Growth & Business Optimization Topics
Growth strategies, experimentation frameworks, and business optimization. Includes A/B testing, conversion optimization, and growth playbooks.
Growth Hacking Fundamentals
Demonstrate a solid grasp of core growth hacking concepts including hypothesis driven experimentation, basic analytics, acquisition and retention levers, and viral mechanics. Candidates should be able to describe how to generate growth hypotheses, prioritize channels and experiments, choose appropriate success metrics, and interpret simple funnel and cohort signals. At junior levels emphasize conceptual clarity and practical examples rather than deep statistical or engineering implementations.
Funnel Analysis and Conversion Tracking
Product analytics practice focused on analyzing user journeys and measuring how well a product or website converts visitors into desired outcomes. Core skills include defining macro and micro conversions, mapping multi step user journeys, designing and instrumenting event level tracking, building and interpreting conversion funnels, calculating step by step conversion rates and drop off, and quantifying funnel leakage. Candidates should be able to segment funnels by cohort, acquisition source, channel, device, geography, or user persona; perform retention and cohort analysis; reason about time based attribution and multi path journeys; and estimate the impact of optimization levers. Practical competencies include implementing tracking, validating data quality, identifying common pitfalls such as missing events or incorrect attribution windows, and using split testing and iterative analysis to validate hypotheses. Candidates should also be able to diagnose root causes of drop off, create mental models of user behavior, run diagnostic analyses and experiments, and recommend prioritized interventions and product or experience changes with expected outcomes and measurement plans.
Growth Priorities and Roadmap
Evaluate the ability to translate business objectives into a prioritized 12 to 24 month growth roadmap. Candidates should show how to identify the highest impact levers, set measurable objectives and key results, sequence experiments and feature work based on impact and feasibility, define milestones and success criteria, allocate resources, manage dependencies, and establish a regular review cadence with stakeholders including product, engineering, and executives.
Growth Prioritization Frameworks
Core frameworks and techniques used to prioritize growth projects and experiments. Includes qualitative matrices such as impact and effort mapping and value versus complexity, and quantitative scoring models such as RICE scoring spelled out as reach times impact times confidence divided by effort. Candidates should understand how to estimate reach, impact magnitude, confidence or uncertainty, and required effort; consider sample size and statistical confidence when prioritizing experiments; assess strategic alignment with company goals and resource constraints; and communicate tradeoffs clearly. Interview preparation includes practicing ranking and scoring hypothetical initiatives, explaining assumptions and sensitivity to inputs, and justifying prioritization decisions under time or resource constraints.
Curiosity & Staying Updated with Growth Trends
Discuss how you stay current with growth tactics, tools, and industry trends. 'I follow Andrew Chen's blog and listen to the Growth Marketing Podcast.' More importantly, show that you apply what you learn: 'I learned about viral loops, designed an experiment to test one, and it improved our referral rate by 15%.' Demonstrate active learning, not passive consumption.
Growth Portfolio Management
Focuses on managing a balanced portfolio of growth initiatives across multiple time horizons and risk profiles. Topics include distinguishing core optimization work from exploratory projects and strategic bets, allocating resources and engineering capacity across those buckets, defining portfolio level metrics and success criteria, applying risk adjusted prioritization and sequencing, constructing roadmaps that preserve optionality, and governance to track and reallocate investment as results come in. Candidates should be able to explain frameworks used to balance short term impact and long term growth, how to handle dependencies, and how to measure portfolio health.
Result Interpretation & Decision Making
Learn to interpret experiment results: 'This is statistically significant. Should we ship it?' Consider practical significance (is the improvement large enough to matter?), business impact (does it align with goals?), and risks (could it have negative second-order effects?). Practice decision frameworks: ship if significant and directionally positive? Roll out gradually to de-risk? Run additional confirmatory experiments?
Apple Ecosystem and App Store Dynamics
Practical knowledge of how the Apple platform and application store mechanics affect discovery, measurement, monetization, and product choices. Topics include application store search and ranking factors, application store optimization best practices, the impact of App Tracking Transparency on targeting and measurement, privacy preserving attribution and analytics approaches, subscription and in application purchase design, operating system feature integration that drives engagement, developer reporting and tooling, and platform policy and review considerations. Candidates should be able to recommend tactics that increase visibility and engagement on Apple platforms while remaining compliant with platform rules and brand expectations.
Company and Product Specific Growth Assessment
Demonstrate you've researched the company's growth metrics, market position, competitive landscape, and growth stage. Discuss how you'd assess their current growth constraints and what you'd prioritize if hired. Show thoughtfulness about their specific situation.