Easy everything in UX Research
First technical questions to scope a journey-map pain point
Ask how widespread and severe it is, where in the system it originates, and what constraints bound a fix.
What is PII and how to keep it out of logs
Define PII, redact or mask at the logging boundary, and avoid logging sensitive fields at the source.
Aesthetics-Usability Effect
The aesthetics-usability effect is the tendency for users to perceive attractive designs as easier to use and to be more tolerant of minor usability problems in them, which can mask real issues during testing.
Describe lightweight user validation without a dedicated researcher
This tests if you value direct user feedback over expert-only evaluation without researchers. A strong answer covers recruiting fresh users and observing real use for intuitiveness.
How would you integrate user research into agile sprints without disrupting velocity?
Tests embedding continuous discovery into agile rather than front-loading research. Strong answers mention parallel tracks, backlog stories derived from insights, and lightweight discount-usability methods.
Which ARIA attribute fixes an icon-only button missing its screen reader name?
Tests knowledge of accessible names for interactive elements lacking visible text. Answer: aria-label on the button describing its function, plus aria-hidden on the decorative icon. Red flag: suggesting alt text on the SVG or title attributes as the fix.
How would you usability-test a feature-flagged staging component?
Tests if you know usability testing works early. Strong answer: realistic tasks with careful wording to avoid priming; facilitator observes behavior and asks followups without influencing participant; staging is just another interface.
How do you share research findings with engineers so they stay actionable?
Tests whether you respect engineering workflows. Offer tiered formats like quick decks, shared docs, or raw notes; embed insights into tickets; anchor findings to user quotes for trade-offs. Red flag: forcing live attendance or sharing long standalone decks.
What research do you give an engineer starting a new feature?
This tests distilling research into actionable engineering guidance. A strong answer gives the engineer a validated problem statement and user context, delivered in the ticket or a five-minute sync. A red flag is handing over a full research deck or raw notes.
How do you reliably deliver a survey to 10,000 users?
Tests systems thinking for outreach at scale. Strong answers cover idempotent delivery, rate-limited async sending, PII handling and retention, plus observability into delivery and response rates.
Design a database schema for a research participant panel
Your ability to normalize relational data without over-engineering. Propose a participants table for contact and demographics; a participation_history table with foreign keys; and a consent_log table.
Are 1-5 satisfaction ratings continuous or discrete?
Tests knowledge of measurement scales. A strong answer calls 1-5 ratings discrete and ordinal, notes intervals may be unequal, and prefers medians or non-parametric tests over means unless equal spacing is defensible.
Explain what a p-value represents in an A/B test and interpret 0.03
This tests frequentist hypothesis testing literacy. It is the chance of seeing a result this extreme if the null of no effect were true; 0.03 means 3% chance of such data under the null, not 97% chance the variant wins. Red flag: saying 97% likely.
Mean, median, and mode: which measure for task completion times?
This tests whether you know task times are skewed and sample size drives the mean-versus-median choice. A strong answer cites the under-25 rule, contrasts mean outlier sensitivity with median robustness, and dismisses mode. Red flag: defaulting to the mean.
Explain coding in qualitative analysis and your codebook process
Tests systematic tagging of observations/quotations to discover themes, not ad-hoc skimming. Strong answers mention uploading transcripts to software or affinity diagramming, and stress that themes emerge across multiple participants.
Walk me through your next steps after five user interviews
Extract observations onto sticky notes, cluster into themes as a team, then prioritize for next steps.
What user struggles indicate code bugs versus design flaws?
This tests triage judgment in usability testing. Bug signals: crashes, broken interactions, data loss. Design flaws: confused navigation, ignored elements, excessive effort. Red flag: blaming users or labeling every issue a UI problem without checking logs.
Describe heuristic evaluation and two heuristics that guide UI components
Tests if you bridge UX research and frontend decisions. Define heuristic evaluation as expert review against rules of thumb, cite two NN/G heuristics, and map each to a concrete component behavior. Red flag: listing heuristics without code impact.
Usability vs A/B testing: when should engineers advocate for each?
Tests qualitative versus quantitative UX methods. Outline: usability observes why users struggle and finds bugs; A/B compares live variants to optimize conversions. Choose usability for unknown friction, A/B for known tweaks.
Your role and pitfalls as an engineer note-taker in interviews
Observe to leverage researcher expertise; pitfalls are skipping prep, academic framing, and inflexible features.
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