Log in or create a free Rosenverse account to watch this video.
Log in Create free account100s of community videos are available to free members. Conference talks are generally available to Gold members.
Casual Inference
Summary
You've probably heard the old adage "correlation does not imply causation" but at some point we've got to say that drinking boiling hot tea and burning our tongues are more than just "strongly correlated". Enter Causal Inference, a collection of techniques for reasoning about the relationship between effects that can be measured and causes that can be identified. It helps us bridge between what we hear when we talk directly to users and what we observe about their behavior at scale and over time. This talk will introduce some of the key techniques in causal inference and how they can be used by UX Researchers and Designers to understand potential users, current users, and the products we might build.
Key Insights
-
•
Causal inference bridges qualitative reasoning about context with quantitative analysis of data.
-
•
Directed acyclic graphs help visualize causal pathways and common pitfalls like confounders and colliders.
-
•
Randomized controlled experiments require random assignment, blinding, and pre-specified hypotheses to measure causal effects reliably.
-
•
Average treatment effect summarizes impact on an entire population, whereas intent-to-treat reveals experiment adherence issues.
-
•
Quasi-experimental methods like regression discontinuity and difference-in-differences allow causal inference when randomization is not possible.
-
•
Matching is an art, relying on context-aware ranges rather than exact numeric equivalence to equate comparison groups.
-
•
Synthetic control methods build counterfactual scenarios when no good control group exists.
-
•
Understanding and designing for interpretability strengthens collaboration between designers and analytics or marketing teams.
-
•
Qualitative research poses valuable questions; quantitative causal inference sharpens and tests these questions.
-
•
Behavioral causes revealed by causal inference may differ from user self-reported reasons, offering deeper insights.
Notable Quotes
"Correlation doesn’t imply causation, but sometimes two things happening together do imply a causal mechanism."
"Qualitative reasoning about causal mechanisms usually comes from lived experience, either the researcher or participants."
"Designers have a hard time interpreting econometrics-driven quantitative research without bridging approaches."
"Random assignment to treatment or control is essential—if it’s not random, it’s not a true experiment."
"If you cannot remove a treatment, it may not be a true cause."
"Matching is very much an art, not a science; there are no hard and fast rules for what counts as a good match."
"Difference-in-differences lets you study treatment effects in groups that start in very different places by looking at trends."
"Synthetic controls create counterfactuals using historical data when no suitable control group exists."
"Qualitative research really poses questions; quantitative methods let you investigate those questions rigorously."
"You don’t want to overdesign just to make something more data interpretable because that can lead you down a dark path."
Or choose a question:
More Videos
"Managers were asking for user stories but hadn’t done any analysis or design — they didn’t understand the scope."
Carl TurnerYou Can Do This: Understand and Solve Organizational Problems to Jumpstart a Dead Project
March 28, 2023
"Most employees take at least 90 days to onboard and another 90 days to become productive — that’s half a year before you see impact."
Karen PascoeDeveloping Experience Teams and Talent in the Enterprise
June 8, 2016
"Having cameras on during meetings, even for those in the same room, really helps remote employees feel included."
Jilanna WilsonDistributed Design Operations Management
October 23, 2019
"We have over 30 contracting teams spread across roughly 10 vendors all working on parts of the veteran experience landscape."
Shawna Hein Kevin HoffmanCreate a Cohesive Civic Design Practice Across Agency, Vendors, and Contracts
November 17, 2022
"Site visits with users don’t just give actionable insight; they give us raw, humbling inspiration to keep going."
Barb SpantonDoing Work That Matters: A Look Beyond The Idealistic Notion of 'Doing Meaningful Work'
June 10, 2022
"If a feature didn’t align with our core UX principles, it probably didn’t belong in our application."
Briana ThomasThe Quiet Force: Uncovering Hidden Leadership in High-Impact Design Teams
September 24, 2024
"Service design is 10% connecting the dots and 90% creating the conditions that bring those dots closer together."
Gina MendoliaTherapists, Coaches, and Grandmas: Techniques for Service Design in Complex Systems
December 3, 2024
"We need to become data ethicists and curators, not just data vacuum cleaners, to prioritize quality data."
Lija Hogan Milan Mijatovic Sam Proulx Louis RosenfeldThree Years Out: Perspectives on the Near-Term Future of User Research
March 15, 2024
"DPM loneliness and siloing happen because of wearing too many hats and inheriting mismatched responsibilities."
John Calhoun Rachel PosmanTwo Sides of the DesignOps Coin: Teams Ops and Product Ops
January 8, 2024
