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When Is Faceted Search Appropriate?

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Earlier this week, Peter Morville and Mark Burrell presented a UIE virtual seminar on “Leveraging Search & Discovery Patterns For Great Online Experiences“. It sold out! And I thought Pete Bell and I had done well with our seminar on faceted search!

But I’m hardly surprised. Although I wasn’t able to attend it myself, I gather from Twitter and the blogosphere that it was a great presentation. I enjoyed serving as a reviewer for Peter’s new book on Search Patterns, and I contributed a bit to Endeca’s UI Design Pattern Library while I was there and Mark’s team was developing it.

In reading reactions to the seminar, I was particularly intrigued by a post entitled “Search and Browse” by Livia Labate on her fantastically named blog, “I think, therefore IA“. She raised a question that I think needs to be asked more often: when is (or isn’t) faceted search appropriate?

Her conversation with readers in a comment thread offered some possible answers:

  • Faceted search helps users who think in terms of attribute specifications as filtering criteria.
  • Faceted search supports search by exclusion, as opposed to by discovery.
  • Faceted search requires a set of useful facets that is neither too small nor too large.

I’d like to propose my own answers. Here are the conditions for which I see faceted search being most useful:

  • Faceted search supports exploratory use cases, in contrast to known-item search. For known-item search, users are better served by a search box to specify an item by name, or a non-faceted hierarchy to locate it. In contrast, faceted search optimizes for cases where users are either unsure of what they want or of how to specify it.
  • Faceted search helps users who need or want to learn about the search space as they execute the search process. Facets educate users about different ways to characterize items in a collection. If users do not need or want this education, they may be frustrated by an interface that makes them do more work.
  • The search space is classified using accurate, understandable facets that relate to the users’ information needs. As I’ve discussed before, data quality is often the bottleneck in designing search interfaces. Offering users facets that are either unreliable or unrelated to their needs is worse than providing no facets at all.

Given the above criteria, it’s not surprising that faceted search has been a huge success in online retail: shopping is often an exploratory learning experience, and retailers tend to have good data.

But the success of faceted search in retail overshadows other domains where faceted search may be even more valuable. My favorite example is faceted people search, most recently demonstrated by LinkedIn. I would love to see other entities (locations, businesses, etc.) receive similar treatment, at least in contexts where exploration is a common use case.

I think Livia is right to be skeptical about any interface that introduces complexity–and facets do introduce complexity. I hope that my guidelines help answer her question as to when that complexity is worthwhile and perhaps even necessary to help users satisfy their information needs.

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