Next-Gen Sponsored Search: Crafting the Perfect Query with Inventory-Aware RAG (InvAwr-RAG) Based GenAI

2026-07-04

AI Summary

This study addresses the prevalent issue in current advertising systems where semantic mismatches between user queries and ad keywords lead to failed ad fill, resulting in lost revenue and engagement opportunities. To mitigate this, the authors propose InvAwr-RAG, an inventory-aware retrieval-augmented generation framework that uniquely integrates real-time ad inventory information into the RAG architecture. By leveraging generative AI to dynamically rewrite user queries—combining semantic retrieval with historically high-conversion query patterns—the approach enhances coverage diversity while preserving relevance. Experimental results demonstrate that InvAwr-RAG improves ad fill rate by 68%, substantially boosting both advertising revenue potential and user experience.

Abstract

Sponsored search plays a crucial role in e-commerce revenue generation, where advertisers strategically bid on keywords to capture the attention of users through relevant search queries. However, the process of identifying pertinent keywords for a given query presents significant challenges because of a vast and evolving keyword landscape, ambiguous intentions, and topic diversity. This paper highlights an opportunity for to earn a considerable amount of Ads revenue and user engagement where a significant proportion of queries fail to retrieve any sponsored ads. To utilize this opportunity, we introduce the Inventory-Aware RAG-based Generative AI model (InvAwr-RAG), which integrates advanced semantic retrieval and real-time inventory data. This model combines dynamically generated and historically successful queries to align with available inventory and ad campaigns while diversifying rewritten queries to enhance relevance and user engagement. Preliminary results show a significant 68% increase in fill rate and balanced relevance metrics, indicating a strong potential for increased ad revenue. The InvAwr-RAG model sets a new standard in dynamic query optimization, significantly improving ad relevancy, advertiser ROI, and user experience on Walmart's digital platform.

Problem

• sponsored search
• query rewriting
• ad relevance
• inventory awareness
• keyword matching

Innovation

• Inventory-Aware RAG
• Generative AI
• Sponsored Search
• Query Rewriting
• Ad Fill Rate