Understanding Facets, Filters, and Sorting for Search and Listing Pages

Facets vs Filters vs Sorting…

When a client recently asked me, "How many facets do we need for our listing page?" it revealed to me a common confusion many have about the mechanics of search functionality, particularly facets, filters, and sorting. While these elements may seem similar, each serves a distinct purpose and can significantly impact a website’s usability, search performance, and overall user experience.

Truth be told, I didn’t have a definitive answer to their question regarding “number” of facets, but I was able to get the following from Coveo:

Each query may have a different “ideal” number of facets, but a good general rule is to not have more facets than the results listed.

This was too vague to be of any real value in giving a definitive answer to my client’s original question - we need to dig deeper. Join me as we seek to find out more, starting with understanding what each of these crucial search functions are:

Defining Facets, Filters, and Sorting

Facets

Facets are dynamic categories or attributes that allow users to refine search results based on multiple criteria. On e-commerce websites, facets often include product-specific attributes like size, colour, price range, brand, or material. On content-heavy websites (such as the site you are currently on), facets can cover tags, topics, authors, publication dates, or even geographical regions. The key to facets is that they enable multi-dimensional filtering, meaning users can combine criteria (looking at an e-commerce site, the combined facets might be something like ‘female shoes’; ‘size 11’; and ‘red’) to narrow down their search.

Filters

Filters, on the other hand, are static, predefined conditions that refine search results. They act as hard boundaries for excluding irrelevant results. As an example, a filter might exclude out-of-stock products or limit content to a specific date range. While filters can overlap conceptually with facets, filters are typically less flexible, offering fewer combinations and often being applied by default without user input.

Sorting

Sorting determines the order in which search results are displayed. Common sorting options include alphabetical order, chronological order, relevance, or price (low to high or high to low). Unlike facets and filters, which focus on narrowing the results, sorting focuses on organizing them, and does not limit or refine the results in any way.

Key Differences from a Content Author’s Perspective

Flexibility and Interactivity:

• Facets: Provide a highly interactive experience. Users can experiment with different combinations of criteria to pinpoint the most relevant results.
• Filters: Are more rigid. They’re either on or off and often act as baseline exclusions.
• Sorting: Offers users control over the order but doesn’t modify the content shown.

Use Cases for Content Type:

• On a commerce site, facets are relatively straightforward. Attributes like size, brand, and colour are concrete and easily defined.
• For content-rich sites (like a blog or industry knowledge base - much like the site you are currently on!), facets need more careful planning. Topics, themes, and audience categories can overlap or be subjective, requiring a clear taxonomy and metadata.

Impact on User Journey:

• Facets empower users to self-direct their search journey. This is ideal for users with specific needs or preferences.
• Filters often serve to eliminate irrelevant or overwhelming options for users.
• Sorting allows users to prioritize results based on what’s most important to them, such as relevance or recency.

How Facets, Filters, and Sorting Improve Website Performance

Improving ‘Findability’:

• A well-implemented facet system helps users locate relevant content or products faster, reducing frustration and bounce rates. For example, a knowledge base might allow users to filter articles by industry, date, and author to locate specific information efficiently.
• Filters ensure irrelevant items are excluded, keeping results concise and meaningful.

Improving User Experience (UX):

• Users appreciate intuitive navigation. When they can tailor search results using facets and filters, the website feels responsive to their needs.
• Sorting options make large result sets easier to navigate by prioritizing the most relevant or desirable items.

Boosting Conversion Rates:

• For e-commerce, facets allow customers to pinpoint exact matches, making them more likely to complete a purchase.
• In content-heavy sites, users finding relevant articles quickly increases engagement and time-on-site metrics.

Best Practices for Content Authors

• Understand Your Audience: Analyze user behaviour to determine what facets or filters they’re likely to use. For instance, if most users search for articles by publication date, make "Date" a prominent facet.
• Limit Facet Overload: More facets aren’t always better. Too many options can overwhelm users. Instead, focus on high-value facets that align with user needs. For example, a shoe retailer might prioritize size, colour, and brand while excluding less impactful facets like “material."
• Implement a Clear Taxonomy: On content-heavy sites, clear metadata is essential for facets to function well. For example, if articles can belong to multiple categories, ensure they’re tagged consistently.
• Combine Facets and Filters Thoughtfully: Use filters for universal exclusions (e.g., out-of-stock products) and facets for user-specific refinement. On content-heavy sites, filters can be used to exclude outdated or less relevant content, ensuring users see only high-quality and timely results.
• Test Sorting Logic: Ensure sorting options align with user intent. For example, relevance should be the default for search results, while chronological order might work better for news articles.

Addressing Challenges with Content-Heavy Sites

Facets for Abstract Content

When content spans diverse topics, defining meaningful facets can be tricky. Start by grouping content into broad categories, then refine with subcategories. For example, a technology blog might use facets like "AI," "Cloud Computing," and "Tech Reviews."

Facets should ideally reduce the total result set by 70-90%. This range ensures the results remain highly relevant without being too narrow to exclude valuable content. If results frequently fall below this range, revisit the taxonomy and tagging to ensure broader applicability.

Balancing Performance with Complexity

Use analytics to monitor how often each facet or filter is used. If a facet isn’t contributing significantly, consider removing or merging it with others.

Maintaining Consistency Across Teams

Content authors must align with developers and designers to ensure facets, filters, and sorting options are implemented correctly. Regular training and documentation help maintain this alignment.

Review the facets and filter strategy and subsequent implementation regularly, assessing user behaviours and their associated queries, and adapting your taxonomy to suit.

Final Thoughts

Facets, filters, and sorting are powerful tools for enhancing a website’s search functionality and user experience. By understanding their differences and implementing them strategically, content authors can create intuitive, efficient search experiences that delight users and drive engagement.

As for answering my client’s original question regarding the number of facets I felt their site needs, the principle of prioritizing quality over quantity continues to apply. The total number of facets on the site matters far less than how those facets allow the visitor to refine the content to provide meaningful results and a better overall experience.

The next time a client asks, "How many facets do we need for our listing page?” You may still not have a definitive answer, but hopefully, armed with this additional knowledge, you’ll have the information you need to guide them in optimizing their search, filter and facet capabilities.

For more information on understanding and optimizing facets and filters on your site, please check out these resources:

Coveo: https://www.coveo.com/blog/faceted-search/

Algolia: https://www.algolia.com/blog/ux/faceted-search-an-overview