Michael Booth, Ph.D.
Product optimization through experimental design. I turn complex trade-offs into clear product decisions for the world's biggest brands.
Product optimization through experimental design. I turn complex trade-offs into clear product decisions for the world's biggest brands.
I'm a survey research specialist in product optimization who has led 100+ conjoint and discrete choice studies for major medtech, consumer devices, and healthcare brands. I query consumers about trade-offs they're willing to make against constraints and prices, then translate those insights into clear product decisions. I built my own experimental design stack from scratch: D-optimal algorithms with Fisher information matrix optimization in Python, and Hierarchical Bayesian modeling using an R-NUTS sampler.
Conjoint, MaxDiff, and pricing research for global brands in medtech, consumer devices, and healthcare, querying consumers about trade-offs against constraints and prices
Built D-optimal and D-efficient discrete choice designs from scratch using Fisher information matrix optimization in Python, with Hierarchical Bayesian estimation via R-NUTS sampler
Longitudinal tracking automation that cut quarterly reporting from 2 months of two people's time down to under 2 weeks
Fraud detection systems for market research, published in Quirk's and presented at major conferences
Balancing stakeholder needs across product, engineering, and finance to deliver research that drives real decisions, not shelf reports
A consumer sentiment tracking dashboard on the state of the national economy that automatically populates with survey responses, showing trends in economic decision-making for financial firms' strategic planning
I bridge the gap between engineering constraints and business value. I translate complex experimental results into strategic product decisions that cross-functional stakeholders can act on.
I don't just deliver analysis. I influence product roadmaps through data, working directly with product, engineering, and finance teams to turn research into revenue.
Ph.D. from the University of Michigan School of Public Health with an appointment at the Institute for Social Research, where I completed my dissertation as a National Institute on Aging Trainee. I worked on the Health and Retirement Study, one of the longest-running longitudinal studies of aging in the U.S.
Ph.D., Public Health
NIA Trainee
2021
M.S., Applied Psychology
2016
B.A., Behavioral Science
2013
Specialized knowledge at the intersection of methods, data, and impact.
Conjoint analysis, discrete choice modeling, willingness-to-pay estimation, portfolio optimization, and competitive market simulators.
Experimental design, A/B testing, Hierarchical Bayes modeling, MaxDiff analysis, and Gabor-Granger pricing studies.
Machine learning, market segmentation, forecasting, and classification. Proficient in R, SQL, Q Research Software, and Displayr.
Peer-reviewed survey methodology research using world-class longitudinal data.
Authors: Booth MJ, Kobayashi LC, Janevic MR, Clauw D, Piette JD
Journal: BMC Rheumatology, 5(1):48
Summary: Longitudinal cohort study using Health and Retirement Study data linked to Medicare claims, examining whether immune-mediated inflammatory diseases (rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis, Crohn's disease, ulcerative colitis) increase risk of Alzheimer's disease. Findings showed no increased AD risk among IMID patients over a 6-year follow-up period.
Authors: Booth MJ, Janevic MR, Kobayashi LC, Clauw D, Piette JD
Journal: BMC Rheumatology, 5(24)
Summary: Cross-sectional analysis of 4,462 participants from the 2016 Health and Retirement Study with linked Medicare claims. Used ICD codes to identify RA diagnoses and the Langa-Weir Classification for cognitive status. Found no association between RA and cognitive impairment in this nationally representative sample.
Authors: Booth MJ, Clauw D, Janevic MR, Kobayashi LC, Piette JD
Journal: ACR Open Rheumatology, 3(4):239-246
Summary: Validation study of 3,768 Medicare-eligible respondents from the Health and Retirement Study. Compared self-reported RA diagnoses against three claims-based algorithms. Found that most older adults who self-report RA do not have Medicare claims history consistent with that diagnosis, suggesting need for revised survey questions.
Discipline, dedication, and competitive excellence.
Athletics has been a cornerstone of my personal and professional development. The discipline, strategic thinking, and resilience cultivated through competitive sports directly translate to my approach to research and problem-solving. As a retired professional cyclist with three state championships and over 60 career wins, I learned the value of data-driven preparation, tactical decision-making under pressure, and the relentless pursuit of marginal gains. These skills directly inform my analytical work today.
