User Experience Study: Best Buy vs Newegg
WPI Course Project: UX Applications
Overview
The purpose of this study was to evaluate the user experience of two websites often used to purchase electronics: Newegg and Best Buy. Our objective was to learn about how the usability of each site differs through the design of our own UX study.
Learning Opportunities
This UX study demonstrates skills in conducting controlled experiments, gathering and analyzing multiple types of data, using statistical tests, creating actionable findings, and effectively presenting results. The knowledge of UX research concepts and principles is also exhibited.
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Conducting user research studies
Designing and executing a within-subjects study
Creating study materials and procedures
Collecting and analyzing quantitative data
Conducting qualitative interviews
Analyzing data using statistical tests like t-tests
Interpreting results using frameworks like technology acceptance model (TAM)
Creating presentations to summarize findings
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Google Forms to collect Common Validated Constructs data
Screen recording tools via Zoom to capture task completion
Statistical analysis tools like Excel for t-tests
Data visualization tools such as Excel or Sheets to create charts/graphs
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Within-subject study design - Comparing user experience of two websites using the same group of participants.
Latin square method - Counterbalancing the order of the website and tasks to eliminate order biases.
Task completion metrics - Measuring duration and number of clicks to complete tasks.
Common validated constructs (CVCs) - Standardized measures of user perceptions, like perceived ease of use, perceived usefulness, and behavioral intention to use.
TAM (technology acceptance model) - Model relating perceived usefulness and perceived ease of use to usage intentions. Used to interpret user responses.
R-squared - Metric indicating how much variation in one variable can be explained by another.
Null and alternative hypotheses - Claims tested by the statistical analysis.
Paired t-tests - Statistical test used to compare means between two related groups
p-values - Used to determine if differences between groups are statistically significant.
Quantitative data - Numerical data from task completion times/clicks and CVC survey responses. Analyzed using statistical tests like paired t-tests.
Qualitative data - Subjective feedback from open-ended interview questions. Analyzed to identify common themes.