Search facets, also known as faceted navigation or faceted search, are a powerful feature used in many websites and search engines to help users refine their search results.
Facets provide a structured way of categorizing and filtering search results based on different attributes or characteristics of the data.
They allow users to narrow down their search by selecting specific values within these attributes, making it easier to find relevant information.
What are facets ?
Search facets are front-end components that allow the users to filter the items they want to see based on their respective metadata or taxonomies.
Each facet represents a specific attribute of the data, such as product categories, price ranges, dates, or any other relevant characteristic. They can be displayed to the users in multiple forms, each one reacting to interactions in different ways. For example, in an e-commerce website, facets may include categories like “Electronics,” “Clothing,” or “Home & Garden,” allowing users to filter products by their desired category. Clicking on a facet value narrows down the search results to only include items within that selected category.
Some common facets are :
- check boxes : check all the data you want to use as a filter. Select as many as you want.
- radio boxes : check the data you want to use as a filter. You can only select one per type.
- select box : select the data you want to use as a filter from a drop-down list.
- date picker : select the date range in a calendar.
- range slider : filter out all the items that contain a numeric property that is outside of the set range using a slider.
- range checkboxes : display checkboxes that allow the user to specify a numeric range. Each check box range is defined by an interval value that has set beforehand.
- star rating : exclusive to e-commerce websites, this facet will display to the users the items that have a score greater than the value selected in the facet.
When a user performs a search, the search engine retrieves relevant documents and analyzes the associated metadata to generate facets.
Why add facets to your search ?
Facets are most commonly used for e-commerce websites for many reasons.
They allow for greater customization from a customer perspective. Your customer can refine or tune their easily with the click of a button. For example, if they are searching for a phone and know which specific brands they want to see, they can check ‘Google’, ‘Samsung’ and ‘Apple’.
Facets also offer a way to filter products based on numerical values. Since search is text based, it can’t filter items based on ranges. For that you need date pickers, sliders or star ratings. For example, the user could want to filter products outside of their price range so they filter out items over $50 using the range slider facet.
But even outside of e-commerce, facets can bevery useful for navigation. If your blog covers a wide range of topics, having all your different topics names displayed in the side bar in form of facets can help your users discover more content that could fit their needs.
All in all, facets can greatly improve user experience by giving your users more freedom to modify their search experience, making them more likely to return in the future.
Which search engines offer faceted search capabilities
To add facets to your website, you could make use of the following search engines :
Apache Solr
Apache Solr is a staple search engine. When it comes to keyword search, it can do almost everything and offers many customization options.
This reliable solution will power both your search and facets.
Elasticsearch
Elasticsearch is probably the most widely used publicly accessible search engine today.
This popular solution will power both your search and facets.
Opensearch
Opensearch is the recent AWS fork of Elasticsearch. It offers almost all the same capabilities and uses a far more lax license than it’s progenitor, Elasticsearch.
Algolia
Algolia is a fully managed search solution that delivers everything from search (keyword search, AI search, facets) to personalized recommendations.
Vespa
Vespa also offers facets. They are called groupings.
Add faceted search to WordPress
WordPress is the world’s most popular CMS, powering more than 40% of the web. So it’s not surprising that a few solutions exist for WordPress facets :
FacetWP
FacetWP is an extremely popular wordpress facets plugin. It delivers many facet types out of the box.
It is very customizable using your own PHP code.
However, since it relies on SQL to send queries, it can have some performance issues as the amount of data increases :
- Increased Query Time: The time taken to generate search facets can increase as the data size grows, especially if the facets require complex calculations or analysis.
- SQL Joins: In relational databases, search facets may require joining multiple tables, which can become slower as the number of joins increases.
- Disk Issues: If the metadata used for facets is stored separately from the main data, disk I/O operations can become a bottleneck as the data size grows, affecting facet generation speed.
- Resource Management (RM) Issues: Facet generation requires computing resources, such as memory and processing power. As data and facet complexity increase, resource management becomes crucial to ensure optimal performance and prevent system overloads.
That is why you could make use of search engines that are optimized for information retrieval tasks. They offer faster query execution times and far better scalability. WPSolr can integrate them into your WordPress website.
WPSolr
WPSolr is a WordPress search & recommendations plugin. It can add search, Ajax search, facets & recommendations powered by world-class search engines & AI recommenders.
Learn how to add facets in our documentation.
Conclusion
Search facets provide a valuable way to filter and refine search results based on various attributes or characteristics of the data.
They enhance the user experience by allowing users to narrow down their search results efficiently. Implementing search facets in popular platforms like WordPress, Elasticsearch, Solr, and Algolia can be achieved through plugins, configuration settings, or API calls.
However, it’s important to consider performance issues such as increased query time, SQL join complexity, disk I/O, and resource management as the data size and facet complexity grow.
By carefully optimizing and monitoring these aspects, search facet functionality can be maintained effectively even with large datasets.
