Intermediate40 minutesStep 7Pro

Shopify A/B Testing: Priorities, Sample Size, and Stop Rules

Run Shopify CRO through experiment hard rules before A/B testing: low sample is not a formal conclusion, no-peeking means no early stop, MDE / power / baseline CVR must be explainable, and traffic, discount, inventory, payment, speed, and tracking counter-evidence must be cleared before choosing formal A/B, directional validation, qualitative validation, or direct repair.

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Review scope Reviewed against Shopify, Google Search, ads, analytics, and ecommerce operating workflows.

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Run Shopify CRO through experiment hard rules before A/B testing: low sample is not a formal conclusion, no-peeking means no early stop, MDE / power / baseline CVR must be explainable, and traffic, discount, inventory, payment, speed, and tracking counter-evidence must be cleared before choosing formal A/B, directional validation, qualitative validation, or…

A Shopify CRO series for teams with traffic but unstable conversion. Learn funnel roles, PDP trust, collection navigation, cart and checkout friction, landing-page message match, behavior evidence, A/B testing discipline, and monthly CRO roadmaps.

Lesson outline

  1. 1Write one falsifiable hypothesis
  2. 2Decide whether this is an experiment issue
  3. 3Lock one main variable and primary metric
  4. 4Use the Sample Reality Calculator to unpack sample reality
  5. 5Write freeze rules
  6. 6Pre-write readout and stopping discipline
  7. 7Classify readout with the Decision Ledger
  8. 8Write back to notes and monthly roadmap

Public core framework

  • Write one falsifiable hypothesis from behavior evidence or GA4/Shopify breaks.
  • Decide whether this is an experiment issue or a bug, payment, discount, privacy, tracking, or stock issue.
  • Lock one main variable, one primary metric, and no more than two guardrails.

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