What is A/B Testing? - Explanation & Meaning

Definition

A/B testing (split testing) is an experimental method where two versions of a web page or element are simultaneously shown to different user groups to determine which variant performs better on a defined metric.

Technical explanation

A/B testing randomly distributes incoming traffic across two or more variants (A = control, B = variant) via server-side or client-side assignment. Server-side testing applies the variant before HTML is sent to the browser, preventing flicker and offering better performance. Client-side testing applies changes via JavaScript after the page loads. Statistical significance, typically at a 95% confidence level, determines whether the difference in conversion between variants is not explained by chance. The required sample size is calculated beforehand based on the expected effect, baseline conversion rate, and desired confidence level via power analysis. Bayesian methods offer an alternative to frequentist approaches and allow continuous monitoring without the peeking problem. Multivariate testing tests multiple elements simultaneously, while multi-armed bandit algorithms automatically direct more traffic to winning variants. Feature flags integrate A/B testing into the deployment pipeline for controlled rollouts. Tools like Optimizely, VWO, Google Optimize, and LaunchDarkly provide complete platforms for experiment management, segmentation, and analysis.

How MG Software applies this

MG Software implements A/B testing via feature flags and server-side experiments in Next.js. We help clients optimize hypothesis-driven by setting up experiments for call-to-action buttons, forms, and landing pages. Data-driven decision-making instead of gut feeling leads to demonstrably higher conversions.

Practical examples

• A SaaS company testing two variants of their pricing page: one with monthly prices and one with annual prices prominently displayed. The annual variant increases average contract value by 23%.
• An e-commerce site testing the color and text of the "Add to Cart" button and discovering that an orange button with "Order Now" generates 15% more clicks than a blue one with "Add to Cart".
• A lead generation site comparing a short form (3 fields) with a long form (8 fields) and discovering that the short form generates 60% more leads but the long form produces higher quality leads.

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