Glossary
CRO & eCommerce glossary
Every term explained — conversion rate optimization, A/B testing, retention metrics, and eCommerce growth. No jargon, just clear definitions.
A
A/B Testing A controlled experiment comparing two versions of a page or element to determine which performs better. The gold standard for data-driven optimization. Average Order Value (AOV) The average dollar amount spent per transaction. Increasing AOV is one of three core levers for eCommerce revenue growth alongside conversion rate and traffic. AXR Score Acceleroi's prioritization framework — Actionability × eXpected Revenue × Resources. Ranks every optimization opportunity by revenue per hour invested.
C
Cart Abandonment When a shopper adds items to their cart but leaves without completing the purchase. The average rate is ~70% — reducing it is one of the fastest paths to revenue growth. Confidence Interval The range within which the true conversion rate likely falls. A narrow interval means more precise measurement; a wide interval signals the need for more data. Conversion Funnel The series of steps a visitor takes from first interaction to completing a goal. Understanding where users drop off reveals the highest-impact optimization opportunities. Conversion Rate The percentage of visitors who complete a desired action. The foundational metric of CRO — everything else builds on understanding and improving this number. CRO Audit A systematic evaluation of a website's conversion performance using analytics data, heuristic analysis, user research, and technical review to identify optimization opportunities. Customer Lifetime Value (LTV) The total revenue a customer generates over their entire relationship with your brand. The metric that determines how much you can profitably spend to acquire a customer.
M
Macro-Conversion The primary conversion goal — a completed purchase, signed contract, or subscription. The ultimate metric your CRO program optimizes toward. Micro-Conversion A small step that indicates progress toward a primary conversion goal — email signup, add-to-cart, video play, PDF download. Leading indicators of macro-conversion health. Minimum Detectable Effect (MDE) The smallest improvement an A/B test is designed to detect. Setting MDE too low requires impractically large sample sizes; too high risks missing meaningful wins. Multivariate Testing (MVT) Testing multiple variables simultaneously to understand how different combinations of elements interact. More complex than A/B testing but reveals interaction effects.
S
Sample Size The number of visitors needed in an A/B test to detect a statistically significant difference. Running tests without adequate sample size produces unreliable results. Statistical Significance The probability that an observed difference between test variations is not due to random chance. Typically set at 95% confidence for CRO experiments.