Picture this: You’re strolling down the aisle of a department store on a mission to find the perfect dress for a special occasion. The store is massive, with racks upon racks of clothing and shelves stocked with accessories. You wander aimlessly, searching for the perfect outfit, but everything falls short of your expectations. You’re overwhelmed, lost, and ready to abandon your search.
This is the epitome of a bad search experience – the average e-commerce abandonment rate is nearly 70%! The good news is – with a well-optimized site search, shoppers can breeze through their online shopping journey and find precisely what they’re looking for with ease.
But according to the Baymard Institute, 42% of sites fail to handle basic search queries. Don’t be a part of that statistic. Let’s make sure your search bar is a standout feature, not a liability.
This guide will explore what e-commerce site search is, how it works, why it’s important, and the steps you can take to optimize it. We’ll also explore the cost of implementing site search and whether you should build it in-house or purchase a solution.
So, let’s dive in!
What is E-commerce Site Search, and How Does it Work?
E-commerce site search is a tool that allows users to search for products and other content on your website. The search engine uses advanced algorithms to return relevant results based on the keywords entered by the user.
Modern site search can also incorporate Machine Learning (ML) to provide personalized results based on a user’s search history and other factors. Behind the scenes, site search involves indexing the product catalog so that the relevant products are quickly retrieved and displayed when a customer searches for a keyword or phrase.
The indexing process involves cataloging all the products on the website, including product descriptions, categories, and other relevant information. This information is then stored in a search index, which is used to quickly retrieve the relevant products when a customer searches for a keyword or phrase. The index is constantly updated to reflect any changes made to the product catalog, ensuring that the search results are always up-to-date and accurate.
Why Does Site Search Matter?
Site search users are 1.8 times more likely to convert. Optimizing your site search enables your customers to quickly and easily find what they’re looking for. Picture this scenario; a first-time visitor lands on your website and is interested in purchasing a very specific pair of shoes. They’ve already made the decision to buy – but if you can’t give them what they want immediately, they’ll bounce.
And let’s not forget the added bonus of being able to boost specific products, deals, and content – talk about maximizing your revenue potential!
So, if you want to ensure that your customers have a seamless shopping experience and keep coming back for more, a well-optimized site search is a must-have.
We’ve got a handle on the basics of e-commerce site search. It’s time to kick things up a notch and see how we can make your search bar the MVP of your website!
Unleash the Power of Site Search:
Put Your Search Bar in Center Stage:
Highlight your search bar and make it the star of the show!
Ensure it’s strategically placed in a prominent area of your website, like the top-right corner, where visitors can easily spot it. On mobile devices, the search bar should have its own line.
Why top right? It’s the most common and expected position. You don’t want to make your users scroll or waste time trying to find it – it should be prominent and big. You can also add an additional search bar that appears as a footer while your users are scrolling through your products.
Implement AI-based search engines:
Artificial intelligence (AI) and ML (ML) are changing the e-commerce industry significantly, and site search is no exception.
Personalization has always been a key aspect of successful e-commerce businesses. However, the traditional methods of personalization have had limitations in terms of their effectiveness and scalability. Advanced search engines that use AI and ML techniques can analyze vast amounts of data, predict customer behavior, and optimize the user experience in real time.
For example, AI and ML algorithms can analyze search queries, click-through rates, and purchase history to identify patterns and trends that can be used to improve the relevance of search results.
Algorithms using these techniques are trained using large amounts of data from your website and user behavior. This data can be used to make informed decisions about the relevance of products and content and predict what users are searching for.
For instance, if a user has previously searched for and purchased running shoes, AI-based search engines can use this information to recommend similar or complementary products during their next search. The result is a smooth, intuitive, and highly effective search experience that engages and converts users at a higher rate.
Fine-Tune Popular Searches:
Track your website’s hottest searches and optimize the results to meet your visitors’ needs.
By keeping a close eye on the most common searches conducted on your website, you can gain valuable insights into the needs and preferences of your target audience. This information can then be used to make necessary changes, like revamping your product descriptions or titles to align with the keywords used in standard searches.
For example, suppose you run an online fashion store and notice that “women’s summer dresses” is one of the most popular searches on your website.
In this case, you can fine-tune your search results by optimizing the product descriptions and titles of your summer dresses to include relevant keywords, such as “women’s summer dresses,” “women’s sundresses,” “women’s casual dresses,” etc. Or you could include a separate tile for summer dresses on your homepage.
Simplify the Search Experience:
- Use predictive search – Take the guesswork out of finding what they want. As users type in their search query, provide them with suggestions to help them find what they’re looking for faster.
- Accommodate synonyms and substitute terms – A person in search of a comfortable pair of shoes may use different terms such as “sneakers,” “athletic shoes,” “tennis shoes,” etc. All of these terms refer to the same product type, but if your search bar is not configured to handle synonyms, a user may be unable to find what they are looking for, even if your website has a large selection of sneakers.
- Enable Filtered Navigation – When users search for a product, they may not know precisely what they’re looking for or have specific criteria in mind, such as color, brand, price range, or features. Filtered navigation allows users to narrow down their results by these criteria, so they can find what they’re looking for without having to sift through a long list of irrelevant results.
- Enable auto-complete and error correction – Offer suggestions for correct spelling and suggest alternative searches if the user’s search is not successful.
Understand Search Intent with Semantic Search:
Semantic search is a type of search technology that attempts to understand the user’s search query and its meaning rather than just matching keywords. It aims to provide more accurate and relevant results by considering the context and relationships between words in a query.
Semantic search technology uses natural language processing and ML algorithms to analyze and understand the user’s intent and then returns results that best match that intent.
Imagine you’re searching for a new coffee maker online, and you type in “best coffee machine for a small office.”
Traditional search algorithms might return results based on keywords, bringing up all the products that include the words “best,” “coffee,” “machine,” “small,” and “office.”
But with semantic search, the algorithm understands the context and intent behind your search query and returns results that are truly the best options for a small office setting. Say goodbye to sifting through countless irrelevant results, and hello to finding your perfect coffee maker in no time!
Never Return Zero Results:
If a user’s search is unsuccessful, don’t return zero results. Instead, offer suggestions for related searches or products that may be of interest. Provide helpful suggestions or alternative products if a user’s search fails. This can include offering related searches or products similar to the user’s search.
Optimize for Mobile:
Half of all online traffic is now on mobile. With the surge of mobile web traffic, it’s crucial to cater to on-the-go users by optimizing your website for their devices.
Here are a few ways to do this:
- Ensure that the search bar stands out and is easily accessible on all screen sizes.
- Use larger images and smaller text on mobile.
- Give users the option to search using their voice.
- Make sure the results page is easily navigable and filterable, even on a smaller screen.
Regularly evaluate your site search to identify areas for improvement.
Track the most common search failures, figure out where most users are bouncing, and make changes to your search algorithms or product descriptions to improve the results.
Whether it’s tweaking your predictive search, fine-tuning your semantic search, or revamping your product titles to align with popular keywords, there’s always room for improvement. By being proactive and data-driven in your approach to site search, you can provide a better, more seamless experience for your users and ultimately drive more engagement and sales on your website.
How much is this all going to cost?
Calculating the ROI of Site Search:
To calculate the return on investment (ROI) of site search, consider the cost of implementation, the cost of maintenance, and the potential impact on sales and customer satisfaction.
If you’re purchasing site search from an external party:
Cost of implementation = Cost of purchase
If you’re developing in-house:
Cost of implementation = Developer cost x No. of hours + Time costs + Cost of maintenance
Should You Buy or Build Your e-commerce Search?
Both these approaches have their own pros and cons. If you’re a massive enterprise, you can afford a truly customized solution. But if you’re a mid-sized B2B company, building site search in-house may not be the best solution.
Building it in-house can be more cost-effective on the face of it, but it requires a significant and continuous investment of time and resources. Purchasing a solution can be more expensive, but it can also provide a more robust and user-friendly search experience.
What are the types of e-commerce businesses?
There are 4 main types of e-commerce businesses that you should be aware of, each with its unique advantages and challenges.
- Business-to-Consumer (B2C) – This is the most common type of e-commerce where businesses sell products directly to consumers.
- Business-to-Business (B2B) – This type of e-commerce involves businesses selling products to other businesses.
- Consumer-to-Consumer (C2C) – This is a marketplace where individuals can sell their products to other consumers.
- Consumer-to-Business (C2B) – This is a unique model where consumers sell products or services to businesses.
What are the three types of searches?
When it comes to searching online, there are three main types of searches that you should know about.
- Navigational Search – This type of search is all about helping users find a specific website or web page. For example, searching for “Amazon homepage” or “NY Times articles” would fall under this category.
- Informational Search – This search query is informational in nature. This could include anything from answering a question to providing data and statistics. For example, someone searching for “The history of chocolate” or “Return policy” would fall under this category.
- Transactional Search – This search type is purchase oriented. Users searching for this type of search are looking for a specific product or service to buy. For instance, someone searching for “Best laptop under $1000” or “Men’s dress shoes” would fall under this category.