Design a system to A/B test headlines for a single article URL
WHAT IT TESTS: controlled experiment design with user bucketing and attribution. ANSWER OUTLINE: hash users for sticky variants; store separately; emit events; compute CTR. RED FLAG: client-side randomization without stickiness or event tracking.
Outline a strategy to improve LCP and CLS for blog article pages
WHAT IT TESTS: Pinpointing LCP/CLS via render, not generic tips. ANSWER OUTLINE: Fix LCP with server speed, resource hints, critical CSS; fix CLS with explicit sizes and font-display.
Build a dynamic table of contents from article h2 tags
WHAT IT TESTS: Basic DOM querying and dynamic element creation in vanilla JS. ANSWER OUTLINE: Query h2s with querySelectorAll, assign ids, map to anchor links, append a nav list. RED FLAG: Importing jQuery or a framework for a six-line native task.
Design a centralized Copy Service with versioning, segmentation, and experiments
This tests separation of editorial workflow from runtime delivery. A strong answer covers immutable versioned records, a resolution API evaluating segmentation rules, and delegating experiment bucketing externally.
Caching and performance challenges in SSR with personalized copy
WHAT IT TESTS: Cache efficiency versus segment personalization at scale. A GOOD ANSWER: Segment-level cache keys, short TTLs with stale-while-revalidate, and edge personalization to protect origin. RED FLAG: Per-user cache keys or disabling cache entirely.
Architect a real-time multi-armed bandit and compare trade-offs to A/B testing
WHAT IT TESTS: Real-time ML serving and statistical trade-offs. ANSWER OUTLINE: Sketch a fast arm router, streaming feedback, and model updates; contrast MAB regret minimization with A/B's unbiased estimates.
How would you track multiple CTAs to the same conversion goal?
Tests granular event attribution beyond aggregate counts. A strong answer uses unique data attributes per CTA, routes clicks through GTM into GA4 events, and ties them to the conversion. Red flag: relying only on destination URLs, which fails if paths match.
How would you architect personalized email and coupon delivery at scale?
This tests decoupled rendering and atomic coupon reservation. A strong answer uses template rendering, atomic coupon reservation, an idempotent queue, and batched ESP delivery. Red flag: generating coupons during SMTP without reservation risks overspend.
How would you instrument a CTA button and describe its event payload?
This tests basic event instrumentation and payload design. Mention a click listener, a gtag call with an event name, and parameters like button_text and page_path. A red flag is a bare event name with no parameters or mixing pageviews and clicks.
Describe how you'd implement an A/B test for a landing page headline
WHAT IT TESTS: Experiment integrity beyond DOM swaps. ANSWER OUTLINE: Mention deterministic bucketing, anti-flicker rendering, tracking with variant IDs, and sample-size planning. RED FLAG: Swapping headlines client-side after paint biases data and hurts UX.
Design an algorithmic E-E-A-T scoring system
Tests turning subjective quality into signals. Split E-E-A-T into distinct feature families, combine structured metadata with unstructured NLP and graph signals, and calibrate against human rater labels. Red flag: one opaque score or CTR as trust proxy.
Design a system to detect keyword cannibalization
WHAT IT TESTS: Whether you can distinguish search-intent overlap from keyword duplication at scale. A GOOD ANSWER COVERS: Query-page-position data, intent clustering, and rank volatility. RED FLAG: exact-keyword deduplication without modeling intent or CTR.
Architect a large-scale real-time recommendation system with data pipelines
Tests multi-stage ML serving under 200ms latency. Strong answers use a funnel: two-tower embeddings with ANN retrieval, ranking, and guardrails, plus separate batch and real-time pipelines. Red flag: scoring the full catalog per request without approximation.
Design architecture for multi-channel article distribution from a single source of truth
Tests separation of content and presentation via headless CMS. Strong answers cite a central structured CMS, content API, channel-specific rendering layers, and webhook push. Red flag: manual duplication or direct database sharing without API abstraction.
Design a secure templating engine for user notifications
Tests balancing creator flexibility with defense-in-depth security and i18n. Strong answers cover context-aware auto-escaping, a restricted AST grammar, ICU MessageFormat for pluralization, and sandboxed execution.
Design a headless CMS model for brand voice metadata and API usage
WHAT IT TESTS: Structured content beyond page blobs. Strong answers validate tone, context, and character limits in the CMS; expose them via API filters; and let clients render context-aware components.
How would you automate forbidden-word checks in CI/CD?
This tests embedding brand governance into engineering workflows. A strong answer covers AST-aware string extraction, CI gating with severity levels, and allowlisting to cut false positives.
How would you architect a white-label content system for multiple brand voices?
Tests content-presentation separation for multi-tenant apps. Strong answers use a headless CMS with tenant keys, a domain resolver for brand voice, and shared components with injected strings. Red flag: duplicate codebases or hard-coded copy per client.
Propose a multi-armed bandit system to optimize headlines faster
This tests online learning and the explore-exploit tradeoff. Answers contrast fixed A/B with adaptive allocation, sketch a Bayesian bandit service with a min exploration rate, and note delay.
How to merge analytics and CRM data to auto-segment users by persona
This tests multi-source data unification and identity resolution. A strong answer covers ID stitching, a unified profile, deterministic or ML segmentation, and data quality. RED FLAG: Treating email as a perfect join key or ignoring anonymous users.