
A search happens whenever a user looks at any GUI: the process of scanning your interface to determine where to click, tap, or look is a conceptual task known as Visual Search. Many factors shape a user’s visual search, for example:
- Habituation
- The salience, number, and legibility of features
- The user’s level of expertise in interfacing with GUIs in general
- Latent biases based upon other/similar sites that they know well
- The user’s language
And even though there are plenty of tools, like user testing, heat maps of user interactions, eye tracking studies – there is no silver bullet for understanding exactly where an individual user will look for things when interfacing with your GUI. Still, assuming visual search is a search task like any other – what insight might we gain from thinking about visual search the way we think about other forms of search?
These are the steps that the user goes through in doing a Visual Search:
- Identify the search space. You might go to Google to search the Web. You may go to Twitter to see what tweets are trending. Both are searches driven by your own high-level goals, but the search spaces themselves are very different. In the visual search of your GUI, the user’s search space will vary too – largely depending upon the user’s proficiency within your site, and their own conceptual biases. If they’ve never been to your site before, the search space will be your overall page (or regions of it). But if they’re familiar with your GUI, the search space may be confined to particular components (like your sidebar nav as an entry point, or the login block) that your user believes will contain the information they’re looking for. This is important to keep in mind when you’re designing for new versus return users: an expert/returning user’s reduced search space helps make Visual Search easier to do, but introduces a preconceptual bias in terms of where the user will tend to look be looking.
- Create the query. Users will be looking for one of two things: a specific artifact that they believe exists within the search space, or artifacts of a certain type that they believe to exist. For example: I may want to revisit a specific article on cnn.com that I was looking at 15 minutes ago to see what comments have popped up. Or, I may simply go to the cnn.com home page to look for new articles that are interesting: I know articles exist there, but I’m not yet sure if there are any interesting ones. These are two very different types of Search, often supported through complementary Browse/Search user flows.
- Examine the resultset. The resultset in a Visual Search is comprised of the particular interface features that were notable and which caught the user’s attention as they scanned the aforementioned search space. Unlike explicit search operations within which the user invokes a query to have a set of results returned to them, Visual Search is more of an implicit search where the user extracts features out of their visual field. The factors impacting notability of any particular feature are the focus of a significant body of research – wikipedia is a great place to start. But some key factors include: salience (i.e., how bright is its color?), positioning (i.e., is it in the expert user’s search space?), and noteworthiness or subjective interest. The resultset is essentially the subset of UI features that stand out to the user, the elements that catch her eye.
- Iteratively refine the search. Like other forms of search, Visual Search is iterative. Based upon the relative quality of the results, a user may reflect upon and change their query: “Did I find what I wanted? Are my options interesting?” But interestingly enough, I may also reflect upon my search space, and change that. If I return to the cnn.com homepage but I don’t find the article where I’d found it before, I may shift my search space to include the entire page (not just the page component where the article used to be) and I might also change my query (from looking for the specific article to looking for a category that I think might contain the article.) A user’s visual search has built-in mechanisms for “adjusting” their mental models in terms of shifting the search space/query. This is both an opportunity and a risk – it might help returning users discover and identify new features, but it could also mean that user will change their search space to someone else’s site, in order to find what they are looking for.
- Select a result. Once the user finds a result that matches their query best, they will select it. In visual search this doesn’t necessarily mean that someone clicks on something – it might just be that the user looks at it, or shift her search space to focus on that particular component. The important thing is that the user has made the decision to focus some of their attention on that part of your GUI.
Have you ever thought about Visual Search this way? Do you find it useful in terms of how you might evaluate your designs? Identifying the Search Space seems like a particularly important step to think about, especially in terms of a user’s long-term usage of our GUIs – something we all hope to support.








