Erdős Institute UX Research
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The work found on this website was completed as part of the Fall 2023 Erdős Institute UX Research Course and represents solutions to UX-centered business problems. Specifically, we conducted market research to advise product diversification, completed qualitative analysis of interview data to construct user personas which were used to inform product design and address website conversion issues, and designed a survey and A/B test to conduct hypothesis testing in order to address Voice of the Customer and improve membership churn. You can explore our research, methods, and findings for each of these projects on this website.
The Team
Kristina Knowles
Kristina Knowles
Interdisciplinary Music Researcher
Kristina has over 10 years of experience leveraging data and domain knowledge to solve problems, answer questions, and communicate findings to diverse audiences. During her years as an academic researcher she has honed skills in data and statistical analysis, human behavior research, and managing complex projects. Throughout her career she's worked with specialists from various disciplines, constantly adapting and learning new methodologies to suit diverse research needs. She is particularly interested in how we can use data to gain insights into the way people perceive and interact with the world, technologies, and each other.
Riti Bahl
Riti Bahl
PhD Candidate at Emory University
As a computational mathematics PhD student at Emory University, Riti focuses on the applications of math in climate-related problems. With a strong background in data collection & processing, communication, collaboration and interdisciplinary applications of mathematics, they bring creative problem-solving skills honed during their academic journey. Passionate about presenting complex ideas accessibly, Riti is interested in projects that leverage data for informed decisions, prioritizing accessible user experiences.
*In the absence of real-world customer data from businesses, synthetic data was created, either through the use of random number generators for survey responses or through the use of prompt engineering with AI models (ChatGPT, Claude) to generate interivew responses based on constructed user profiles provided to the model. Real data from market research was used where possible.
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