A/B Testing
Comparing two versions of a marketing asset to see which performs better.
What is A/B Testing?
A/B testing (also called split testing) is a method of comparing two versions of a webpage, ad, email, or other marketing asset to determine which one performs better.
The process: split your audience randomly into two groups, show version A to one group and version B to the other, measure performance, and determine the winner based on statistical significance.
Test one variable at a time for clear results: headline, CTA button color, image, copy length, or offer. Testing multiple changes simultaneously makes it unclear which change drove results.
Successful A/B testing requires: sufficient traffic/volume for statistical significance, clear hypothesis, single variable testing, adequate test duration, and proper tracking.
A/B Testing for NZ Businesses
NZ businesses with lower traffic volumes need longer test durations to reach statistical significance. Don't conclude tests prematurely.
Focus on high-impact elements: headline, offer, CTA, and social proof. These typically have the biggest performance impact.
Common NZ A/B tests: NZ vs international imagery, casual vs formal tone, pricing displayed vs "Get a quote", testimonials vs no testimonials.
NZ Business Examples
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A Wellington SaaS company tests "$99/month" vs "From just $3.30/day" pricing display - daily rate increases conversions 18% -
An Auckland service business tests phone call vs form submission CTAs - call button generates 2.3x more enquiries -
A Christchurch e-commerce store tests free shipping threshold of $50 vs $75 - $50 increases conversion rate by 14%
Real-World Industry Examples
E-commerce
An online retailer tests checkout page variations
Single-page checkout vs multi-step: single page wins with 19% higher completion rate and 23% more revenue
Lead Generation
A B2B company tests long-form vs short-form landing pages
Long-form page (2,400 words) converts at 9.2% vs short-form (600 words) at 5.8% for high-ticket service
SaaS
A software company tests "Start Free Trial" vs "Get Started Free" CTA button text
"Get Started Free" increases trial signups by 12% - simpler language performs better
Related Terms
Frequently Asked Questions
How long should I run an A/B test?
Run tests for at least 1-2 weeks or until you reach statistical significance (usually 95% confidence level with 250+ conversions per variation). Account for weekly patterns - don't stop mid-week.
What should I test first?
Start with elements that impact conversion most: headline, offer, CTA button, and hero image. These typically drive 70%+ of performance. Save minor elements (footer links, color shades) for later.
What if my A/B test shows no difference?
Inconclusive tests are common. Either the change doesn't matter to users, or you need more volume. Try testing a more dramatic variation, or move on to test a different element. Not all tests will be winners.
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