Dating App Deep Dive: The Untold Story of User Behavior and Retention
An engineer who spent months working inside a dating app reveals its inner workings. The article details user ranking algorithms (based on like-to-pass ratio, with significant gender differences), user behavior (men prioritize looks, women prioritize personality, but both lean towards entertainment rather than serious dating), recommendation algorithms (personalization over simple recommendations), retention (tied to likes and matches, harder to improve for men), monetization (men pay for more likes), and user demographics (younger users prioritize looks, older users prioritize personality). The author argues that a dating app's success lies in precise personalization and effective retention strategies, not complex algorithms or features.
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