Analyst Skill Stack

Christoph Janz outlines five distinct strategies for building a $100M company, ranging from enterprise (elephants) to consumer (flies). He analyzes pricing models, customer acquisition, and go-to-market approaches to help founders identify their optimal growth path. A foundational read for SaaS entrepreneurs and startup operators.

This article presents the first level of the Hierarchy of Marketplaces framework, focusing on creating user happiness and scalable engagement. Tavel draws on real examples to show how leading marketplaces like Etsy and Airbnb progressed through each level. Useful for marketplace builders aiming for long-term defensibility.

Tavel extends her original framework to highlight how companies can build products that retain users over time. She categorizes engagement loops and stresses the importance of value creation at each step. Highly relevant for product managers and growth teams focused on long-term user engagement.

This post by A16Z outlines the most important KPIs for two-sided marketplaces. Metrics include match rate, take rate, market depth, and concentration of supply. It offers a rigorous diagnostic toolkit for founders, investors, and operators looking to assess or pitch marketplace startups.

Jamie Sullivan and Alex Immerman use data from 60+ public tech companies to explain how each turn of the LTV:CAC ratio flows through to margins, reinvestment capacity, and ultimately valuation. A clear, numbers-backed argument for why every startup needs to understand their unit economics.

Mina Mutafchieva explains how unit economics can serve as a diagnostic tool rather than just a reporting metric. She shows how to analyze customer cohorts, align spend with ROI, and avoid common pitfalls like cost-cutting without insight. Packed with real-world boardroom questions and frameworks.

Understanding unit economics is essential for analytics professionals in SaaS and product-driven businesses. This post emphasizes how focusing on granular, per-customer profitability metrics can outlast vanity growth metrics, providing a more sustainable view of business performance. By mastering techniques to analyze customer acquisition costs, lifetime value, and other unit-level metrics, analysts can uncover crucial insights to inform strategic decision-making and drive long-term success.

Understanding the business context behind data is essential for analytics professionals to deliver impactful insights. By exploring the interconnected factors shaping the organization's operations and objectives, analysts can uncover meaningful patterns and make informed recommendations that drive strategic decision-making. This holistic approach empowers product, marketing, and revenue teams to optimize their strategies and achieve tangible business results.

Designing effective metrics trees is a crucial skill for analytics professionals who need to extract meaningful insights from complex data. This blog post delves into the techniques and strategies for structuring your metrics in a hierarchical, intuitive manner, enabling you to uncover hidden patterns, identify key drivers, and present data-driven recommendations that resonate with stakeholders across your organization.

Discover the hidden root cause of your analytics woes and unlock unprecedented insights with this insightful guide. Learn proven techniques to diagnose and address the underlying issues that plague your data analysis, empowering you to make data-driven decisions with confidence across marketing, product, and business domains. This essential resource equips analytics professionals with the skills and strategies needed to transform their data into actionable intelligence and drive meaningful impact within their organizations.

Uncover the rare and highly sought-after data skills that set top analytics professionals apart. Dive into cutting-edge techniques and tools that enable deeper insights, predictive modeling, and data-driven decision-making – empowering data analysts, business analysts, and data scientists to drive transformative results for their organizations. Elevate your data mastery and unlock the keys to becoming an indispensable asset in today's data-driven business landscape.

A guide to using four causal analysis techniques to measure the contribution of product features and marketing initiatives to key business metrics and KPIs. Covers experimental design, quasi-experimental methods, propensity scoring, and causal graphs to establish causality and quantify feature impact.

Explores the concept of customer lifetime value (LTV), including how to calculate it, the importance of retention and margin in driving LTV, and using LTV as a key metric for making data-driven business decisions.

This article provides an in-depth overview of the key SaaS metrics that founders need to understand when preparing for fundraising. It covers critical areas like revenue recognition, unit economics, customer lifetime value, and growth metrics - all essential for showcasing the health and potential of a SaaS business to investors.

This article discusses the importance of measuring incrementality and causal impact in marketing campaigns, rather than relying solely on ROAS. It covers methods like geo-split tests, hold-out audiences, and ghost ads to establish true lift and isolate the causal effect of marketing investments.

Understand key SaaS metrics that influence profitability, such as recurring revenue, churn, and the 'triangle of despair' - the balance between customer acquisition, retention, and revenue growth.

Techniques for measuring and forecasting the lifetime value of customers, including retention curves, discount rates, cohort LTV, and probabilistic vs. deterministic LTV models. Linking LTV to other key metrics like CAC and LTV:CAC ratio to assess the efficiency of the business model.

Build your experimentation system to get new insights at a fast pace. Kickstart the compounding effect that will generate long term business outcomes and customer value.

Calculating the gross-margin contribution of a customer over their expected lifetime; including retention curves, discount rates, cohort LTV, probabilistic vs. deterministic models, and segment-level LTV comparison.

This article provides an in-depth look at how WeTransfer leveraged a custom growth model to predict marketing ROI and identify their biggest revenue opportunities. It covers the process of building the growth model, how it was used by the product and marketing teams, and the key insights and results that were uncovered.

This article discusses how BBC Studios utilizes geo holdouts and causal inference techniques like Propensity Score Analysis (PSA) to accurately measure the marketing impact of their campaigns. It provides a detailed overview of the methodologies and challenges involved in conducting rigorous lift tests to establish causality.

An in-depth look at the technical and analytical considerations around revenue recognition, such as aligning with ASC 606/IFRS-15 rules, handling multi-element allocations, and analyzing ratable vs. point-in-time recognition patterns. Explores how to build revenue waterfalls, cohort aging tables, and other financial reporting to ensure data integrity and accounting compliance.

Discusses key metrics and analytical techniques for understanding customer retention, churn, and expansion drivers. Covers topics like logo vs. dollar churn, net revenue retention (NRR), cohort-based survival analysis, and identifying expansion opportunities through upsell and cross-sell.

Foundational concepts and best practices for defining, categorizing, and documenting key performance indicators (KPIs) and other business metrics. Covers the taxonomy of leading vs. lagging, input vs. output, and actionable vs. vanity metrics, as well as establishing naming conventions and a single source of truth for metric definitions.

Covers key revenue metrics for marketplace businesses, including gross vs. net revenue, recurring vs. non-recurring, bookings vs. billings, and other accounting-aligned measures. Explores cohort analysis, revenue waterfalls, and drivers of expansion and churn.

Analyzing the gross-margin contribution of a customer over their expected lifetime, including retention curves, discount rates, cohort LTV, and probabilistic vs. deterministic models. Understanding how to leverage LTV to optimize customer acquisition and inform revenue forecasting.

A comprehensive guide on designing and implementing an in-house feature flagging and A/B testing platform for managing product rollouts, experiments, and user segmentation at scale.

An in-depth look at how to calculate, analyze, and leverage customer lifetime value (LTV) - a critical SaaS metric for understanding the long-term value of customers and optimizing acquisition and retention strategies.

Overview of key performance indicator (KPI) fundamentals, including definitions of leading vs. lagging, input vs. output, and actionable vs. vanity metrics. Discusses best practices for creating a consistent metric taxonomy and documentation.

Methodologies for calculating and understanding the lifetime value of customers, including retention curves, discount rates, cohort LTV, and using LTV to evaluate the efficiency of customer acquisition.

This article discusses key unit economics and efficiency metrics for SaaS businesses, including CAC payback, LTV:CAC ratio, contribution margin, and the rule-of-40. It explains how to calculate and analyze these metrics to understand the underlying profitability drivers and unit-level economics of the business.

This article discusses the data-informed product cycle, which involves translating high-level strategy into models, testing hypotheses, and iterating based on data. It covers key topics like freemium, free trials, usage-based pricing, activation metrics, and product-qualified leads (PQLs).

This article argues that powerful ideas, even if imperfectly measured, are more useful for business decision-making than perfect measures for less impactful ideas. It discusses the importance of focusing on high-leverage metrics and acknowledging the limitations of data, rather than getting overly bogged down in pursuit of perfect measurement.