What is an A/B Test?
An A/B test compares two variants to see which performs better on a defined metric.
Technical detail
In campaign and workflow contexts, A/B testing can compare copy, CTA, routing logic, or landing page variants. A valid test needs a clear hypothesis, a stable metric, and enough data before deciding. Teams should avoid changing too many variables at once. Results should feed directly into operational decisions.
Why it matters
- Reduces guesswork in messaging and workflow changes.
- Improves decision speed with measurable evidence.
- Supports continuous optimization of conversion flows.
- Helps teams pause low-performing variants earlier.
Example
A team tests two CTA variants on a landing page and tracks view-to-submit rate over a fixed period. After reaching the sample threshold, they scale the better performer.
How Retailbridge relates
Retailbridge campaign reporting surfaces variant-level funnel signals so teams can make practical pause or scale decisions quickly. The focus is consistent weekly decisions, not complex experimentation tooling.