Articles exploring cro through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
8 articles
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.
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.
"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.
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.
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 24 practitioner guides organized by cluster.
Most testing roadmaps are just feature wishlists. Here's how to build a real experimentation roadmap—with prioritization frameworks, sequencing logic, and stakeholder buy-in tactics that keep the program moving.
"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 lose—with 5 real rewrites and a hypothesis library framework.
Not all A/B tests are equal. Here are 10 experiments with tight behavioral hypotheses, realistic lift expectations, and the exact failure modes to watch out for — plus 3 bonus tests the standard lists always miss.