A/B Testing

Where A/B Testing belongs

A/B Testing sits in the Marketing layer of LuperIQ and focuses on Experiment management with statistical significance testing and AI-powered optimization. For a site owner, the practical value is not the module name by itself; it is whether Experiment creation and management, Variant allocation and traffic splitting, and Statistical significance testing becomes easier to manage in the real customer or admin path.

For pricing and setup, the useful context is Free and Pro and the place the owner will likely manage it is Marketing. Those details help the reader understand the module without turning the page into a technical inventory.

Setup checks for A/B Testing

• Verify that "Experiment creation and management" is represented in the live setup before treating A/B Testing as ready for customers or staff.
• Verify that "Variant allocation and traffic splitting" is represented in the live setup before treating A/B Testing as ready for customers or staff.
• Verify that "Statistical significance testing" is represented in the live setup before treating A/B Testing as ready for customers or staff.
• Verify that "Conversion tracking per variant" is represented in the live setup before treating A/B Testing as ready for customers or staff.
• Verify that "AI-powered optimization suggestions" is represented in the live setup before treating A/B Testing as ready for customers or staff.
• Open the Marketing admin section during setup so the owner knows exactly where this module is managed after launch.

Dependencies and AI connections

A/B Testing works best when Customer Journey are already understood, because those surrounding tools shape where the data, settings, or customer actions will land.

A/B Testing currently connects to A/B Experiment Suggestion, A/B Result Analysis, and A/B Variant Generator in the public AI workflow catalog, which gives this module a clearer next step for owners who want AI-assisted work around the same operational area.

• Related workflow: A/B Experiment Suggestion uses 3 credit(s) and lives under Experimentation & CRO.
• Related workflow: A/B Result Analysis uses 2 credit(s) and lives under Experimentation & CRO.
• Related workflow: A/B Variant Generator uses 2 credit(s) and lives under Experimentation & CRO.