Algolia, the AI Search and Retrieval platform powering more than 1.75 trillion queries each year for over 18,000 businesses worldwide, today announced the availability of Dynamic Facets, a new capability that automatically surfaces the most relevant filters based on what a shopper is actively searching for. Rather than presenting the same fixed refinement options for every query, Dynamic Facets adapts in real time to search context and user behaviour, helping shoppers find what they need faster while reducing the manual configuration work typically required by search and merchandising teams.
For online shoppers, filtering is supposed to be the shortcut. Too often, it becomes another obstacle. As product catalogues grow, shoppers are forced to navigate numerous options through filter panels that show the same fixed refinement choices regardless of intent. Someone searching for televisions may have to scroll past irrelevant attributes before finding screen size or resolution, while a skincare shopper may need to hunt for ingredients, skin type, or product concerns.
The issue is not poor design. Most filter experiences were configured once in the early stages of the web design and based on reasonable assumptions about how people would shop. But categories change, inventory shifts, trends move, and customer behaviour evolves. Over time, the filter panel starts to reflect how the business organizes its catalogue rather than how shoppers search. The result is more scrolling, fewer refinements, slower discovery, and missed opportunities to convert.
Algolia’s Dynamic Facets addresses this challenge by intelligently adapting the filtering experience to each search. Facets, the attributes shoppers use to narrow results such as size, color, brand, or format, are automatically prioritized based on what is most relevant in the context.
Egil Grønn, Search and Discovery System Lead at Elkjøp, said: “We see significant potential with Algolia’s Dynamic Facets feature to make filtering more responsive to how people actually shop. Rather than relying on a fixed order of filters, the experience can automatically prioritize the attributes that matter most in each category. For example, when someone searches for a television, screen size should not be buried at the bottom of the filter list. If shoppers consistently use that attribute, it should automatically rise to the top.”
Early usage of Dynamic Facets shows that when the most relevant filters are surfaced sooner, shoppers engage faster and more frequently. In the strongest-performing markets, clickthrough rates on specific filters improved by 10 to 15 percent, with shoppers clicking results that appeared two to three positions higher on the page. By reducing the distance between search intent and the right result, Dynamic Facets helps retailers create faster, more effective discovery experiences that move shoppers closer to purchase.
Dynamic Facets also surfaces data on which filter values are seeing the most interaction, for example which brand, size, color, or attribute users are actually clicking on. Algolia exposes this as a data layer that teams can build on. A practical example: pulling the top five filter values for a given query and surfacing them as quick-filter chips directly on the page, reducing the number of steps between a search and a refined result.
Nate Barad, Vice President, Product & Technical Marketing at Algolia noted: “Shoppers instinctively turn to filters to refine search and move quickly from intent to product. But as language, trends, and customer expectations evolve at speed, static facets can hold retailers back and place unnecessary pressure on merchandising teams. Dynamic facets, powered by behavior and AI, adapt automatically to each shopper’s context, surfacing the most relevant refinement options in real time. The result is a faster, more intuitive discovery experience for customers, and a more scalable, efficient way for merchandising teams to deliver relevance without constant manual intervention.”
Dynamic Facets is particularly valuable wherever search must work across large, varied catalogues, especially for retailers, marketplaces, media libraries, and any environment where what someone is looking for varies dramatically from one query to the next. The more diverse the catalogue and the more varied the queries, the more likely a static filter list gets in the way.
Algolia’s observations on digital commerce points to a future where AI and automation sophistication has become increasingly central to the shopping experience. Algolia’s Dynamic Facets aligns with this by using shopper behavior and search context to automatically surface the most relevant filters and values, helping retailers reduce friction for customers while lowering the manual burden on merchandising teams.
Heather Hershey, IDC’s Senior Research Director for Digital Commerce & Agentic Commerce Strategies, added: “Dynamic Facets is compelling because it’s incorporated within an AI Search platform and applies AI and automation analysis to a very practical commerce problem: helping shoppers get from intent to product faster. Retailers do not need more novelty AI. They need capabilities that reduce friction, improve relevance, and make merchandising operations more scalable. Context-aware faceting is especially important as discovery moves from static navigation toward AI-enabled, behaviour-driven experiences.”
Dynamic Facets builds on Algolia’s existing faceting suite, including searchable facets, which let users search within long filter lists without scrolling. Together, they give teams the flexibility to choose how much to configure manually and how much to automate.
Dynamic Facets is available now for Algolia customers—see more details here: https://www.youtube.com/watch?v=dli4ekL_GbQ&t=25s.
About Algolia
Algolia is the leading AI Search and Retrieval platform, powering 1.75 trillion searches a year for more than 18,000 businesses. With a unified keyword and vector search and retrieval engine, Algolia delivers the world’s fastest and most scalable search and discovery technology. Companies rely on Algolia to build agentic, generative, and search experiences through tools like Agent Studio. With over a decade of innovation, Algolia is redefining retrieval-powered applications and the future of AI discovery.
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