Know what to test, when to trust the result, and what to do next. Practical guides for analysts, growth teams, and founders.
Nike didn't win sports by accident. They built a $165B brand by stacking three well-documented behavioral biases — Authority Bias (Milgram, 1961)…
B.F. Skinner's 1957 pigeon experiments on variable reinforcement built every slot machine in Las Vegas.
In 1980, Kmart was ten times bigger than Walmart. By 2002 Kmart was bankrupt.
When a measure becomes a target, it stops being a useful measure. The Cobra Effect is the most colorful illustration of Goodhart's Law — but Wells Fargo's…
Most marketing copy is bad in ways that are research-documented. Present tense beats past tense (Packard, Berger, Boghrati 2023).
In 2009, two Domino's employees nearly destroyed the brand with a viral YouTube video. CEO J.
In 1927, a Russian psychology student watched German waiters in a Berlin restaurant and noticed something strange.
Most behavioral economics blogs give you a list of 17 cognitive biases ruining your conversion rate. The real number is three.
Victor Gruen designed the world's first enclosed shopping mall, then spent fifteen years trying to disown it.
The single most important paper in modern behavioral economics is about colonoscopies.
In 1996, an American who didn't speak French and didn't drink vodka set out to build the world's most expensive vodka brand.
Something interesting happened quietly in a recent ad platform API release: experiment statistics got pulled directly into the same reporting layer as
Most teams treat the moment a test hits significance like a gun going off at the end of a race. The experiment reaches p<0.
Most stakeholder-submitted hypotheses describe a goal ("make X clearer") instead of an intervention.
There's a moment in most experimentation programs when volume becomes the goal. The team hits a rhythm. The tooling is set up.
A bare point estimate is uninterpretable. This guide walks through the 5 elements that should appear on every test readout — power analysis, MDE, confidence…
Five statistical mistakes that derail new DTC testing teams, with practical checks for sample size, peeking, metrics, and interpretation.
A five-step method for learning from CRO case studies without mistaking curated success stories for representative evidence.
A plain-English guide to why selected extreme A/B test results often shrink, and why no universal discount can recover the true effect.
How outcome-dependent stopping changes A/B test error rates, why there is no universal peeking multiplier, and how to precommit a valid stopping rule.
The standard 3-tier pricing-page playbook — anchor + decoy + "Most Popular" badge — works under specific conditions. Here are the ones that break.
Dark patterns optimize for the next quarter. Bright patterns optimize for the next decade. The 12 alternatives, and why your A/B test will misjudge them.
Princeton found dark patterns on 11% of shopping sites. The FTC, EU, and California now regulate them. The 12-pattern taxonomy and what each costs you.
Krug's usability principles still hold — but the cost of misapplying them now compounds in places dashboards cannot see. The complete Krug-2026 reading list.
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