What Is A/B Testing? Meaning, Formula and Examples
A/B Testing explained in plain English: what it means, why it matters, how to calculate or apply it, a worked example and common mistakes.
A/B Testing: Comparing two versions to see which performs better. It supports evidence-based decisions.
What A/B Testing means
Comparing two versions to see which performs better.
Why it matters
It supports evidence-based decisions. Used alongside other metrics, it helps teams make better budget and strategy decisions.
How to calculate or apply it
Split traffic and compare results
Worked example
Testing two headlines.
Common mistake to avoid
Stopping tests too early.
Related terms
Conversion Rate
The percentage of visitors who complete a desired action.
Core Web Vitals
Google's metrics for loading (LCP), interactivity (INP) and visual stability (CLS).
Statistical Significance
Confidence that test differences are not due to chance.
Need help putting this into practice? Gravmo offers conversion rate optimisation. Get a proposal or message us on WhatsApp.
Frequently asked questions
Is A/B Testing the same for every business?
No. Good values depend on your industry, margins, goals and data quality. Compare against your own history first.
Where can I see A/B Testing?
Most values come from analytics, ad platforms, marketplace dashboards or your own sales records, depending on the metric.
Written and reviewed by Gravmo's marketing team. Read our editorial policy.
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