When we introduce ourselves as quantitative UX researchers, people often get curious about the “quantitative” part of our title. One question they ask is how our work is similar to, or different from, the work of product analysts or product data scientists. We hope this article will provide a comprehensive answer.
Recreativo de
The confusion is understandable. For one thing, we both love data. We’re trained to conduct quantitative analyses with variety of different data sources, including experiments, surveys, and logged behaviors. Many of us, across both groups, come from quantitative disciplines such as social psychology, statistics, computer science, and economics, which help us drive insights and elevate our teams’ understanding of product usage through large amounts of data.
At Facebook, the Data Analytics and the UX Research team share the same mission of explaining phenomena we observe in data. We both focus on making meaningful and interpretable inferences about data, relationships between variables, and explanations for changes or patterns in the data. (By contrast, machine learning engineers and those in other big data roles focus on predicting unknowns as accurately as possible.)At Facebook, the Data Analytics and the UX Research team share the same mission of explaining phenomena we observe in data. We both focus on making meaningful and interpretable inferences about data, relationships between variables, and explanations for changes or patterns in the data. (By contrast, machine learning engineers and those in other big data roles focus on predicting unknowns as accurately as possible.)At Facebook, the Data Analytics and the UX Research team share the same mission of explaining phenomena we observe in data. We both focus on making meaningful and interpretable inferences about data, relationships between variables, and explanations for changes or patterns in the data. (By contrast, machine learning engineers and those in other big data roles focus on predicting unknowns as accurately as possible.)
At Facebook, the Data Analytics and the UX Research team share the same mission of explaining phenomena we observe in data. We both focus on making meaningful and interpretable inferences about data, relationships between variables, and explanations for changes or patterns in the data. (By contrast, machine learning engineers and those in other big data roles focus on predicting unknowns as accurately as possible.)At Facebook, the Data Analytics and the UX Research team share the same mission of explaining phenomena we observe in data. We both focus on making meaningful and interpretable inferences about data, relationships between variables, and explanations for changes or patterns in the data. (By contrast, machine learning engineers and those in other big data roles focus on predicting unknowns as accurately as possible.)