Practical A/B testing frameworks, behavioral science, and conversion optimization — for growth leaders responsible for revenue.
Analysis of 13 mobile A/B tests reveals a 38% win rate, beating desktop. Learn why device-specific testing matters more than responsive design alone.
97 real A/B experiments tested behavioral science principles in the field. Here is what actually worked, what failed, and a prioritization framework for practitioners.
Most companies quantify testing costs but never calculate what NOT testing costs. The Experiment P&L framework reveals the true economics.
19 A/B tests on product comparison pages reveal layout structure beats content additions, attribute curation drives decisions, and interactive builders outperform static tables.
Learn how CUPED (Controlled Experiment Using Pre-Experiment Data) and other variance reduction techniques can cut your A/B test duration by 20-50% without sacrificing statistical rigor.
A practical guide to A/B testing across the e-commerce funnel — from category pages to checkout. Learn which metrics matter, where to focus tests, and why RPV beats conversion rate.
Learn why aggregate A/B test results hide the truth. Master segmentation analysis, understand heterogeneous treatment effects, and avoid the segment fishing trap.
Feature flags and A/B tests are complementary tools, not substitutes. Learn why rolling out a feature to 10% of users is NOT the same as running an experiment.
From Obama's $60M fundraising lift to modern campaign optimization, political A/B testing is a masterclass in high-stakes, time-constrained experimentation that every product team can learn from.
A/B testing isn't free. Learn the real costs — opportunity cost, engineering resources, decision delay — and develop the judgment to know when shipping fast beats measuring precisely.
Learn how to test pricing without the ethical and brand risks of showing different prices to different users. Test the pricing page, the framing, and the structure — not the number.
Standard A/B testing breaks when users influence each other. Learn about interference, network effects, and how platforms like LinkedIn and Uber solve experimentation at scale.
A/B tests, multivariate tests, and bandit algorithms each solve different problems. Learn when to use each method based on your traffic, goals, and what you need to learn.
Generic onboarding flows force diverse users through identical experiences, losing those who don't see immediate relevance. Learn how personalized onboarding paths dramatically improve activation across segments.
Empty states are the most overlooked conversion opportunity in product design. Learn how to transform blank screens into activation engines using behavioral science principles.
Social proof during onboarding transforms uncertain new users into confident adopters. Learn how to strategically deploy testimonials, usage data, and peer evidence to accelerate activation.
The first 5 minutes of product usage determine whether users become power users or churned statistics. Learn the behavioral design patterns that shape lasting first impressions and drive product adoption.
Front-loading your entire product's complexity into the first session is the fastest way to lose users. Learn why progressive onboarding aligned with learning theory dramatically improves activation.
Time-to-value is the hidden variable that determines whether users activate or abandon. Learn how to measure, optimize, and compress the gap between signup and first meaningful outcome.
The ultimate product goal is not just activation but habit formation. Learn how behavioral psychology's habit loop, variable rewards, and identity attachment create products that become indispensable.
Onboarding checklists exploit deep psychological patterns around task completion, the Zeigarnik effect, and endowed progress. Learn why they work and how to design them for maximum activation.
Trace A/B testing from 1835 drug trials through Claude Hopkins' coupon testing to Google running 10,000 experiments annually. Understanding history prevents you from reinventing old ideas.
Not all A/B tests use the same statistics. Learn which test to use for conversion rates, revenue, count data, and small samples — with a practical decision tree.
Nobel laureate Robert Shiller's concept of narrative economics reveals that stories, not data, drive economic behavior. Learn how to apply this principle to brand building, positioning, and growth strategy through the lens of behavioral science.
Practical A/B testing frameworks, behavioral science, and CRO strategies for growth leaders responsible for revenue. Practical. Free. Weekly.
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