Open this lesson in your favourite AI. It'll walk you through the why, explain the demo, and quiz you on the try-it list.
CRO without a structured loop produces random changes dressed up as optimization — the loop is what separates teams that compound learning from teams that run cosmetic tests and wonder why nothing improves. Every step feeds the next: research surfaces hypotheses, tests validate or refute them, and learning sharpens the next round of research.
Use these three in order. Each builds on the one before.
In one paragraph, explain the CRO loop and why each stage is necessary rather than optional.
Walk me through how a CRO team would execute one full cycle of the research → hypothesis → test → learn loop for a pricing page.
Given a team that runs 20 tests per quarter but sees diminishing returns, how would you redesign their loop to produce higher-quality hypotheses from better research?