Explore versus repeat: insights from an online supermarket

At online supermarket Picnic, we implemented both traditional collaborative filtering and a hybrid method to provide recipe recommendations at scale. This case study presents findings from the online evaluation of these algorithms, focusing on the repeat-explore trade-off. Our findings allow other online retailers to gain insights into the importance of thoughtful model design in navigating this important balance. We argue that even when exploiting known preferences proves highly beneficial in the short term, prioritizing exploratory content is essential for long-term customer satisfaction and sustained growth. Our research lays the groundwork for a compelling discussion on defining success in balancing the familiar and the novel in online grocery shopping.

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Publication Details

Published
2024-10-08
DOI
https://doi.org/10.1145/3640457.3688050
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Explore versus repeat: insights from an online supermarket

Mariagiorgia Agnese Tandoi, Daniela Solis Morales
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Recommender Systems and Techniques
article

Explore versus repeat: insights from an online supermarket

Mariagiorgia Agnese Tandoi, Daniela Solis Morales
article en

Abstract

At online supermarket Picnic, we implemented both traditional collaborative filtering and a hybrid method to provide recipe recommendations at scale. This case study presents findings from the online evaluation of these algorithms, focusing on the repeat-explore trade-off. Our findings allow other online retailers to gain insights into the importance of thoughtful model design in navigating this important balance. We argue that even when exploiting known preferences proves highly beneficial in the short term, prioritizing exploratory content is essential for long-term customer satisfaction and sustained growth. Our research lays the groundwork for a compelling discussion on defining success in balancing the familiar and the novel in online grocery shopping.

Openalex Percentile: Top 73%
Recommender Systems and Techniques
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