A/B TESTING

A/B Testing Tool for Websites

Test headlines, layouts, CTAs, and entire pages. LuperIQ runs statistically valid experiments and tells you which version wins — with AI-powered optimization available.

Statistical
Significance Testing
Multi-Variant
Experiment Types
AI-Powered
Optimization

Stop Guessing, Start Testing #

Every business decision about your website should be backed by data. A/B testing lets you compare variations and know — not guess — which version performs better.

Visual Experiment Builder #

Create experiments without code. Test headlines, button colors, page layouts, pricing displays, and form designs with a visual editor.

Statistical Significance #

LuperIQ uses proper statistical testing to determine winners. No more ending tests early or making decisions on insufficient data.

Traffic Splitting #

Automatically split visitor traffic between variations. Control the percentage allocation and target specific visitor segments.

AI-Powered Optimization #

Use AI credits to analyze experiment results and generate optimization recommendations. The AI identifies patterns across experiments to suggest high-impact tests.

Conversion Goal Tracking #

Define what counts as a conversion for each experiment: form submissions, button clicks, page visits, or purchases. Track micro and macro conversions.

Experiment History #

Full archive of past experiments with results, learnings, and performance data. Build institutional knowledge about what works for your audience.

Free Tier

$0forever
  • 1 active experiment
  • 2 variations per test
  • Basic conversion tracking
  • Manual traffic split
Get Started

Professional

Includedwith Pro plan
  • Unlimited experiments
  • Multi-variant testing
  • Statistical significance engine
  • AI optimization
  • Segment targeting
  • Full experiment history
Start Free Trial

Customer Journey — understand visitor behavior to design better experiments.

Email Marketing — test email landing pages and optimize post-click conversion.

SEO Tools — optimize pages that A/B tests prove work best.