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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Make Growth Decisions
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Know what to test, when to trust the result, and what to do next. Practical guides for analysts, growth teams, and founders.
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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How Optimizely Counts Conversions (And Why It Changes Your Results)
Visitor-based vs session-based conversion counting, the exact math showing how it changes your reported rate, unique vs all conversions, how to audit your…
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Ratio Metrics, Revenue Metrics, and Conversion Metrics in Optimizely: When to Use Each
The three Optimizely metric types explained for practitioners — when revenue per visitor beats revenue per purchase, the variance problem with revenue…
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Choosing the Right Primary Metric for Your A/B Test
Why you can only have one primary metric, how to choose it correctly, why revenue per visitor usually beats CVR alone, and how metric selection affects test…
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URL Targeting vs Audience Targeting in Optimizely: What's the Difference?
The exact technical difference between URL targeting and audience targeting in Optimizely, when to use each, wildcard patterns, regex examples, and the most…
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Audience Conditions in Optimizely: A Practical Guide to Targeting
A practitioner-level guide to Optimizely audience conditions — AND/OR logic, cookie targeting, dynamic evaluation timing traps, and why your audience is…
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How to Build an Experimentation Roadmap That Actually Gets Used
Most testing roadmaps are just feature wishlists. Here's how to build a real experimentation roadmap—with prioritization frameworks, sequencing logic, and…
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Metrics by Revenue Model: What to Measure Based on Your Business Type
"Conversion rate" means completely different things for an ecommerce site vs. SaaS vs. media company.
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How to Share A/B Test Results With Stakeholders (Who Don't Care About P-Values)
Your CEO doesn't care about statistical significance. Here's the one-page results template, the revenue translation formula, and how to handle every awkward…
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How to Write A/B Test Hypotheses That Don't Suck
"Let's test a bigger CTA" is not a hypothesis. Here's the exact structure for writing A/B test hypotheses that produce useful results whether they win or…
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Why Optimizely Data Doesn't Match Google Analytics (And How to Fix It)
Optimizely and GA4 will never show identical numbers — and that's expected.
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When to Stop an A/B Test (And Why 95% Confidence Isn't Enough)
Stopping rules for A/B tests: what 95% confidence does and doesn't guarantee, the peeking trap, and how to call a test without wrecking your data.
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Segmenting A/B Test Results in Optimizely: Where the Real Insights Hide
The top-line result is often a lie. This guide shows you how to segment Optimizely results correctly, which segments actually matter, and how to avoid the…
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How to Read Your Optimizely Results Page (A Complete Walkthrough)
A practitioner's guide to every element on the Optimizely results page — what it means, what to check first, and how to avoid the most common misreads that…
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How to Run an A/A Test in Optimizely (And What It Actually Tells You)
Most teams skip A/A tests and only realize the mistake after shipping a 'winner' that quietly reverses.
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