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An international peer-reviewed journal

Usability Testing with Real Data

Alex Genov, Mark Keavney, and Todd Zazelenchuk

Journal of Usability Studies, Volume 4, Issue 2, February 2009, pp. 85-92

Article Contents

Real Tasks, Real Users … But What About Real Data?

In the field of user experience design and research, we routinely speak of the importance of having real users perform real tasks in order to effectively evaluate the usability of our products. The following are just a few examples:

What is rarely discussed, however, are the pieces of information or data that participants actually encounter when they interact with our prototypes. In most cases, these data are fictitious, made to resemble the average users' data in the hopes of having participants successfully immerse themselves in the given scenarios. However, like the proverbial man with his head in the freezer and feet in the fire (but who's just fine, on average), having all the users interact with an average set of data does not mean that those data will be appropriate for any of them. A usability task with a 10-item list of stock sales is not a good test for anyone if nine in ten users typically have one stock sale in the list and one in ten has 100. And even for those users for whom the fake data is typical, the fake data will at the very least be unfamiliar, and will require the participant to assume the role of someone else in order to understand and relate to their experience during the research study.

For many products and systems, this may not be a huge problem. For example, participants involved in testing an online retail or travel Web site are likely to be familiar with the scenarios and able to adapt to the data presented. So a task to purchase a particular book or arrange a trip to Miami may be a good test of the interface even if a user has never bought that book before or if the user has never flown to Miami. Data are not critical in these cases, and the user is likely to be able to relate the test scenario to their own life experience, as long as they have some familiarity with these types of tasks.

But for some products, the participants' personal data represent an integral part of the product. For example, imagine testing an interface for setting photo sharing permissions or a system for online bill pay. In such cases, the particular photos that a user wants to share, and friends with whom they want to share them, or the number and timing of the bills to be paid will have a huge effect on how the user interacts with the interface. In these systems, testing with fake data means testing a fake user experience, one that's potentially quite different from what users will have in the real world.

The way to get around this problem is to use the usability participant's real data in the study, rather than data artificially created to simulate the real thing. In other words, rather than making up reasonable approximations of users' banking transactions, annual income statements, or medical claim details, a researcher can find ways to incorporate users' actual information into the design being tested.

Numerous examples of research in psychology support the wisdom of this strategy. The first involves the "self-referencing effect" (Greenwald & Banaji, 1989) which suggests that information relevant to the self can be more easily encoded in memory and easily retrieved at a later date. Based on the self-referencing effect, we may hypothesize that by using artificial data rather than users' real data in a usability test we may impede a user's ability to perform as efficiently as he or she normally might.

A second line of research with similar implications for real data usability evaluations is related to the familiarity or novelty of content. This research has found that reactions to familiar vs. novel content are correlated with changes in different regions of the brain and may reflect different memory processes (Tulving, Markowitsch, Craik, Habib, & Houle, 1996), again potentially having a negative impact on a user's efficiency and effectiveness performance when completing desired tasks.

Finally, research has shown that a connection exists between personally relevant information and one's motivation to think about and elaborate on the topic at hand (Thomsen, Borgida, & Levine, 1995). In the context of usability studies, users' real data may motivate users to engage with a product in a more authentic, genuine manner than with artificial data. In the experience of Intuit product teams, this increased level of engagement has produced more accurate and richer findings than otherwise collected with fictitious user data.

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