hypothesis-generator

To generate a CRO experiment roadmap, you can use a hypothesis generator that transforms L0/L1 context into testable hypotheses with ICE scores, page targets, and audience mapping. It outputs a sequenced roadmap deliverable with prerequisites for execution.

ICE scoring in CRO hypotheses evaluates experiment opportunities based on Impact, Confidence, and Ease. The hypothesis generator applies this framework to prioritize testable hypotheses, producing a sequenced experiment roadmap with scored deliverables.

You create testable CRO hypotheses by applying a library of CRO patterns to existing context to identify opportunities. The generator outputs complete hypotheses with causal reasoning, target pages, before/after variants, and audience mappings.

You do not need web research or data collection for this hypothesis generation process. The generator relies strictly on existing L0/L1 positioning context and CRO patterns, explicitly skipping external data collection to output the experiment roadmap.

Yes, applying CRO patterns to context automatically maps audiences and sequences experiments. The generator identifies opportunities, assigns page targets and audience mappings, and outputs a prioritized roadmap with ICE scores and execution prerequisites.

Automated hypothesis generation for experiment roadmaps does not perform web research or data collection. It relies solely on provided L0/L1 context and CRO patterns, meaning the quality of the output depends entirely on the input context available.