This post was written in collaboration with Afsana Moriom, Customer Success Manager, EMEA at Constructor.
Site visitors are often on a mission to find specific products, and search is the fastest way to bridge the gap between their desire and reality. But broad search queries like “women’s sweaters” can return hundreds of results, many of which may not be attractive.
Faceted search is a shortcut for buyers, allowing them to filter through result pages and refine their search to find exactly the right item. It’s also a shortcut for businesses to drive more conversions and create better shopping experiences that inspire higher customer lifetime value (CLV).
Here we cover the foundations of ecommerce faceted search, including challenges merchandisers face with facets, best practices to overcome them, and real-life examples of ecommerce facets done well.
Table of Contents
- Faceted Search vs. Faceted Navigation
- Challenges Merchandisers Experience with Facets
- 5 Best Practices for Ecommerce Faceted Search
- 3 Faceted Search Examples to Copy for Your Site
Faceted Search vs. Faceted Navigation
The difference between faceted search and faceted navigation boils down to where they appear on your ecommerce site. Faceted search applies to filterable results on search results pages, while faceted navigation applies to the filterable items on category pages.
For instance, searching “women’s summer dresses” on Target Australia automatically returns dresses that satisfy the “women’s” and “dresses” categories. Additional facets groups and options appear so you can further refine search results.
Sometimes sites may pre-build facet groups and options into their search results. Birkenstock does this well by pre-selecting the black option for the search “black shoes.” (Although small, these optimizations can have a mighty impact on customer experience.)
Challenges Merchandisers Experience with Facets
Managing ecommerce faceted search and navigation without a strategic approach can be difficult, especially for merchandisers who handle thousands of SKUs. Here are some of the most common challenges merchants face:
- Balancing facet variety with a user-friendly interface. Merchandisers need to ensure pertinent facets are easily accessible while trying not to overwhelm or confuse the customer with an excessive number of facets.
- Ensuring accurate product categorization and tagging. A diverse product range, constantly changing inventory, and varying product terminology (think: “hoodie” vs “hooded sweatshirt”) can provoke inconsistencies in data quality and product listings.
- Adapting filtering strategies to changing circumstances. There’s a continuous need for ecommerce businesses to adjust their product filtering and recommendation systems to dynamic consumer behaviors, new arrivals, and seasonal influences.
- Ensuring facet data provided by suppliers is accurate. Suppliers often provide incomplete or incorrect product information, which can hinder data standardization and integration into unified product catalogs or databases. (Address this quicker by enriching product data with AI.)
Sound like a lot? That’s because it is. And that’s always why merchandisers worldwide are seeking ways to overcome these issues and propel buyer experience and KPIs alike. The following best practices for ecommerce faceted search will help.
5 Best Practices for Ecommerce Faceted Search
Here’s what to keep in mind as you build out your product search strategy.
1. Know when to expand, collapse, hide, or protect facets
For large ecommerce sites and complex product categories, it’s easy for facets to become unwieldy. Merchandisers can be selective of which facets to show when and where to make them less so.
When deciding whether to expand or collapse facets, best practice is to collapse most facets and expand or highlight only the most relevant ones for the search query or category page. This allows customers to easily see all their options and choose the ones they’d like to expand for more details. (Your mobile experience should also default to collapsed to optimize for small screen space.)
Let’s look at the query “spf foundation” on beauty retailer Sephora website. At the very top, there are only a few facet groups highlighted that are most likely to be attractive to customers (“vegan” ingredients, “mini size,” etc.).
Underneath this small list, Sephora’s search platform automatically collapses the rest of the facets, except for “pickup & delivery.” This is so customers can filter by fulfillment option, which could be important when sampling foundation in-store before purchasing.
Merchandisers also have the option to hide facets that they don’t want returned as a value. This setting is helpful when you want to be able to searchandise against an attribute, but you don’t want to surface that as a facet option/filter. Hiding facets also provides a clear and more streamlined customer experience.
For example, the Maxeda DIY Group have set their stock levels and stock group attributes as hidden facets. They still searchandise against these — as in, boosting and burying based on stock level. They’re just not returned as a response within the customer-facing facets.
Merchandisers can also employ protected facets, which function similarly to hidden facets. Unlike hidden facets, protected facets not only remain concealed from customer-facing search or category pages, but also go a step further by concealing the associated data in the API response. Consequently, this information can’t be accessed through API calls either.
To illustrate, consider the example below from Backcountry’s merchant dashboard. They choose the protected facet option for groups such as margin, velocity rate, and weeks of coverage.
2. Select the right facets for your query
Providing the right facet for your query can improve your user’s experience and boost your conversions by connecting customers to the right products faster. The facets you show are broadly divided into a few categories:
Facets that are common to most products include size, brand, price range, product category, and subcategory. Depending on the type of products you sell, you may provide some additional facets as standards. For instance, when searching for vitamins in a pet supplies store, it may be useful to provide a facet for type of pet.
In many industries, themes can help customers find the right products. For the query “dog card” on greeting card site American Greetings, the website displays facets for both “occasion” and “recipient” to facilitate the product discovery experience.
This type of ecommerce faceted search has a number of applications for apparel retailers as well. Customers looking for a dress could shop by style (like maxi dress or cocktail dress) or event (like a wedding or a date night).
In the absence of an in-store associate, thematic filters coordinate with shopping intent and with how humans think about shopping: “I need a Christmas gift for my 10-year-old daughter” or “I need an outfit for a wedding next month.” At the end of the day, using a product discovery platform that can handle natural language queries helps build customer loyalty and trust because shoppers receive a better, more targeted experience.
Numerous studies have shown that ratings and reviews have a significant impact on customers’ shopping decisions, which solidifies the strategy of including reviews as facets.
In the example below, this website allows customers to filter by star ratings, eliminating products that have bad reviews:
Dynamic, contextual facets
While the categories of search facets are generally broad, sometimes product searches warrant the need for specific attributes. In these cases, it’s important that facets match the context of the search.
For example, a search for “women’s pants” would typically have the common facets like size, color, and style. But it might also have other more pant-specific facets, such as inseam length, rise, leg silhouette, or number of pockets. Those facets wouldn’t fit another query for “women’s hats.”
Apparel brand Bonobos appropriately provides neck type (crew neck or v-neck) and shirt pockets as facets for the query “tee:”
This type of faceting helps shoppers get more granular during their product search, reducing time to purchase and improving conversion rate.
3. Decide the order in which to display facets
While facet order can be set globally in your product discovery software, there may be times when you want to slot facets in a different order to further support a contextually relevant experience. For this, you have two options available:
- Manually slot facets for specific searches given what you know about the context.
- Leverage AI-assisted merchandising tools to automatically order your facets in a way that optimizes search results for context, product attractiveness, and conversions (more on this later!). For example, for a category like accessories on an apparel site, a standard facet like “size” might slot below more relevant facet groups like color, brand, or price. “Size” will still be present for that category within the facet listings, but it won’t take up valuable space for other more contextually relevant options.
Maxeda DIY Group is a great example of a company that employs a hands-on, data-driven approach for displaying facets. To determine the most effective facet order, their team leverages Facet Usage Statistics, which are readily accessible through the merchant dashboard of their ecommerce platform.
These statistics provide valuable insights into the facets’ recent performance, drawing data from the past seven days.
Having data as their foundation ensures that facet orders are not arbitrary, but based on recent user interactions and preferences. And because Maxeda regularly monitors facet orders on a weekly basis, they’re able to adapt quickly to changing user behaviors and preferences.
Here are other benefits to the Maxeda facet display strategy:
- Enhanced user experience. By arranging facets based on usage statistics, customers find products they are looking for quicker, ultimately increasing user satisfaction.
- Operational efficiency. Facet sorting and organization are guided by real-time data, enabling the team to maintain a relevant, user-friendly interface without unnecessary delays.
- Increased flexibility. By focusing on recent data, Maxeda shows flexibility in responding to trends and seasonal shifts in customer behavior. This adaptability is key in the ever-evolving ecommerce space.
- Continual improvement. All of this work in refining facet orders implies an ongoing effort to improve the online shopping experience. This process is not static but evolves alongside user preferences and behavior.
The Ultimate Guide to Searchandising with Constructor
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4. Make facets easy to select and filters easy to use
Finally, consider your buyer’s shopping experience when they’re in the process of narrowing down search results. Even the slightest frustrations with filtering through attributes could make them bounce.
There are a number of ways customers could potentially get confused during their search experience. Keep the following tips in mind when planning your ecommerce’s faceted search interface:
Prominently display selected facets
If customers don’t remember which facet options they’ve chosen, it can frustrate them to see only a few products and then need to go through the entire facet list and unselect everything — or bounce. Solve this headache by prominently displaying selected facets at the top of the search results page.
On the Rugs Direct website, “pillow” is automatically selected and displayed at the top (as that was the search query). And since the shopper further refined results to see only vintage/overdyed pillows, that facet option is also clearly displayed at the top. This allows shoppers to understand filtered results and easily unfilter if necessary.
Are there facets for which it makes sense to select multiple attributes, or are they all mutually exclusive?
Most of the time it makes sense to have checkbox filters so that shoppers can select more than one attribute (e.g., red and yellow). But sometimes you may want to have radio buttons instead to show users that only one attribute can be selected at a time, such as a pick-up location or fulfillment method.
Make filtering responsive and interactive
Make filtering interactive, meaning that results filter automatically as soon as a selection is clicked. Customers will stop applying filters when they begin to see attractive products, and this reduces the chance that they’ll receive unattractive results (or no results) from applying too many unnecessary filters.
See how it works here on Target Australia’s website:
If this isn’t an option with your current ecommerce platform, make sure that the “Apply” button is very clearly displayed so that customers know they’ll have to manually apply the filters they select.
5. Select the right ecommerce faceted search software
While implementing these best practices is crucial, manual execution can prove challenging. An effective product discovery software powered by AI offers an automated solution for arranging facets, prioritizing product rankings, and optimizing for business KPIs.
The ideal software collaborates seamlessly with your ecommerce team, complementing their expertise in various contexts. Once any manual slotting or hiding preferences have been applied, an advanced search solution equipped with searchandising capabilities can further enhance the user experience by featuring or reordering facets based on several factors:
- Relevance to product results. It considers whether the facets align with the products in the search results, ensuring that the facets presented are contextually appropriate.
- Product appeal. The software evaluates the attractiveness of the products associated with specific facet values, influencing their positioning to showcase the most appealing options.
- Attribute frequency. It takes into account the frequency of a particular attribute across the entire result set, guiding the presentation of facets to align with user preferences. For instance, a product with a unique attribute may rank high in search results due to its appeal, but its associated facet value might not receive the same prominence due to its rarity.
By integrating traditional merchandising features like boosting, burying, slotting, and hiding facets with this advanced automation, you consistently drive outsized results and gains across the board in revenue, margin, and conversion rates, demonstrating the substantial impact of such a comprehensive approach.
3 Ecommerce Faceted Search Examples to Copy for Your Site
Ecommerce faceted search software like Constructor definitely makes creating a great search experience easier. See how these websites are tapping into sophisticated facets and filters to help their customers find products they love:
Outdoor retailer Backcountry knows a thing or two about ecommerce faceted search. Thousands of people visit their website every day looking for very specific outdoor gear — everything from workout supplements to snowboards. With an extensive catalog across a wide variety of outdoor activities, it’s critical for Backcountry to leverage search effectively.
What we love: Backcountry has some of the most detailed contextual facets we’ve seen. For a search for snowboard clothing, customers can filter by everything from seaming and weight to insulation and shell construction. This helps build confidence that the folks at Backcountry know their outdoor gear inside and out and are dedicated to helping customers find just the right item.
Serena & Lily
Modern furniture company Serena & Lily offers proof that ecommerce faceted search doesn’t have to mean a clunky or complicated user experience. Their clean filtering for search results opts for collapsed filters by default so that customers can open and select what they’d like.
What we love: Serena & Lily understands how people shop for furniture: by looking for coordinating pieces and collections. The “Collection” facet above allows shoppers to refine results by collection, seeing all matching pieces in one place. This increases average order value (AOV) by providing upsell opportunities and builds customer trust in the brand.
Shoe manufacturer Birkenstock understands the possible uncertainty that comes with buying the right pair of footwear online. In a situation where a single query for “women’s shoes” could return hundreds of products, their ecommerce’s faceted search (powered by AI for personalization) provides shoppers with a better experience by allowing them to narrow down results quickly.
What we love: As we mentioned before, Birkenstock is one of those ecommerce sites that pre-builds facets and filter selections into search results, making it easier for customers to find the right products for their needs. Analyzing what each customer clicks on after refining their search, Birkenstock’s product discovery platform uses those insights to make more attractive suggestions in the rest of the site experience and optimize for conversions. For example, clicking on products with the “washable” attribute might make more waterproof and easily washable products show up higher on other pages.
The Next Step in Ecommerce Faceted Search
Ecommerce faceted search is a powerful tool to help merchandising teams improve the customer experience and drive revenue, but it doesn’t work alone.
Some optimizations mentioned — like dynamic filtering or flexible filter ordering — work best when they’re powered by an AI-native product discovery solution that leverages advanced algorithms, transformers (the “t” in ChatGPT), and large language models (LLMs). These technologies can help surface insights and automate manual processes, which frees up time for merchandisers to strategize how to further improve the customer experience and drive KPIs.
Interested in learning how merchandising tools can help your team do more with less? Check out The Constructor Guide to AI-Assisted Merchant Tools.
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