes advanced product recommendations, content personalisation and automation, and more.

Best for: Large ecommerce operations and enterprise retailers that need a deeply integrated platform connecting AI-powered search with personalisation, content, and marketing automation under one roof.

Coveo.

Coveo is an enterprise AI relevance search platform, serving more than 3,500 customers worldwide.

One of Coveo’s standout features is a “personalisation-as-you-go” functionality, which pulls data from your product catalogue and pairs it with real-time shopper data. From there, you can offer real-time intent rankings for search results, offering a hyper-personalised search experience. On top of this, their platform can sync with customer support and internal knowledge management data from within your platform.

Best for: Enterprise and B2B retailers who need a unified AI search platform spanning ecommerce, customer support, and internal knowledge management — particularly those already invested in an extensive customer database.

The final word

Perfecting ecommerce site search takes time. Just like escaping the labyrinth. But, with a calculated approach, determination, and a ton of testing, you can figure out what works best for your team and your ecommerce setup.

Start by auditing your zero-results page, benchmark current search-to-conversion rates, and begin your hunt for the right search partner.

Speaking of which, BigCommerce offers a comprehensive, headless ecommerce platform that integrates with numerous trusted AI-driven search solutions.

See for yourself how BigCommerce can provide you with the perfect platform on which to build a scalable, searchable store.

Site Search in Ecommerce FAQs