The Channel Expansion Paradox: When Making Calls Easier Doesn't Hurt Digital
Making phone calls dramatically easier should cannibalize digital enrollments. A non-inferiority test on an energy provider's landing page proves otherwise.
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Writing · Lean Experiments
Revenue-First
Revenue-First
Experimentation
Practical A/B testing frameworks, behavioral science, and conversion optimization — for growth leaders responsible for revenue.
The Uncomfortable Truth About Scaling Experimentation: Why Running More Tests Makes You Worse
Teams double their experiment volume and cut their learning rate in half.
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The Address the System Did Not Recognize
When a major energy retailer tightened address lookup logic, manual entry jumped sharply. The test looked flat. The signal was a trust collapse.
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Flat Primary Metric, Positive Downstream: A Framework for the Hardest Shipping Decision in CRO
Your primary metric did not move. Your secondary metrics improved. Behavioral analytics look good. Do you ship? Here is the decision framework.
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The Privacy Override: How Benefit Framing Defeats the Default to Withhold
Why people instinctively withhold sensitive data — and how one copy-only test at a utility provider used benefit framing to override that instinct.
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The Form Chunking Illusion: Why Faster Steps Still Lose Users
Form chunking reduces per-page exit rates but creates new drop-off points at every transition.
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The Guarantee Nobody Saw: Risk Reversal Psychology and the Commitment Gap
A satisfaction guarantee only works if people actually see it. This A/B test from a major energy provider reveals why risk reversal messaging works…
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The Complete Taxonomy of A/B Test Results: Why Most Teams Misclassify Half Their Experiments
Most CRO teams use only three labels — Winner, Loser, Inconclusive — and misclassify half their experiments as a result.
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How NRG Scaled to 100+ Experiments with $30M+ in Internal Program Reporting
How NRG scaled from roughly 20 to 100+ annual tests across five brands, with $30M+ in internal program reporting and explicit evidence limits.
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Optimizely Visual Editor Not Working? Here's How to Fix It
Complete troubleshooting guide for the Optimizely visual editor not loading or working.
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Optimizely Snippet Performance: How Much Does It Slow Down Your Site?
The honest numbers on Optimizely's page speed impact — async vs. synchronous snippet, anti-flicker costs, Core Web Vitals effects, and how to measure and…
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Why Your Optimizely Experiment Isn't Showing Visitors (Troubleshooting Guide)
The complete diagnostic guide for Optimizely experiments showing zero or very low visitor counts.
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How to Fix the Optimizely Flicker Problem (FOOC)
The complete guide to diagnosing and fixing Optimizely flicker (Flash of Original Content).
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Optimizely Alternatives: 6 Platforms Worth Considering in 2026
Honest, specific comparison of 6 Optimizely alternatives — VWO, AB Tasty, Statsig, Convert, LaunchDarkly, and GrowthBook — with a decision framework to help…
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10 A/B Tests Every CRO Team Should Run (With Benchmarks)
Not a list of random test ideas. These are 10 high-ROI tests with hypothesis templates, realistic lift benchmarks, and what to test next after a win or a…
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How to Write A/B Test Hypotheses That Actually Lead to Insights
"Let's test a bigger button" is not a hypothesis. Here's the full hypothesis template, 5 bad-to-good rewrites, and how a good hypothesis turns a losing test…
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What Is Statistical Significance in A/B Testing? (Plain-English Explanation)
Most definitions of statistical significance are wrong — or at least misleading.
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How Long Should You Run an A/B Test? (The Definitive Answer)
There's no single number. But there is a rigorous framework. Here's how to calculate exactly how long your A/B test needs to run — and why stopping early is…
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How to Build an A/B Testing Roadmap (That Isn't Just a Feature Wishlist)
Most A/B testing roadmaps fail because they list tests, not hypotheses.
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When to Stop an A/B Test: A Framework That Protects Your Data
Most teams stop A/B tests for the wrong reasons. This framework gives you four conditions to verify before calling a test — and explains the peeking…
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Minimum Detectable Effect (MDE): How to Set It in A/B Tests
What minimum detectable effect (MDE) means, the formula behind it, and how to choose one so your A/B tests aren't underpowered or endless.
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Bayesian vs Frequentist A/B Testing: A Practitioner's Honest Guide
A practical comparison of Bayesian and frequentist A/B testing from a CRO practitioner who's run 100+ experiments.
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Getting Started With Optimizely Web Experimentation: A No-Fluff Setup Guide
The correct Optimizely setup sequence — snippet installation, A/A testing, custom events, naming conventions, and the 5 mistakes that create months of bad data.
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The Optimizely Practitioner Toolkit: Start Here
The front door to the Optimizely Practitioner Toolkit. Find the right learning path based on where you are, avoid the 5 most common mistakes, and access all…
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