8% Higher Conversions
Impact Area: Cross-Sell & Upsell
How India’s leading e-commerce marketplace boosted conversions by 8% through AI-powered recommendations
About the Project
A leading e-commerce marketplace in India aimed to unlock revenue growth through intelligent cross-sell and up-sell strategies. While the client had access to behavioral and transactional data, their existing systems lacked the orchestration and intelligence required to drive contextual, customer-specific nudges at scale.
The client sought a unified intelligence layer that could segment users based on purchase intent, surface category-level recommendations, and activate them through real-time digital touchpoints.
Key Issues
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Disconnected recommendation logic across platforms, leading to generic nudges
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Inability to rank category affinities at a user level for precision targeting
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No dynamic way to factor in contextual signals like time, device, or browsing path
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Promotional spends lacked targeting, resulting in low ROI on coupon-based campaigns
Our Approach
Enterprise-Grade Recommendation Framework
We designed and deployed a modular AI recommendation system built on collaborative and content-based algorithms to personalize suggestions across channels.
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Data Engineering: Unified historical and real-time signals from purchase logs, category views, app behavior, and marketing engagement
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Multi-Label Classifier: Built to predict top category affinity per user with confidence scores
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Activation Engine: Automated audience segmentation for targeted nudges via WhatsApp, email, and push notifications
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Experimentation Layer: A/B testing to compare recommendation variants and measure impact continuously
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Campaign Sync: Integrated with digital marketing and merchandising workflows for consistent experience across touchpoints
Impact
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~8% increase in conversion from recommendation-activated cohorts
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~5% improvement in notification click-through rates
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Strategic coupon spend ROI of 6x (factoring GMV uplift vs. discounts)
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Personalization system now supports 25M+ user interactions monthly
