A/B Testing: decisions backed by data
Test landing pages, offers, pricing, and creatives. Statistical significance, audience segments, and automatic calculation.
Without testing, you're just guessing
Gut-feeling decisions cost businesses millions in lost conversions.
average conversion lift after the first 3 A/B tests for our clients
of hypotheses fail — but without testing, you'd roll them out to all traffic
minimum for statistically significant results at 1,000+ daily visits
How A/B testing works
Set up a test in 5 minutes — results include automatic significance calculation
Create variants
Original (A) and one or more variants (B, C, D). Traffic split — even or weighted.
Collect data
Conversion rate, average order value, bounce rate — per each variant. Data updates in real time.
Statistical significance
Automatic p-value and confidence interval calculation. The test concludes when there's enough data.
Deploy the winner
One click — the winning variant is applied to all traffic. Full test history is preserved.
What A/B testing delivers
What our clients test
Any element that impacts conversion and revenue
Landing pages
Headlines, CTA buttons, form design, social proof. Typical conversion lift of 15-40%.
Pricing
Plans, discounts, bundles. Which price point maximizes revenue, not just conversion.
Email campaigns
Subject lines, send times, CTAs. Open rate and click rate improvements of 20-50%.