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
"If you don’t understand the financial flow in an organization, you’re financially illiterate and you’re on top."
Christian MadsbjergInfluencing Strategy
March 31, 2020
"Solutions range on a spectrum from offensive and impartial to informed and holistic toward women."
Mansi GuptaWomen-Centric Research: What, Why, How
March 29, 2023
"We’ve learned that clear communication about roles and process is key to reduce confusion between regular design work and self-service."
Nora Tejeda Giovanna AlonsoScaling Design Capabilities at BBVA Through a Self-service Design Model
June 10, 2021
"Youth, families, and communities impacted by the child welfare system experience a lot of loss of control, with important aspects of their lives decided without their input."
Sarah FathallahA Typology of Participation in Participatory Research
March 28, 2023
"Qualitative data is data. It’s okay to be informal and human when designing complex systems."
Alison Rand Sarah BrooksScaling Impact with Service Design
March 25, 2021
"Accessible mobile designs can be reused on desktop, but desktop-first accessibility is harder to transfer to mobile."
Sam ProulxMobile Accessibility: Why Moving Accessibility Beyond the Desktop is Critical in a Mobile-first World
September 8, 2022
"The most successful way to ask about job function is a single-select question, not an open field."
Sydney LawsonAnatomy of a Strong User Panel
March 10, 2026
"Research is the most analytical form of information processing because it involves active knowledge generation."
Kristen Guth, Ph.D.Out of the FOG: A Non-traditional Research Approach to Alignment
March 28, 2023
"It’s important to put the participant at ease and not add to their cognitive burden."
Sam Ladner Megan Blocker Tanvi Dhond Katie Hansen Ricardo MartinsMethodologies: Beyond the interview [Advancing Research Community Workshop Series]
September 4, 2024
