ab-testing Apr 7, 2026 9 min read
How to A/B Test Pricing Page Anchors Without Losing Trust
A pricing page can raise revenue or quietly poison trust. I've seen both happen from changes that looked minor.
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Lean Experiments · Blog
Revenue-First
Revenue-First
Experimentation
Practical A/B testing frameworks, behavioral science, and conversion optimization — for growth leaders responsible for revenue.
ab-testing Apr 7, 2026 8 min read
Anchoring Bias Tests for SaaS Pricing Pages
The biggest pricing-page mistake I see isn't bad math. It's showing prices with no frame around them.
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ab-testing Apr 7, 2026 8 min read
How to Use Prospect Theory in Pricing Page Tests
Most pricing page tests fail for a simple reason: teams treat pricing strategy like math, while buyers treat it like psychological pricing. On the page, people rarely ask, "What's the optimal plan?" They ask, "Compared with what, and what do I lose if I choose wrong?"
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ab-testing Apr 7, 2026 7 min read
How Decoy Effect Pricing Changes Choice on Pricing Pages
Ever watched buyers stare at two plans, then leave? I have, and it's usually not because both plans are bad. It's because the page makes the choice feel hard.
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ab-testing Apr 7, 2026 8 min read
How To Use Price Anchoring On SaaS Pricing Pages Without Tricking Buyers
Your pricing page is not where buyers start thinking about price. It's where they compare.
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ab-testing Apr 7, 2026 7 min read
SaaS Pricing Page Testing Ideas That Lift Paid Signups
Most pricing page tests die for a simple reason, they chase clicks instead of cash. When I work on saas pricing page testing, I care less about a prettier page and more about whether more visitors become paid users.
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experimentation-culture Apr 7, 2026 11 min read
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. Here is what actually breaks when experimentation programs scale — and why the real problem is cognitive, not mechanical.
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experimentation Apr 7, 2026 9 min read
How I Built a $30M Experimentation Program in a Year
Atticus Li shares how he scaled NRG Energy's experimentation program from 20 tests per year to 150+ total experiments across 7 brands, tying every test to revenue per customer and generating over $1.2M in projected annual lift.
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optimizely Mar 31, 2026 8 min read
Optimizely Visual Editor Not Working? Here's How to Fix It
Complete troubleshooting guide for the Optimizely visual editor not loading or working. Covers the 6 most common causes — Chrome extension issues, CSP/X-Frame-Options, HTTPS mismatches, SPA timing, JavaScript conflicts, and missing snippet.
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optimizely Mar 31, 2026 8 min read
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 minimize the actual performance hit.
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optimizely Mar 31, 2026 7 min read
Why Your Optimizely Experiment Isn't Showing Visitors (Troubleshooting Guide)
The complete diagnostic guide for Optimizely experiments showing zero or very low visitor counts. Covers the 7 most common causes with exact debugging steps for each.
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optimizely Mar 31, 2026 7 min read
How to Fix the Optimizely Flicker Problem (FOOC)
The complete guide to diagnosing and fixing Optimizely flicker (Flash of Original Content). Covers all four fix types, performance tradeoffs, and a 3-step diagnostic to identify which fix you actually need.
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optimizely Mar 31, 2026 8 min read
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 you pick the right tool for your team.
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ab-testing Mar 31, 2026 16 min read
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 loss — built from 100+ experiments at NRG Energy.
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ab-testing Mar 31, 2026 11 min read
A/B Testing vs Multivariate Testing: When to Use Each
A/B testing and MVT are not interchangeable. The difference between them — interaction effects, traffic requirements, and what you actually learn — determines which one you should run. Here's the framework.
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ab-testing Mar 31, 2026 12 min read
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 into your next win.
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ab-testing Mar 31, 2026 11 min read
What Is Statistical Significance in A/B Testing? (Plain-English Explanation)
Most definitions of statistical significance are wrong — or at least misleading. Here's what p < 0.05 actually means, why 95% confidence is a convention not a law, and how to avoid the significance theater killing your CRO program.
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ab-testing Mar 31, 2026 12 min read
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 the most expensive mistake in CRO.
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ab-testing Mar 31, 2026 11 min read
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. This guide covers the four roadmap categories, ICE scoring, sequencing strategy, and what a mature 90-day roadmap actually looks like.
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ab-testing Mar 31, 2026 10 min read
A/B Test Sample Size Calculator: How to Use It (And Why Teams Get It Wrong)
A practical guide to A/B test sample size calculations, with worked examples, common mistakes, and what to do when your traffic is too low. Covers multiple variations, MDE sensitivity, and how to avoid the '2-week arbitrary duration' trap.
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ab-testing Mar 31, 2026 10 min read
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 problem, sequential testing, and what 'results stabilized' actually means.
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ab-testing Mar 31, 2026 9 min read
Minimum Detectable Effect in A/B Testing: The Number That Determines Everything
MDE is the most underrated concept in A/B testing. Get it wrong and you'll run underpowered tests for months. This guide covers MDE calculations, real benchmarks by test type, and how to frame it as a business decision.
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ab-testing Mar 31, 2026 8 min read
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. Covers the peeking problem, sequential testing, and a decision table for choosing the right approach.
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optimizely Mar 31, 2026 8 min read
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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