Ecommerce Site Search: The What, Why, How and More
Table of Contents
A straightforward, easy-to-use site search tool is vital for a successful eCommerce store. Just think of this: If shoppers don’t find your products easily enough, they might not buy them.
What Is Ecommerce Site Search?
In simple terms, a site search solution in an eCommerce store is an in-built or integrated search engine. Its primary job is to find the product the shopper is looking for. A site search engine typically matches the shopper’s search keywords with the product in your online store.
Ecommerce site search helps a shopper find the product they want to buy in your store quickly and easily. Hence, the site search engine plays a decisive role in the success of your ecommerce store. Look at the site search box below:
It’s clear that the site search feature is an effective shortcut for shoppers in your store. It gives them an idea of the products you sell. A site search feature is also essential to browse your store with the usual navigation options.
Site search includes more than your search box, though. It refers to product ranking, synonym management and faceted search, too.
Why Is Site Search Important for Ecommerce?
As I already mentioned, site search is a decisive interaction point for shoppers on your online store. When your site search works to perfection, it’s efficient, convenient, and fast for shoppers. They can buy the product they want in your store without any hassle.
But when your site search doesn’t work smoothly, a shopper will have an unpleasant experience. The main downside is they will not find the product they are looking for. And as a result, they will leave your store without making a purchase.
Therefore, you need to ensure that the site search experience on your online store is user-friendly. Your site search feature needs to be streamlined so that shoppers can find the products they want without any difficulty. This also places shoppers in control of their online shopping experience.
A smooth, hassle-free shopping experience results in an increase in customer loyalty and shoppers are more likely to convert. Also, they will return to your online store to make more purchases.
On average, search users are 7-10 times more likely to convert than regular site visitors.
Let’s take a quick look at the Four most important factors in eCommerce site search.
1. conversion optimisation
If a shopper can’t find a product in your eCommerce store, they can’t buy it. It’s rather unfortunate but true. So, the main point of conversion optimisation is to optimise closer to the cash.
Include Product Images in the Search Bar Results
One proven way of improving eCommerce site search is to include images of different products in the search bar results, as shown in the image below:
Shoppers can now see the products available in your online store without having to look through all the product pages. Your product images need to be clear in thumbnail form, as indicated by the green arrows. A clear image can be flattering to your product.
Also, the chances of a shopper buying go up when you display the product image along with the product description.
2. User Experience
Imagine you walk into an on-the-ground brick and mortar store. You look around for an item you want but don’t find it. What will you do?
You will ask for a sales assistant. Pretty natural, isn’t it? But nobody is there. Now, what do you do?
You may try some more but with no help around you’ll eventually walk out. Well, isn’t that natural, too?
The site search feature in your eCommerce store is similar to a sales assistant in a brick and mortar store. The site search engine points the way to shoppers in your online store.
3. Time Efficiency
An online shopper’s expectations are high. I’d say they are unrealistic at times. But the real culprit is Google search.
The Google search bar has conditioned online shoppers to think a certain way about your store’s search box as well.
A shopper typically expects comfort and instantaneous results. If the site search in your store doesn’t provide rapid results, the shopper will leave your store and go to your competitor’s store.
So, overall time efficiency is critical for eCommerce sites. A shopper who uses the site search feature already has a specific product or keywords in mind. They visit your store with the intention to buy that product or discover a close match.
So, it’s important that your site search engine delivers accurate and fast results. You need to direct these kinds of shoppers to the right products in your eCommerce store. If you don’t place a premium on time efficiency, you might not get a second chance.
You don’t want to just deliver fast results to the shoppers. Accuracy is something you also need to keep in mind.
It’s useless if your site search can deliver a fast search but doesn’t show the accurate results that users are looking for.
Shoppers who use the site search are those who already have a specific product in mind. So it’s important to give them the search results that solve their queries.
How Does an Internal Search Engine Work for Ecommerce?
Most basic site searches are relatively simple and user-friendly. They feature basic text-matching and usually support indexing of product titles, product descriptions and category structure.
They also support fuzzy-match (allows for non-exact close matches of a visitor’s typed search items), auto-correct, and recognise synonyms (frequently through a configurable dictionary).
Some of the common site search problems include:
- Language processing: stemming – e.g. buys, buying, bought
- Tokenisation: breaking a sentence into smaller segments known as Tokens, etc
- Query expansion: evaluating what a user has typed, indexing – collecting, parsing, and storing web pages, product ranking and so on.
Functionalities of Basic Search Algorithms:
- Break query string into words
- Map out the search query by focusing on known data fields, such as title, features, description, word-by-word
- Display results in rank order based on the location of the query term in the product metadata (for instance, a match found in the product description has less weight than a match found in the product title).
The way the search results are ranked is pretty complex. Even when you have a moderate product range, you can spend countless hours tweaking and redirecting search results.
You may also spend quite some time adding related products at every product level.
Sometimes, it becomes so time-consuming that you might partly or entirely neglect the functionality aspect. And this, in turn, might result in lower conversion rates and a below-par user experience.
You can resolve these issues by opting for first-rate third-party search software.
Which Are the Best Ecommerce Site Search Applications and Why?
1. Elastic Search
Elasticsearch, one of the most reliable and accurate search engines, is used by several top ecommerce brands. More than 3,000 companies use Elasticsearch. Some of the well-known companies that use this search tool include Udemy, Uber, Instacart, Shopify, Slack, Stack and Robinhood.
Elasticsearch is a highly scalable and competitively priced ecommerce search engine that provides real-time search. The key feature of this ecommerce site search tool is it is one of the fastest in the marketplace.
Algolia is a fast site search application that integrates well with most ecommerce platforms. This search tool presents shoppers with relevant search results instantaneously. The main advantage of Algolia is since it comes with a plug-in, it’s super easy to configure for most ecommerce platforms. This highly scalable ecommerce search application is very easy to set up and maintain.
Unbxd automates the whole search and product discovery engine for eCommerce.
The key feature of this search engine is you can personalise the search experience for individual shoppers by profiling every single shopper in real-time. This unique feature will enable you to increase customer loyalty as well as overall customer lifetime value.
4. Fact Finder
Fact-Finder, Europe’s market leader in search, is a powerful application that combines search and navigation along with merchandising solutions. This premium search engine streamlines online searches and powers sales.
The unique features of this search tool include built-in AI capability and Predictive Basket. This intelligent search solution operates across 127 nations and drives sales in 1,800+ online stores worldwide.
Doofinder’s advanced Natural Language Processing (NLP) technology enables the search tool to learn from the behaviour of the shoppers on your eCommerce store.
This search engine can understand what shoppers are looking for by filtering out typos and identifying synonyms, too.
Doofinder can also predict the products that shoppers want to search for and quickly suggest the best results. Doofinder’s faceted navigation enables shoppers on your ecommerce store to apply search filters. They can refine their product search with different filters such as price, size, brand, colour, etc.
What Are the Best Ways You Can Approach Creating an Accurate Search Engine for an Ecommerce Website?
A smooth ecommerce site search requires several things to work in tandem. You really need to follow multiple ecommerce site search best practices.
Only then you can fulfil the unrealistic site search expectations of shoppers nowadays.
There are mainly three factors to focus on in creating an accurate search engine for your ecommerce store.
I’ll briefly cover these three factors: Process, Data and Algorithms.
The search quality and the overall search experience of shoppers are a direct function of the amount of time and care you give it.
When it comes to site search, you cannot improve anything that you cannot measure. In simple terms, it means if you want to improve an eCommerce search metric, you need to measure it.
Let’s look at the most common queries on your ecommerce store that you can measure and improve:
- Null Queries: No results returned
- Abandoned Queries: No clicks
- Reformulated Queries: Constantly modified/changed by shoppers
- Low Conversion Queries: Conversions not satisfactory
These are the top places to check for problems with your site search.
Remember, you need to look at these queries in a rinse-repeat cycle.
Try to come up with the best solutions that make sense in relation to a shopper’s search intent.
This process is ongoing and never stops.
Once you have established a data-driven culture in your site search, you need to get as much data as possible. My main contention is that once you have more relevant search data, you can easily beat the cleverest search algorithms.
So, focus on collecting data that can give you a definite edge in understanding your catalogue and customers better.
An easy way to access your Site’s Search terms is through Google Analytics.
In Google’s latest version of Analytics ( GA4), it is possible to access search terms by going to Real-Time Reports and following the path: Real-time -> Event count by Event name -> view_search_results event -> search_term parameter.
You can transform both the product catalogue and the visitors queries into a better-structured form by following this process.
Conventional keyword-based searches can be tricky.
A basic site search tool will not understand that in the query “orange blue cap,” the most important keyword is cap. The shopper is looking for that product, and orange-blue is a ‘feature’ of that product.
The following examples show the critical need to understand the word that carries the most weight in a multi-word query:
You have so far invested your valuable time in an accurate data-driven process as well as in the right systems for gathering as much data as possible. The next step is to put in place algorithms that are capable of constantly learning and calibrating themselves.
It becomes easier now to learn the association between words and products, and you can keep amplifying those associations.
For example, on Google Search, try “cleaning cloth” on sunglasses, shoeshine kit, computers, electronics and home furniture.
Notice how products that may not directly contain the words cleaning or cloth show up. These were learned mainly by learning the association of “cleaning cloth” with other words. The other thing is they were also learned through the interaction of shoppers posing this query with the different products that were returned.
The point is there is no shortcut to getting a perfect search. You need to focus constantly on these three factors: Process, Data and Algorithms.
The improvement you see every day is the only measure. Hence, you not only need to automate, but you also need to make everything a self-learning system as much as possible.
Top 9 Ways to Make Your Ecommerce Site Search More Effective
Customer acquisition is harder than ever nowadays because customer expectations are higher than ever.
If you fail to leverage the full power of ecommerce site search, you are going to miss out. So, you need to configure your site search intelligently to gain a competitive advantage.
You can achieve this objective by following the ecommerce site search best practices outlined below.
1.Make the Search Box Easy to Find and Easily Usable
A shopper’s decision to use the search box to find products matters a lot. Hence, the prominence and visibility of the search box on the page are decisive factors. They determine how easily a shopper can find the product they want.
If the site search feature is important to your online store and you want shoppers to use the site search box, then you can consider imitating the design of the search box in the Ebay.co.uk web store:
But I’ve also seen some ecommerce stores sidelining the search box in the design of their web page.
Look at the search box on the Google Merchadise ecommerce store below. The problem with this type of design is the search box can be difficult to spot.
So, please focus on making the search box easy to find and easily usable.
2. Keep the Search Box Placement Consistent
This ecommerce site search best practice is so obvious. But it’s still important to bear in mind that when you design your web store pages, make certain that your search box placement is consistent.
Your search box must be located at the same spot on each page of your store. This way, you make it easier for shoppers to find it.
3. Add Placeholder Text To Encourage Searches
Placeholder text in the context of ecommerce site search would mean adding specific suggestive text, so the user has some kind of ‘anchor’ to work with.
You can see this in Contact Us forms where for “Full Name” the box in front may contain “First Name Last Name” as an anchor for the person to enter their name in that order.
Likewise, you could include some text in the search box that indicates a product related to a specific niche.
This sample text would help guide a visitor when they want to type something. For instance, a store selling apparel may have their placeholder text as the highest-selling products, or they may even vary it depending on the time of year, e.g. Christmas Gowns.
4. Self-Learning Search (Auto Suggestions and Grammar Corrections for Misspellings)
The most effective way of making site search easier for your shoppers is to include auto-complete suggestions.
This feature doesn’t restrict search to a single category. Instead, it simplifies the shopper’s task of filling the search box, as shown here:
Auto-complete suggestion enables shoppers to choose from a dropdown menu of some common suggestions for what they are searching for.
Site search bars typically don’t have spell checkers. However, that shouldn’t necessarily lead to displaying zero products. Instead, the search function should show the closest match.
If you don’t plan for misspellings, a large percentage of your shoppers will assume – wrongly – that your store doesn’t have the product they want to buy before they realise they made a typo. It’s rather unfortunate but true.
Shoppers will think you have a bad search, or they’ll think you don’t stock the product they want. Either way, you’ll get the blame. And they may not even realise it was a user error.
You can sidestep this issue by optimising your search bar to handle simple misspellings, as shown here:
This way, you can ensure you don’t lose any business from your engaged shoppers.
5. Utilise Data to Refine Site Search Parameters
The analytics data on site search gives you insights into what the users are searching for when they visit your ecommerce store. Once you have enough data, you can use it to optimise Site Search.
You can plan for new products or add similar phrases/words to the product title/ description that site visitors are using to look for products.
6. Deliver Personalized Results Using Machine Learning
Poor ‘site search’ results will lead to people leaving the site unsatisfied. This will result in reduced conversions, revenue and an overall negative impact on your Site’s SEO.
One way to address this is to build a strong site search solution with machine learning capabilities. This can deliver highly personalised results based on individual shopper behaviour.
An AI-powered search solution learns from the data on the user- their on-site and past shopping behaviours, purchases, and of course the intent behind the search. It returns personalised results to the user when they search for the query.
The increase in voice and visual searches also opens up more possibilities for AI-powered site searches.
7. Synonym Results
Other than personalised results, factor for synonym-based results.
This type of search result will help the user find the product they’re looking for. They will see various and relevant products from their search queries.
Synonym results can be built using Natural Language Processing (NLP).
8. Avoid Zero Search Results
A “Zero Search Results” is the web page displayed to a shopper when your store’s internal site search engine isn’t able to locate any product relevant to the shopper’s query.
A well-designed site search engine can present a shopper with the best matches by dynamically breaking down the semantics as well as the structure of a complex search.
This feature permits the search engine to return relevant results, even when a shopper misspells their query or they don’t use the exact terms as the concerned product listing.
Finally, if there are no relevant results to show, you may display a customised message such as:
- “Sorry, nothing found for…”
- Ask the user to correct the spelling
- Display the closest possible match or a pre-selected list of products
9. Optimise for Mobile (functions and results)
Anywhere between 50%-80% of site traffic comes from mobile devices nowadays. This includes e-commerce sites.
As a result, optimising site search for the mobile experience is critical.
Make sure that your site search is visible and easily accessible on smaller screens. If a searcher is confused about site search or unable to find it, that’s likely a lost sale for your Business.
Ecommerce Site Search: Summary Checklist
- Conversion optimisation – make finding a product in your web store easy
- User experience – ensure navigational features are exceptional
- Site speed is closer is less than three seconds
- Understand your web store’s Process and Data
- Pick the most suitable site search engine for your web store
- Make the search box easy to find and easily available
- Keep the search box placement consistent on all pages of your web store
- Add place holder text to encourage searches.
- Install self-learning search with auto-complete suggestions and grammar suggestions for misspellings
- Avoid zero search results
- Optimise your ecommerce store for mobile search
We have finally come to the end of this in-depth blog post. Are you looking to fine-tune all the essential design elements on your eCommerce store and boost your business revenue?
If your answer to my question is yes, then please speak to our friendly team of eCommerce SEO experts.
We specialise in optimising your eCommerce Store for SEO, User Experience, and Conversion Optimisation. Get In Touch With Us For a No-Commitment, Initial Consultation.