Faceted search is not just a feature; it’s a game-changer for ecommerce websites. It transforms the way users interact with your site, enhancing user experience and driving conversions.

If you are still considering whether or not to invest in providing faceted search functionality on your website, this article is for you.

Let’s discuss the benefits of implementing faceted search on your ecommerce site.

What is faceted search?

Faceted search (also called faceted browsing or faceted navigation) is a navigation feature used in many ecommerce websites.

Faceted search allows users to filter large sets of product inventory. It narrows down abstract search queries and brings back user-relevant product offerings.

This helps them to find the most relevant products filtered by size, color, pattern, brand, price, and other criteria.

In essence, it combines traditional search methods with a dynamic navigation system, allowing users to refine their search based on specific attributes like color, size, brand, and price range.

Amazon.com example of faceted search

How does it work?

Faceted search is a game changer for stores with a large and complex inventory. It eliminates the need for your website visitors to scroll down endless product listings and guess if the product they need is available.

Integrating a faceted search in your online store puts you in a better position. It allows your website to offer a specific product for a person looking for it fast, so he does not purchase from your competitors.

Here is an example:

A user is looking for running shoes. Usually, when a user writes running shoes in the search bar, the site returns hundreds of results matching the search: all sizes, colors, and brands included. Most of these products are not the ones that brought a person to your website.

For that, the faceted search comes in handy.

It allows a user to apply the specific criteria (facets) relevant to his search. For instance, he might want Nike running shoes of size 11. Then, a user can narrow the search further by applying such filters as color or material.

With only a few choices of the most relevant running shoes, the user is now very likely to make a purchase.

That said, this powerful feature is more than just a convenience; it’s a catalyst for customer satisfaction and engagement:

1. Enhanced engagement through satisfaction and trust:

Faceted search on e-commerce sites can boost customer engagement by increasing satisfaction and trust.

By providing customers with an efficient and tailored browsing experience, e-commerce sites can significantly enhance the user experience, leading to higher satisfaction levels [1].

2. Influence on customer loyalty:

Faceted search can influence engagement behaviors, which in turn affect the perceived benefits like social, entertainment, and economic benefits on e-commerce sites.

This enhanced perception can increase customer loyalty and satisfaction, critical metrics for e-commerce success [2].

3. Positive attitudes and loyalty:

For e-commerce, engaged customers who have a positive interaction with faceted search interfaces are likely to develop positive attitudes towards the brand.

This can lead to increased future loyalty and a better perception of product value, drastically boosting customer retention [3].

4. User satisfaction with preference-based interfaces:

Preference-based search interfaces directly relate to e-commerce success. Implementing faceted search that caters to customer preferences in product selection can significantly improve user satisfaction, potentially leading to better conversion rates and customer loyalty [4].

Benefits of implementing faceted search

Faceted search is widely used in the top ecommerce stores. Why should you implement this functionality on your website?

1. Refined search results to enhance the shopping experience:

At least every fourth website visitor goes immediately to search - it is the quickest way to find the needed product. (If the search works well, of course.)

A fast, accurate, and intuitive-to-use search radically improves the user experience. Website visitors who find it easy to navigate the website are more likely to find and buy the product they came for.

The automated algorithm optimizes facet ranking based on user preferences, streamlining the product discovery process and enhancing user satisfaction [5].

A seamless user experience also builds trust with the retailer, strengthens loyalty, and encourages buyers to purchase again.

2. Discovery of new products and increased order value:

Website visitors who use the search are 2.4 times more likely to convert.

An effective faceted search should predict the user’s query and automatically suggest products in real time. It should display only the most accurate results (sorted by relevance) and allow modifying search results.

With faceted search, users discover more alternatives that meet their preferences than standard search. As a result, the faceted search can lead to the discovery of products users hadn’t initially considered, potentially increasing average order value [6].

3. Enhanced website performance and improved SEO:

Faceted search, by efficiently organizing and presenting information, can contribute to improved SEO and website performance [7].

Research exploring the importance of SEO in marketing demonstrates that efficient search functionality, like faceted search, can enhance a website’s SEO performance and effectiveness of online advertisement [8].

4. Data for scaling:

A data-driven search is also a valuable source of information for business growth.

A search dashboard allows you to analyze how people interact with your products and website and make data-based decisions.

By analyzing the most popular search terms and suggestions, you can change product descriptions, rank, or automatically suggest trending products.

Queries with zero results help you identify the demand and stock new products to meet users’ expectations.

5. Increased revenue:

People who use the search on the ecommerce website spend 2.6x more compared with website visitors who do not use the search.

A highly relevant search in your ecommerce website narrows choices from thousands of results to a few. This way, a user can find what he needs quicker than the spontaneous buying impulse fades away.

How to implement faceted search in your store?

When it comes to implementation, user-friendly integration should be your main priority.

The filters and options should be clear and easy to understand, with an option to easily clear selections. Navigation should be simple, making it easy for users to move between filters, and it should be easily visible on the page.

You can choose a custom integration or an already-tested and perfected ecommerce search solution like LupaSearch.

LupaSearch is an AI-driven ecommerce search that gets to the core of the users’ search queries and delivers highly-matching, personalized results. This site search engine integrates faceted search functionality to improve product discoverability and boost sales.

You do not need coding knowledge to power your site search with facets. The LupaSearch dedicated team of search professionals is here for your needs.

Contact us today, and receive a free demo.

References

1. Santini, F., Ladeira, W., Pinto, D., Herter, M., Sampaio, C., & Babin, B. (2020). Customer engagement in social media: a framework and meta-analysis. Journal of the Academy of Marketing Science, 1-18. https://doi.org/10.1007/s11747-020-00731-5.
2. Gummerus, J., Liljander, V., Weman, E., & Pihlström, M. (2012). Customer engagement in a Facebook brand community. Management Research Review, 35, 857-877. https://doi.org/10.1108/01409171211256578.
3. Bergel, M., Frank, P., & Brock, C. (2019). The role of customer engagement facets on the formation of attitude, loyalty and price perception. Journal of Services Marketing, 31, 890-903. https://doi.org/10.1108/jsm-01-2019-0024.
4. Kern, D., Hoek, W., & Hienert, D. (2018). Evaluation of a search interface for preference-based ranking: measuring user satisfaction and system performance. Proceedings of the 10th Nordic Conference on Human-Computer Interaction. https://doi.org/10.1145/3240167.3240170.
5. Vandic, D., Aanen, S., Frasincar, F., & Kaymak, U. (2017). Dynamic Facet Ordering for Faceted Product Search Engines. IEEE Transactions on Knowledge and Data Engineering, 29, 1004-1016. https://doi.org/10.1109/TKDE.2017.2652461.
6. Kern, D., Hoek, W., & Hienert, D. (2018). Evaluation of a search interface for preference-based ranking: measuring user satisfaction and system performance. Proceedings of the 10th Nordic Conference on Human-Computer Interaction. https://doi.org/10.1145/3240167.3240170.
7. Tsuei, H., Tsai, W., Pan, F., & Tzeng, G. (2018). Improving search engine optimization (SEO) by using hybrid modified MCDM models. Artificial Intelligence Review, 53, 1-16. https://doi.org/10.1007/s10462-018-9644-0.
8. Khraim, H. (2015). The Impact of Search Engine Optimization on Online Advertisement: The Case of Companies using E-Marketing in Jordan. American Journal of Business and Management, 4, 76-84. https://doi.org/10.11634/216796061706676.
9. Kharlamov, E., Giacomelli, L., Sherkhonov, E., Grau, B., Kostylev, E., & Horrocks, I. (2017). SemFacet: Making Hard Faceted Search Easier. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. https://doi.org/10.1145/3132847.3133192.
10. Dang, D., Nguyen, H., Nguyen, B., & Duong, T. (2015). A Framework of Faceted Search for Unstructured Documents Using Wiki Disambiguation. , 502-511. https://doi.org/10.1007/978-3-319-24306-1_49.
11. Baeza-Yates, R. (2006). Algorithmic Challenges in Web Search Engines. , 277-278. https://doi.org/10.1007/11764298_25.
12. Mahdi, M., Ahmad, A., Ismail, R., & Subhi, M. (2020). Review of Techniques in Faceted Search Applications. 2020 International Symposium on Networks, Computers and Communications (ISNCC), 1-5. https://doi.org/10.1109/ISNCC49221.2020.9297275.
13. Koren, J., Zhang, Y., & Liu, X. (2008). Personalized interactive faceted search. , 477-486. https://doi.org/10.1145/1367497.1367562.