Faceted Search For Ecommerce: Best Practices
Customer experience is the key to success in the eCommerce business, and a faceted search can help you with that. Good customer experience now is even more crucial, as a global pandemic shifted customers’ behavior to online shopping. Moreover, for the same reason, competition is more fierce than ever. In fact, a study made by Forrester revealed that 4 out of 10 users would not return to the same online store if they had a bad customer experience. Also, they said that they would even agree to pay for a better experience.
No doubt, your users want a better shopping experience. And there are many ways to increase customer experience levels – from offering qualified support to better overall site performance. But in this article, we focus on making site search to serve your customers. To be more specific here, we cover the faceted search feature. Keep on reading to discover what it is, how it differs from simple filters, and why it’s worth to use it. Besides, in the end, we covered some best practices of faceted search and some inspirational examples for eCommerce.
Table Of Contents:
- What Is Faceted Search?
- Faceted Search Vs. Filtering
- Benefits Of Faceted Search
- 8 Best Practices Of Faceted Search For Ecommerce
What Is Faceted Search?
Imagine that you sell home improvement items. A user comes to your site looking for a new black chair for the kitchen. He puts “chair” into a search box and starts the discovery. The problem is that you may have hundreds or thousands of different chairs. However, in this case, you don’t have any specific navigation options, just some simple filters.
What happens? The user is displayed with lots of messed and most probably irrelevant results, such as blue chairs, armchairs, etc. This is the opposite of a good customer experience. The way to fix it – faceted search.
Faceted search (or guided navigation) is a filtering feature that allows users to refine search results by choosing from a wide variety of filters from product attributes. It is basically a bedrock of contextual filtering experience. By providing facets, you help your users find exactly what they are looking for faster and more efficiently.
Facets consist of filters made of attributes, which are usually pre-defined, based on each business specifics, and arranged into groups. It uses product data to identify these attributes and create relevant filters, which users can select when adjusting their results. The filters themselves can be applied just to some part of the search results.
Of course, facets can be used by all of your online store users, but it’s much more important for the ones who use search, as facets remove the need for blind browsing. Nobody likes doing that, as well as performing tons of searches, trying to refine their queries. Your job here is to remove frustration – provide users with relevant and specific options when they need it. Baymard’s research found out that only 10% of eCommerce websites address this, so by doing this, you’ll gain a great competitive advantage as well.
By implementing faceted search, you help your users find (and eventually buy) what they came for without asking them to go deep into your catalog structure, product descriptions, etc. It’s like putting the product right in their hands!
Faceted Search Vs. Filtering
You may ask by now – how the heck it differs from simple filters? Well, that’s a pretty frequent misunderstanding. Both terms have one thing in common: they help users to narrow down the results displayed. However, facets are much more complex and powerful.
Filters usually consist only of site-wide options, which can be really valuable for users, such as color, brand, price, etc. Also, it is usually accompanied by categories – a universal sorting option for products. The problem is that they are too generic, and they are not product-specific. And that’s not enough for a remarkable user experience.
Faceted search includes multiple filters simultaneously – a separate one for each different attribute of the product. It touches various aspects of the product and provides the architecture for users to better understand how the catalog is constructed. Moreover, a smart eCommerce search engine can make the job even easier for users. It can automatically adjust the most relevant facets based on the users’ query to match its’ intent.
If you have a large product catalog, simple filters won’t do the work. Even if your users know exactly what they want, they don’t know how your products are named and described or under which category the product is put on. They won’t use the language you use to describe their desire in a search box. Without facets, you are dooming them for endless scrolling and frustration, leading to lost sales. On the other hand, faceted search takes time and effort to be implemented and maintained. Thus if you have a small product catalog, traditional filters & categories options are more than enough for your users not to get lost.
Benefits Of Faceted Search
We already mentioned – if you have a narrow product catalog, facets may not be worth implementing, and you probably won’t see ROI in it. But if you have a wide range of products, especially complex ones, when you should really consider enriching your site search with facets. And the main reason for this is Better Shopping Experience.
With facets, users are empowered to refine their search, as they like swiftly and effortlessly. This way, they don’t need to spend too much time browsing through different categories or results pages, or worse – desperately refining search after search… Even more, modern site search solutions, enriched with machine learning, should automatically guess and display dynamic facets to match users’ intent as well as possible and create an experience that users can’t forget. Thus users have a pleasant shopping experience, meaning that they are more likely to convert than they would be if needed to do the work themselves.
For instance, at our client’s KESKO Senukai Digital online store, smart faceted search helps users shop for a tent, even if they are not sure how to do it.
Keep in mind that you won’t seal the deal if your customers can’t find what they want, even if they came with clear intent in the first place. Facets also work as an investment in the future, as users tend to go back to the stores if they had a pleasant shopping experience. Hence, facets can help you to decrease the abandonment rate, increase user retention, conversions, and as a result, earn you more money.
8 Best Practices Of Faceted Search For Ecommerce
We’ve already covered what faceted search is, how it differs from basic filters, and how it can help eCommerce stores with complex product catalogs increase their profits. But simply having facets is not enough to make the magic. It’s all about how you design it and how you use it. Below, we listed 8 best practices to help your online store earn more.
1. Prepare Your Data Well
Data is always first and foremost when it comes to eCommerce search. When creating facets, you should first work with your product data. Collect as much data about the products as possible. Remember that you will need to clean and optimize it to generate the most suitable facets. The attributes you use to create filters should be relevant and understandable. You wouldn’t want to end up with messy results.
Another important thing to do is to log the data correctly. To understand where the data should be logged, you have to decide how the filters will be displayed (the UI side of your faceted search). It’s not enough to have general product descriptions. You should log every attribute into a corresponding field to simplify conditions and scripts to create such things as size charts, brands, names, etc. The key message here is to understand that facets depend primarily on the data.
2. Relevance Is The Key For Faceted Search
Facets should be product-specific. Their goal is to help users – not to confuse them. You won’t probably help your users if you’ll add a pants size filter to those Adidas sneakers your user was dreaming about for the past month. The golden rule – step into your customers’ shoes. In the example below, we demonstrate how product-specific facets look like on SearchNodes’ client Decathlon store:
Try to think about your users and what might be useful for them when searching for that product. Your site search analytics is a good starting point. By looking at the data, you can get an idea of what your users are looking for and how they interact with specific products. Relevance really is the key, so think about all of the appropriate options. Just don’t overwhelm with too many options – you don’t want to end up shifting their focus from buying the product.
3. Use Context and Automation
Contextual filtering uses dynamic facets and filters to match users’ intent automatically. Your site search should analyze the context of each query and select only relevant filters and facets.
To illustrate, here is an example from SearchNode client Euronics. User searches for a “laptop”. You can see that all of the filters are contextual to the “laptop” query. Then, the user searches the “washing machine”. Filters are now clearly different and are specific to washing machines.
Even more, intelligent site search solutions should use machine learning for that. Advanced automation algorithms can learn from historical data and evolve over time to make even better suggestions in the future. With context, and even better – automation, you not only increase the probability of sale but remove the guesswork and manual job for your search and analytics teams.
4. Show The Numbers Near Facets
Facets are all about assisting users, so you most probably don’t want to confuse them. Showing how much product every filter has, both selected, and unselected, helps the user to get a broader picture of what they can expect from the product catalog.
Here is a great example from Hubo, where we built faceted search with numbers:
This is a fine way to let users know how well their search went, and if it meets the expectations, or if they need to go further by narrowing down the results. This provides a pleasant shopping experience for users, as they don’t need to go back, resulting in higher conversions.
5. Avoid Facets With No Results
Another way to beat your users’ motivations to buy is to display them empty filters. They did the job – selected the attribute they want to be applied, and for what – only to see zero results. Your job is to make sure it never happens. The best way to do this is with nice UI practice: make these kinds of filters almost invisible.
Here is an example from Pigu Group, our client selling general merchandise. When the user looks for women’s’ bicycle, empty facets with brand gets almost invisible, letting the user know, that the shop doesn’t have a certain brand.
This way, the same as with showing the numbers in filters, users will know what to expect and be delighted that their time is not wasted.
6. Have Multiple Selection Faceted Search
One filter may not be enough to refine the results. Remember, facets explore many different dimensions of a single product. Thus the user may want to use more than one. It’s especially important when users use generic queries, such as “Sneakers”. If your product catalog is big (and it’s probably the case if you consider using facets), such a query could return thousands of results. They might want to play around with different attributes altogether, such as brand, color, etc. Maybe they prefer both Nike and Adidas sneakers – who knows?
To illustrate, in our client Castorama online store, clients can select multiple facets simultaneously. In this specific case below, the user can view a few different color pillows that Castorama has on their website, which can be transported by the company, and are within a certain price range.
By giving them multiple selection options, you honor your users’ time by saving them from extra searches, and it returns back to you in a monetary value.
7. Make Sure SERP Doesn’t Reload
Multiple selections are great until the results page reloads, and suddenly your user is brought back to the top. Usually, users sort out the results using more than one filter. Thus it gets very frustrating when selecting one filter, the whole page reloads. Oh, and if results update slowly, it gets even more frustrating. The result – the user may leave the page instantly and go straight to the competitor. Hence, make sure to have a nice and easy-going refresh of the results without unpleasant reloading.
8. Consider Using Image Facets
Sometimes it can be tough to describe what you are looking for in words. Maybe your user saw a very nice round lamp in their friend’s apartment, but they don’t know what word filters to use to discover it. Image recognition driven by AI can help users select appropriate visual filters, then words simply can’t help. Using visual filters is quite a new thing in eCommerce, and it might not be for everyone, but it’s definitely worth considering when building facets.
Here is the example from Vestig.io, which provides visual filters, that can help users to choose:
Facets are a great way to improve your site’s overall shopping experience for users and eventually increase your profits. However, they may not be for everyone, and it also requires loads of resources and time to be developed correctly. Not to mention that you constantly need to monitor and analyze it to make improvements. Of course, intelligent site search solutions can lift most of the weight by doing all of this for you. So, to sum up, make calculations on potential ROI to decide if facets are the way to go for you.
We would love to hear about faceted search practices at your company. Please, share them in the comments section below!