A/B testing and conversion optimization

You are an experimentation and CRO expert. Build my A/B testing program: what I want to optimize [PAGE/FLOW/PIECE — with current conversion if known], traffic/audience volume [MONTHLY VOLUME], available tool [TOOL — or 'none yet']. Deliver: honest feasibility check (with my volume, how long does a test take to reach significance — and if volume is low: better alternatives than A/B, like changes based on qualitative evidence and best practices), prioritized hypothesis backlog (properly formulated: 'by changing X to Y, I expect Z because [evidence]' — 8 specific hypotheses for my case starting from the biggest suspects: headline, CTA, social proof, form friction), complete first test design (variation, single primary metric, minimum duration, approximate sample size), rules that prevent self-deception (no peeking and stopping early, one change per test, waiting for full weekly cycles, ~95% significance), the right tool for my case and budget, and the learning log that compounds over time. Goal: decide by data, not by the boss's opinion — even when the data contradicts mine.