Flipkart Tech
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The Science of Unified Ranking: Integrating Ads and Organic Recommendations

Flipkart's engineering team developed a unified ranking system that allows sponsored ads and organic product recommendations to compete dynamically for placement slots, replacing the traditional fixed-slot approach. The solution addresses challenges like data distribution mismatches, fallback risks, and feature parity gaps through a single robust model using isAds flags and cross-features, combined with calibrated scoring functions. The system uses FTRL (Follow The Regularized Leader) algorithm for online learning and multi-stage filtering with CTR and CVR models. Production deployment resulted in a 1.36% increase in organic orders and 3.4% lift in ad revenue, demonstrating that dynamic ranking outperforms static ad placement while maintaining user experience.

    #machine-learning#ecommerce#recommendation-systems
Nov 04, 2025•14m read time•From blog.flipkart.tech
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Executive SummaryIntroductionSystem ArchitectureThe Hurdles on the Path to UnificationGet Amar Kumar’s stories in your inboxOur Solution: A Unified RankerImpactThe Path Forward
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