BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations

TL;DR

BroadGen is a novel framework that improves broad match keyphrase recommendations in sponsored search advertising by leveraging historical data to enhance relevance, stability, and efficiency.

Contribution

It introduces a new approach for recommending broad match keyphrases that balances effectiveness and efficiency, addressing limitations of previous methods.

Findings

BroadGen achieves better query relevance and stability.

It supports daily recommendations for millions of sellers at eBay.

Over 2.5 billion items are served using BroadGen.

Abstract

In the domain of sponsored search advertising, the focus of Keyphrase recommendation has largely been on exact match types, which pose issues such as high management expenses, limited targeting scope, and evolving search query patterns. Alternatives like Broad match types can alleviate certain drawbacks of exact matches but present challenges like poor targeting accuracy and minimal supervisory signals owing to limited advertiser usage. This research defines the criteria for an ideal broad match, emphasizing on both efficiency and effectiveness, ensuring that a significant portion of matched queries are relevant. We propose BroadGen, an innovative framework that recommends efficient and effective broad match keyphrases by utilizing historical search query data. Additionally, we demonstrate that BroadGen, through token correspondence modeling, maintains better query stability over time. BroadGen's capabilities allow it to serve daily, millions of sellers at eBay with over 2.5 billion items.