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Applications of Analytics

User Testing

Category: Predictive Analytics

Analytics can offer novel approaches to user testing using data that might be otherwise opaque to evaluators. For example, Lester Tong and his colleagues (Tong, et.al., 2020) investigated whether “individuals’ neural responses to videos could predict their choices to start and stop watching videos.” Tong explains, “Here we have a case where there is information contained in subjects’ brain activity that allows us to forecast the behavior of other, unrelated, people—but it’s not necessarily reflected in their self-reports or behavior” (Stanford, 2020).

A company called UserTesting writes on its website, “analytics can—and should—guide usability testing efforts… because analytics can reveal problems that usability testing could never uncover. Usability testing is typically conducted with a small, representative sample of visitors. It also takes place on a fairly limited number of pages. So if a site has 10,000 products, and there’s a problem with one page or product category, it’s highly unlikely that usability testing would reveal the problem” (UserTesting, 2013).

Aaron Powers (2018) identifies three major types of application of analytics for user testing: discovery (“when your project is early on, you don’t know what you don’t know, and are open to anything”), testing hypotheses (“When your team has specific ideas and you’ve collected specific data around those ideas”), and to simplify problems (in case “results are too complex for people to understand, or the problem just seems too big to pull it together”).

Examples and Articles

Analyzing usability testing data
Clouston Mahon Feb 17, 2018. "I aim to provide a system for anyone involved in user research, or, anyone wanting to get a better insight into the research practices of their team or company, a way to analyse the data gathered from usability testing studies." Direct Link

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