CRO Glossary

Understand abandoned carts, key causes, and practical strategies to reduce cart abandonment, improve checkout flow, and recover more sales.

Adaptive content helps websites deliver the right message to the right user by adapting content based on context, behavior, and device.

Discover how to improve Add to Cart performance with UX tactics, button best practices, and optimization tips that boost conversions in any online store.

An agile CMS helps teams create, manage, and deliver content faster across channels using modular content, workflows, and API-first delivery.

Discover what annual recurring revenue is, how it’s calculated, and how SaaS companies use ARR to drive predictable, long-term subscription growth.

Annual subscription explained: benefits, pricing strategies, examples, and when annual vs monthly plans make sense for businesses and customers.

An attribution window defines how long ads can receive credit for conversions. Learn how different windows work, why platforms disagree, and how to choose the right setup.

An attribution window defines how long ads can receive credit for conversions. Learn how different windows work, why platforms disagree, and how to choose the right setup.

ARPU reveals how much value each user contributes and exposes the patterns, segments, and behaviors that truly drive a company’s revenue.

Behavioral triggers personalize experiences by responding to real user behavior, reducing friction, and guiding visitors toward conversion.

Bucket testing explained: how to compare two versions, improve conversion rates, and make data-driven decisions with confidence.

Canary testing releases new features to a small user group first, helping teams detect issues early before a full rollout and reduce deployment risk.

Improve your checkout conversion rate with actionable tips to reduce abandonment, streamline checkout, and boost conversions for your online store.

A clear guide to click maps—what they show, how users click and scroll, and how this insight improves page layout, UX decisions, and conversion performance.

Cohort analysis reveals how user behavior changes over time, helping teams improve retention, engagement, and long-term performance.

Stop guessing in experiments. Understand confidence levels, confidence intervals, and how to choose the right threshold for reliable CRO decisions.

More than a receipt, a confirmation page is a strategic touchpoint that reassures customers, clarifies next steps, and strengthens the post-purchase experience.

A CRO test helps you improve conversion rates by comparing page variations, analyzing user behavior, and making data-driven decisions that drive growth.

A downsell offers a lower-priced alternative when customers hesitate on a premium option. Learn how to use downsells to prevent lost sales, increase conversions, and guide buyers toward long-term value.

An experimentation framework is a structured system for testing hypotheses, collecting reliable data, and making evidence-based product decisions.

Feature tests assess new functionality in controlled conditions to verify performance, stability, and user impact before full release.

Funnel testing helps optimize every step of your sales funnel by identifying friction, improving flow, and increasing conversion rates.

Guest checkout simplifies buying by removing registration friction, helping shoppers purchase quickly and boosting conversions across all devices.

A clear guide to multivariate testing: how it works, when to use it, and practical steps for improving conversions with data-backed decisions.

A practical guide to representative samples, sampling methods, and how to avoid bias when running experiments, surveys, and market research.

Scroll depth shows how far users scroll on a page. Learn how to track, interpret, and improve scroll depth to boost engagement and conversions.

Test duration explained: how long to run A/B tests, calculate sample size, reach statistical significance, and get reliable CRO results.

A test hypothesis is a clear, data-backed statement predicting how a specific change will impact user behavior and guide reliable digital experimentation.

A Type 2 error happens when you fail to reject a false null hypothesis. Learn its meaning, causes, and examples to understand how it affects stats decisions.