Grocery to General Merchandise: A Cross-Pollination Recommender using LLMs and Real-Time Cart Context
- URL: http://arxiv.org/abs/2509.02890v2
- Date: Mon, 29 Sep 2025 13:23:57 GMT
- Title: Grocery to General Merchandise: A Cross-Pollination Recommender using LLMs and Real-Time Cart Context
- Abstract summary: This paper introduces a cross-pollination (XP) framework that bridges grocery and general merchandise cross-category recommendations.<n>Our solution employs a two-stage framework: (1) A candidate generation mechanism that uses co-purchase market basket analysis and LLM-based approach to identify novel item-item associations; and (2) a transformer-based ranker that leverages the real-time sequential cart context.<n> offline analysis and online A/B tests show an increase of 36% add-to-cart rate with LLM-based retrieval on the item page, and 15% lift in add-to-cart using cart context-
- Score: 3.407794744126759
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Modern e-commerce platforms strive to enhance customer experience by providing timely and contextually relevant recommendations. However, recommending general merchandise to customers focused on grocery shopping -- such as pairing milk with a milk frother -- remains a critical yet under-explored challenge. This paper introduces a cross-pollination (XP) framework, a novel approach that bridges grocery and general merchandise cross-category recommendations by leveraging multi-source product associations and real-time cart context. Our solution employs a two-stage framework: (1) A candidate generation mechanism that uses co-purchase market basket analysis and LLM-based approach to identify novel item-item associations; and (2) a transformer-based ranker that leverages the real-time sequential cart context and optimizes for engagement signals such as add-to-carts. Offline analysis and online A/B tests show an increase of 36\% add-to-cart rate with LLM-based retrieval on the item page, and 15\% lift in add-to-cart using cart context-based ranker on the cart page. Our work contributes practical techniques for cross-category recommendations and broader insights for e-commerce systems.
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