3.4. Learning About Information Needs and Information-Seeking Behaviors

How does one learn about their users' information needs and seeking behaviors? There are a variety of user research methods to considertoo many to cover in detail hereso we'll recommend a pair of our favorites: search analytics and contextual inquiry. Search analytics ^{[ ]} involves reviewing the most common search queries on your site (usually stored in your search engines logfiles) as a way to diagnose problems with search performance, metadata, navigation, and content. Search analytics provides a sense of what users commonly seek, and can help inform your understanding of their information needs and seeking behaviors (and is handy in other ways, too, such as developing task-analysis exercises).

^{[ ]} For more on search analytics, read the forthcoming book by Rosenfeld and Wiggins, While search analytics is based on a high volume of real user data, it doesn't provide an opportunity to interact with users and learn more about their needs directly. Contextual inquiry, ^{[ ]} a user research method with roots in ethnography, is a great complement to search analytics because it allows you to observe how users interact with information in their "natural" settings and, in that context, ask them why theyre doing what they're doing.

^{[ ]} For more on contextual inquiry, read Beyer and Holtzblatts Contextual Design: Defining Customer-Centered Systems (Morgan Kaufmann).

Other user research methods you might look to are task analysis, surveys, and, with great care, focus groups. Ultimately, you should consider any method that might expose you to users' direct statements of their own needs, and when you can, use a combination of methods to cover as many bases as possible.

Finally, remember that, as an information architect, your goal is to do your best to learn about your users' major information needs and likely information-seeking behaviors. A better understanding of what users actually want from your site will, naturally, help you determine and prioritize which architectural components to build, which makes your job much simpler, especially considering how many ways a particular information architecture could be designed. You'll also have great user data to help counterbalance the other drivers that too often influence design, such as budget, time, politics, entrenched technologies, and designers' personal preferences.