Clicks Versus Conversion: Choosing a Recommender's Training Objective in E-Commerce
August 14, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Michael Weiss, Robert Rosenbach, Christian Eggenberger
arXiv ID
2508.10377
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Ranking product recommendations to optimize for a high click-through rate (CTR) or for high conversion, such as add-to-cart rate (ACR) and Order-Submit-Rate (OSR, view-to-purchase conversion) are standard practices in e-commerce. Optimizing for CTR appears like a straightforward choice: Training data (i.e., click data) are simple to collect and often available in large quantities. Additionally, CTR is used far beyond e-commerce, making it a generalist, easily implemented option. ACR and OSR, on the other hand, are more directly linked to a shop's business goals, such as the Gross Merchandise Value (GMV). In this paper, we compare the effects of using either of these objectives using an online A/B test. Among our key findings, we demonstrate that in our shops, optimizing for OSR produces a GMV uplift more than five times larger than when optimizing for CTR, without sacrificing new product discovery. Our results also provide insights into the different feature importances for each of the objectives.
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