Articles exploring decision-making through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
12 articles
The most expensive misreading in A/B testing is treating 'not statistically significant' as 'no difference.' It actually means 'we didn't collect enough evidence.' Here is the 2-word swap that fixes it, the mistake burying your real wins, and why the language trips up smart teams.
Personality tests give you a label. Labels don't change behavior. What works: functional bottlenecks, hard constraints, and feedback loops.
Your AI optimizes for speed, not truth. Here's why it confidently lies about real-time data and the prompting fixes that force verification.
Most non-execution is risk management in disguise. The fix: cut scope until shipping becomes the path of least resistance.
Most recession forecasts fail because they treat deterioration as breakdown. Track income, spending, and credit — ignore everything else.
Smart people build systems that optimize storage instead of throughput. Here's why organization backfires and constraint-based execution wins.
A data analyst's real job is not producing dashboards. It is helping stakeholders make better decisions with data. Here is how analysts should work with experimentation teams, translate data into stories, and earn a seat at the decision table.
Most experimentation advice assumes perfect statistical significance. Here is how to make the best decision when the data will never be complete — a pragmatic framework from 150+ enterprise experiments.
When A/B tests track multiple metrics, statistical complexity increases. Learn frameworks for managing metric conflicts and making sound decisions.
Confidence intervals tell you more than p-values ever could. Learn how to read them, use them for decisions, and avoid the common misinterpretations teams make.
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.
A practical framework for designing three-level metric trees tied to real decisions, financial outcomes, and guardrails that withstand stakeholder pressure.