Dating App A/B Testing
A specialist A/B testing practice built only for dating, social discovery, and community apps. We design and run paywall, onboarding, and retention experiments at 95%+ statistical confidence — the same playbook that scaled CRO across 19 dating domains and 120+ web properties.
Paywall A/B testing
Pricing tiers, trial mechanics, and screen architecture tested against revenue per user — typical lift of 15–40%.
Onboarding experiments
Signup-to-first-action flows rebuilt and measured against activation and Day-7 retention, not vanity completion rates.
Retention testing
Match cadence, notifications, and re-engagement loops tested against D7 and D30 — the metrics that compound LTV.
Statistical rigor
Every test ships with proper sample sizing and is called at 95%+ confidence, so you act on signal, not noise.
Why dating apps need a different testing approach
Generic CRO advice breaks down in dating products. Liquidity, match quality, and intent all distort the funnel, so a "best practice" onboarding flow can quietly suppress activation while a longer one lifts it. We've run experiments across mainstream, premium, niche, and video-first dating apps — and the patterns that move revenue are rarely the ones a generalist would test first.
Read the weekly teardowns on the Cohort Variant homepage for one real dating-app A/B test every Wednesday, or browse the dating app case studies for the full experiment design behind each lift, or the dating industry news breakdown for the full experiment design and result behind each lift.
Want us to run A/B tests in your dating app?
We embed as your fractional experimentation lead — paywall redesigns, onboarding overhauls, and a statistically rigorous testing program. Tell us what you want to test.
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