A/B Testing
Definition
A/B Testing (also called split testing) is a controlled experiment where two or more variants of a page, form, or element are shown to different segments of users at the same time to determine which version performs better against a predefined goal.
How It Works
Hypothesis
Identify a change you believe will improve a metric (e.g., "A shorter form will increase completions").
Variants
Create two versions: the Control (original) and the Variant (with your change).
Traffic Split
Randomly assign visitors to each version, typically 50/50.
Measure
Track your goal metric (conversion rate, completion rate, etc.) until you reach statistical significance.
Decide
Roll out the winning version or iterate with a new hypothesis.
Why It Matters for Forms and Surveys
Even small changes to a form can dramatically affect completion rates. A/B testing lets you make data-driven decisions instead of guessing. Common elements to test include:
- Number of fields: fewer fields often increase conversions, but may reduce lead quality.
- Button copy: "Submit" vs. "Get My Free Quote" can yield very different click rates.
- Layout: single-column vs. multi-column, single-step vs. multi-step.
- Social proof: adding trust badges or testimonials near the form.
- Field labels: placeholder text vs. floating labels vs. top-aligned labels.
Best Practices
- Test one variable at a time so you know exactly what caused the difference.
- Wait for statistical significance before declaring a winner: at least 95% confidence.
- Run tests long enough to account for day-of-week and traffic fluctuations.
- Document everything so your team can learn from past experiments.
Related Terms