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 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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