Data Forest logo
Home page  /  Glossary / 
A/B Testing

A/B Testing

A/B Testing is a statistical method used to compare two versions of a variable to determine which performs better. It involves creating two variations, A and B, and randomly assigning subjects to each version to measure their performance. This method is commonly used in marketing, web development, and user experience design to test changes to webpages, advertisements, or other elements. By analyzing the results, organizations can make data-driven decisions to optimize their strategies and improve outcomes. A/B testing helps ensure that changes lead to measurable improvements, reducing the risk of implementing ineffective modifications.

Data Science
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

Latest publications

All publications
Article image preview
September 26, 2024
19 min

Data Analytics Puts the Correct Business Decisions on Conveyor

Clear Project Requirements: How to Elicit and Transfer to a Dev Team
September 26, 2024
12 min

Clear Project Requirements: How to Elicit and Transfer to a Dev Team

Prioritizing MVP Scope: Working Tips and Tricks
September 26, 2024
15 min

Prioritizing MVP Scope: Working Tips and Tricks

All publications
top arrow icon