[Sold Out] User-Centered Product Instrumentation and Metrics with Don Kalar

User-Centered Product Instrumentation and Metrics

This two half-day, in-person course focuses on how to turn telemetry from user interactions into useful metrics (aka logs analysis). Topics covered will include: how to collaborate effectively with cross-functional partners to implement and interpret a measurement strategy, the pragmatics of modeling behavior based on limited signals, approaches to identifying instrumentation needs that are user-centered, ethics and responsibilities of gathering behavioral data for research, and more.

This course is suitable for all researchers, or those curious about gathering user-centered data at scale to help inform product health. There is no requirement to know a specific programming language, statistics platform, or front-end library. There will be collaborative exercises that allow for networking with colleagues.

Days and times:
This is a 2-day, in person class. It occurs 1:00pm-4:00pm each day on Tuesday Feb 11 and Wednesday Feb 12, 2025.
An optional lunch will be available and included at no cost at 12:00pm.

Join us at beautiful Fort Mason in San Francisco, and learn to succeed with product metrics from an industry leading expert! 

Note: this course is scheduled so participants may take it together with, or separately from, the Choice Modeling Master Class offered Feb 10-13 in the mornings at the same location (link). 

Instructor: Don Kalar, PhD

Don is a Staff Quantitative UX Researcher and UXR Manager at Google, where he has supported user-centered measurement programs for Google Workspace, Google Cloud Platform, and most recently Android OS. Prior to joining Google, he was a research psychologist at NASA Ames Research Center, and adjunct faculty in the Psychology Department of San Jose State University, teaching courses in statistics, human factors, sensation & perception, and behavioral neuroscience. Don holds a PhD in Cognitive Neuroscience from UCLA, where his research focus was divided between perceptual psychophysics and neuroinformatics.