User Research

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Statistics ( 51 )
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Online panels are a major source of participants for both market research and UX research studies. In an earlier article I summarized some of the research on the accuracy and variability of estimates from online panels. The types of estimates from those studies tended to center around general demographic or psychographic questions (e.g., smoking, newspaper readership). To understand whether similar findings would hold for UX-related

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Online panel research has been a boon for market research and UX researchers alike. Since the late 1990s in fact, online panels have provided a cost effective pool of sample participants ready to take online studies, covering topics from soup to nuts (literally)…from apple juice to zippers. But can you trust the data you get from these online participants? In this article, I'll examine the

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"I'd like you to think aloud as you use the software." Having participants think aloud as they use an interface is a cornerstone technique of usability testing. It's been around for much of the history of user research to help uncover problems in an interface. Despite its popularity, there is surprisingly little consistency on how to properly apply the think aloud technique. Because of that,

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[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_column_text]The affinity diagram is a visual technique to organize ideas and information. The "affinity" between pieces of information reveals patterns and often a hierarchy that can help with product design (similar to the affinity or basket analysis). It's also known as the K-J method for its creator, Jiro Kawakita, who developed it as one of his seven quality tools in the 1960s. Jiro was a

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Google Analytics is an amazing tool for understanding website traffic. There's a reason most of the top websites use it. Among other things it can tell you: - How many people visit daily, monthly, and across years and seasons - How much time people spend on pages - What pages get the most visitors - Which pages people arrive on and depart from Despite the

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You often hear that research results are not "valid" or "reliable." Like many scientific terms that have made it into our vernacular, these terms are often used interchangeably. In fact, validity and reliability have different meanings with different implications for researchers. Validity refers to how well the results of a study measure what they are intended to measure. Contrast that with reliability, which means consistent

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In 1963 Yale Psychologist Stanley Milgram paid volunteers $4 to "teach" another  volunteer, called the "learner" new vocabulary words. If the learner got the words wrong, he or she received an electric shock! Or, so the teacher/volunteer was led to believe. In fact, no shock was given, instead a person working with Milgram pretended, with great gusto, that they were being shocked. So while no

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Which design will improve the user experience? One of the primary goals of conducting user research is to establish some causal relationship between a design and a behavior. Typically, we want to see if a design element or changes to an interface lead to a more usable experience (experiment) or if more desirable outcomes are associated with some aspect in our designs (correlation). Even though

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For as long as user interfaces have had icons, there have been strong opinions about what makes an effective icon. From the business analyst to the CEO, we all like to tell the designer what's "intuitive" and what's "terrible." Instead of making decisions based on the pay grade of the people in a meeting, consider using some data driven approaches to make better decisions. While

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There are a lot of mistakes that can be made when conducting any type of research. But almost all research contains some mistakes in methodology, measurement or interpretation. Rarely do the mistakes render the research useless. To help make your next user research endeavor more useful, here are five common mistakes to avoid. 1. Usability tests that are actually feature reviews: If you ask users

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