Lenny Rachitsky and Dan Hockenmaier argue that every business can be reduced to a simple equation, and that you don't fully understand your business until you can write one. Building the equation forces teams to name…
Olga Berezovsky, guest-writing for Lenny Rachitsky, argues that cohort retention is widely misunderstood and costly to get wrong, and offers a practical guide to measuring it. She recommends defining "active" by the…
Jorge Mazal, former CPO of Duolingo, recounts how the company reversed a slide in daily active user growth and eventually grew DAU about 4.5x over four years. The journey began with failed attempts: a…
“This is just quick email to let you know I wrote a guest post for Future (a16z’s new media site) that I’m pretty excited about. It’s a guide for helping you choose your North Star Metric(s), based on a survey of current and past employees at over 40 of today’s most successful growth-stage companies. Check out the table below for a glimpse of what you’ll find. Your North Star Metric is your strategy, and your strategy is your North Star…”
Lenny Rachitsky compiles the most concrete and actionable definitions of product-market fit (PMF) from leading investors, founders, and operators, organized into signals before a product exists and signals after launch…
The post argues that experiments are usually the right default for product changes, but describes when to skip them. It covers the benefits and downsides of A/B testing, then three cases to ship without testing: when…
Teresa Torres profiles Thomas Groendal, a senior PM at Bluestone Analytics, whose intelligence-analysis products (DarkBlue and DarkPursuit) operate on the dark web with few users, privacy restrictions, and very long…
Teresa Torres argues that product teams should start by defining what success looks like, since a clear goal is the ultimate measure that makes alignment and decisions easier. She warns against drowning in dozens of…
Cagan argues that product optimization, typically A/B testing and iterative tuning, is often confused with product discovery, and that optimization only makes sense after a team has found product/market fit. He…
Lenny Rachitsky answers a reader's question about which metrics matter for a consumer app, arguing the right metrics depend on how the business makes money. He walks through five consumer models (trial-based…
Teresa Torres argues that product teams should treat every idea as a testable hypothesis, which requires explaining why a change matters and how much impact it should produce. Ideas from design, sales, and product…
Teresa Torres argues that the popular "We believe... will result in... we will have confidence when..." hypothesis format is quick but insufficient for sound experiment design. She explains that teams should test the…
Teresa Torres argues that a single A/B test rarely settles a question; instead, teams should string related hypotheses together around one underlying insight. Using an email subject-line example about urgency, she shows…
Teresa Torres argues that as product teams adopt experimentation, their tests are only as good as their hypotheses and experiment design, so poor setup wastes money, time, and sprints. She lists fourteen common pitfalls…
Teresa Torres argues that choosing product themes is not enough; teams also need a way to predict and measure how each user story moves the product goal. Using an event-site example with the goal of increasing the…
Guest author Olga Berezovsky explains the difference between correlation and linear regression analysis for product teams. Correlation measures how strongly two variables move together on a scale from -1 to 1, and is a…
Teresa Torres reviews Lean Analytics by Alistair Croll and Ben Yoskovitz and argues it is an essential, accessible guide to product and startup analytics. She notes it covers the basics of good metrics and segments…
Teresa Torres argues that many teams run A/B tests without first knowing what they are trying to learn, which produces wasted effort and unclear results. Before testing, a team should define a specific hypothesis and…
Teresa Torres argues that product leaders need only a basic grasp of statistics to avoid being misled by A/B tests. She explains statistical significance using a conversion example and warns that many web testing tools…
Marty Cagan argues that many product teams still fly blind because they do not instrument their products to collect usage analytics, or collect so little that they cannot see how customers actually use features. He…
Teresa Torres recounts advising a junior designer who wanted to grow in user experience design. She argues that hands-on learning matters more than reading or talking, and that the designer's best growth opportunity is…
Lenny answers a reader question by unpacking how Airbnb built a strong experimentation culture, using its early data science hires, north-star metric, embedded data scientists, and trustworthy tooling as the core story…
Torres argues that all-time totals, like lifetime registered users, are rarely useful because they only go up and hide whether a product is improving or declining. The right measure depends on choosing a time increment…
Aman Khan argues that writing evaluations is becoming a defining skill for AI product managers, since evals measure how each part of a system affects quality. The post explains what evals are, compares human, code-based…