Why 95% Confidence Isn't Always Enough (And When to Use 99%)
A deep dive into statistical significance thresholds, false positive rates, and when raising the bar from 95% to 99% confidence is worth the extra sample size.
Read Article →Practical insights on A/B testing, design optimization, CRO strategy, and building data-driven design teams.
Everything you need to know about running rigorous design experiments — from hypothesis formation to statistical analysis. Includes 15 test templates, sample size calculator, and a results documentation framework.
Read Full Article →A deep dive into statistical significance thresholds, false positive rates, and when raising the bar from 95% to 99% confidence is worth the extra sample size.
Read Article →We analyzed 200+ CTA tests across the Desig platform. Here are the copy patterns that most reliably outperform generic button text.
Read Article →How to use A/B test learnings to build audience segments and eventually serve personalized experiences at scale — without losing statistical rigor.
Read Article →The companies that win at optimization run more tests, not just better tests. Here's how to build the culture, processes, and buy-in needed for 4+ tests per month.
Read Article →Heatmaps aren't just for looking at where users click — they're a goldmine of test ideas. Learn how to translate heatmap data into prioritized, high-impact test hypotheses.
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