Search engines use algorithms to fetch information and deliver it. Over 68% of websites offer poor site sorting results and 72% of the sites fail to meet user expectations.
This means we all need better search engines to work with. However, making eCommerce search engines more like conventional search engines isn’t the solution. There is a lot more that users can do to improve their eCommerce product search algorithm. This is where site discovery comes in.
Search vs. Search Algorithm: Understanding the difference
An effective eCommerce search is when the customers know exactly what they want. For instance, a customer can search for a 5 feet tall bookshelf with wooden paneling and the search engine will filter out the results. This is where the search engines perform the search or try to do so. However, most engines these days focus on natural language search.
While this simple method helped millions of eCommerce customers globally in the beginning, things are changing.
Why is it Different now?
Now that the eCommerce site dynamics have changed so much, it is becoming increasingly difficult for users to navigate through the results and find optimal products.
For instance, users searching for the term mentioned above, i.e. 5 feet tall books shelf with wooden paneling, find that there are no products available. On the other hand, the search engine may show something like 404 results for bookshelves.
You may think that those results are for bookshelves that you want, but they aren’t. People who add “filters” to their searches end up narrowing down the results that do not resonate. A simple comparison between an eCommerce search and a Google search can also help you understand this.
What can you do?
Users need to understand the importance of precision when it comes to search engine results, and so do companies. It is not wise to burden the consumer with half-related products on their search results in hopes of helping them reap better results.
Instead, a better search and discovery balance can help the company, as well as the consumers, meet their goals. This is because the discovery element will not only prompt better results but also streamline them by adding important features like location into the mix.
Several contextual filters can help users get a streamlined interface. Common filters like age, location, device differences, etc, can be excellent additions.
Things like these can help people find other products that they may not have realized they needed.
eCommerce Search and Discovery: The Tools Used
Regular internet users and business owners both need to know how the eCommerce search and discovery algorithms work. This applies to companies that want to improve their eCommerce product search algorithm. Thus we are going to talk about how these eCommerce searches and discoveries work.
The system uses a set of tools to create full contextual results and an enjoyable user experience on-site. This allows users to make their internet searches educational instead of laborious. Let us take a quick look at these tools ahead.
Leveraging search bars
The search bar can help open windows discover better results. Most of the search bars on eCommerce websites have a drop-down menu when you click on them. The drop-down menus have suggestions, common FAQs, and popular queries for customers to refer to.
Moreover, options like auto-complete are a predictive method to help customers find well-suited products on eCommerce sites. This also uses the user search context to determine what the user may be looking for in results.
Accurate auto-complete options can improve the eCommerce site experience by as much as 25% if done correctly.
Most popular eCommerce websites help users operate in a more intuitive approach, where they can work and search without any search bars. For example, Netflix, which is one of the most popular streaming services globally, works entirely on discovery instead of searches.
This is because they expect users to know what they would like to see, show up suggestions for each content category, allowing them to decide what they want to watch. The streaming platform also has a designated “discovery” section, allowing users to discover the best choices.
Filtering and faceting
Filters are one of the most common user facilitative elements in search bars. For example, users can narrow down possible results on search engines by using particular filters on their search engine. For example, people searching for a “Bluetooth connector” can add it as a filter, and find relevant products only.
This is where the facets can come in incredibly handy, as they ensure that people see relevant products only. It is a simple yet effective method for better eCommerce product search algorithm results.
Unified search and Discovery experience
Searching and browsing are both important elements of eCommerce browsing, which is why business owners should provide both options to their consumers.
To make things clearer, let us take a look at both of them with simple examples. A consumer searching for a pair of jeans of a particular brand, color and size often finds their ideal product from search results.
Browsing searches, on the other hand, have vaguer search intent. Results like a “business suit”, “formal shoes”, “men’s sunglasses”, etc all qualify in the browsing results. Thus, businesses can merge the two search intents, and allow users to search for specific products, or make random browsing searches too.
While the searches will help users land on specific products, the browsing options will help them choose more items they may not have initially needed.
Improve eCommerce product search algorithm with Expertrec
Understanding the eCommerce product search algorithm is a key step to attracting more consumers, earning more conversions, and improving the user search experience on-site. Incorporating eCommerce search, browsing, and a smart merchandising strategy can help unlock the best results for customers.
We also suggest you check out our professional services. Our Ecommerce Search UX expertise include
- Compatibility for all platforms
- Facets and Filters
- Fast search results
- Spell checker
- Supports 30+ languages