Practical A/B testing frameworks, behavioral science, and conversion optimization — for growth leaders responsible for revenue.
Skeleton screens, progress indicators, and temporal distortion in digital experiences. How our perception of time waiting shapes satisfaction more than objective milliseconds.
The long-term business cost of manipulative UX: churn, reviews, regulatory risk, and brand erosion. Why ethical persuasion outperforms manipulation over any meaningful time horizon.
Mobile UX beyond responsive design: touch targets, one-handed use patterns, and interruptible flows. Why mobile optimization requires rethinking interaction models, not just layout.
Card sorting, mental models, and how information hierarchy affects both findability and purchase confidence. The hidden economics of navigation design.
The engagement metrics that actually predict conversion: scroll depth, interaction rate, and qualified sessions. Why bounce rate tells you almost nothing useful and what to replace it with.
How grouping users by acquisition date reveals retention, engagement, and revenue patterns invisible in aggregate data. A behavioral lens on why cohorts expose the truth that averages conceal.
Data discrepancies between platforms, the observer effect in measurement, and how to build a single source of truth when every tool tells a different story.
Mean reversion in marketing channels, the diminishing returns curve, and when to trust your model vs. your gut. Why the past is an increasingly unreliable guide to the future in growth.
Why tracking plans fail, how naming conventions compound, and the hidden cost of retrofitting analytics. The architectural decisions that determine whether your data is an asset or a liability.
You study users who entered the funnel but ignore those who never started, creating systematically wrong conclusions about where to invest optimization effort.
The fundamental measurement problem in digital marketing and why all models are wrong but some are useful. An exploration of attribution through the lens of behavioral economics and epistemology.
Why pageviews, followers, and time-on-page are seductive but misleading without context. A behavioral science framework for distinguishing metrics that inform decisions from metrics that merely comfort.
Demystify A/B testing statistics — p-values, confidence intervals, Type I and Type II errors, and one-tail vs two-tail tests explained in plain English with business context.
The Elaboration Likelihood Model applied to copy length decisions based on product type, price point, and user intent. Why the length debate misses the point entirely.
The Elaboration Likelihood Model applied to copy: high-involvement users need substance, not sizzle. Why emotional power words backfire when the decision stakes are high.
How word-level decisions in UI copy trigger or suppress action through cognitive fluency, loss framing, and autonomy. The behavioral science behind microcopy that moves conversion metrics.
Why specificity, similarity, and narrative social proof outperform generic numbers. The psychology of social proof copy that moves conversion metrics instead of just filling space.
The cognitive bias where deep product knowledge makes it impossible to write from the user's perspective. Why the people who know a product best are systematically the worst at explaining it.
Flesch-Kincaid meets conversion data: cognitive load theory applied to marketing copy. Why the smartest companies write at a sixth-grade reading level and convert better because of it.
Brand voice as a trust signal through mere exposure and processing fluency. How systematic voice consistency reduces cognitive friction and builds the familiarity that drives conversion.
Attentional capture, novelty detection, and the information gap theory applied to headlines. The neural mechanisms that determine whether your headline gets read or ignored.
Higher experiment velocity compounds learning and growth, but only if quality is maintained. Learn frameworks for increasing testing speed through better prioritization, parallel testing, and organizational maturity.
Incremental A/B testing can trap your product at a local maximum. Learn the difference between exploitation and exploration, and why the most successful optimization programs balance small tweaks with bold, transformative experiments.
An A/A test pits two identical experiences against each other to validate your experimentation infrastructure. Learn what surprising A/A results reveal about the limits of significance testing and how to use them to calibrate your program.
Practical A/B testing frameworks, behavioral science, and CRO strategies for growth leaders responsible for revenue. Practical. Free. Weekly.
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