Predicting Potential Customer Support Needs and Optimizing Search Ranking in a Two-Sided Marketplace

Fuente: arXiv
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Bibliographic Details
Main Authors: Kim, Do-kyum, Zhao, Han, Gao, Huiji, He, Liwei, Haldar, Malay, Katariya, Sanjeev
Format: Preprint
Published: 2025
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author Kim, Do-kyum
Zhao, Han
Gao, Huiji
He, Liwei
Haldar, Malay
Katariya, Sanjeev
author_facet Kim, Do-kyum
Zhao, Han
Gao, Huiji
He, Liwei
Haldar, Malay
Katariya, Sanjeev
contents Airbnb is an online marketplace that connects hosts and guests to unique stays and experiences. When guests stay at homes booked on Airbnb, there are a small fraction of stays that lead to support needed from Airbnb's Customer Support (CS), which may cause inconvenience to guests and hosts and require Airbnb resources to resolve. In this work, we show that instances where CS support is needed may be predicted based on hosts and guests behavior. We build a model to predict the likelihood of CS support needs for each match of guest and host. The model score is incorporated into Airbnb's search ranking algorithm as one of the many factors. The change promotes more reliable matches in search results and significantly reduces bookings that require CS support.
format Preprint
id arxiv_https___arxiv_org_abs_2503_17329
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Predicting Potential Customer Support Needs and Optimizing Search Ranking in a Two-Sided Marketplace
Kim, Do-kyum
Zhao, Han
Gao, Huiji
He, Liwei
Haldar, Malay
Katariya, Sanjeev
Machine Learning
Airbnb is an online marketplace that connects hosts and guests to unique stays and experiences. When guests stay at homes booked on Airbnb, there are a small fraction of stays that lead to support needed from Airbnb's Customer Support (CS), which may cause inconvenience to guests and hosts and require Airbnb resources to resolve. In this work, we show that instances where CS support is needed may be predicted based on hosts and guests behavior. We build a model to predict the likelihood of CS support needs for each match of guest and host. The model score is incorporated into Airbnb's search ranking algorithm as one of the many factors. The change promotes more reliable matches in search results and significantly reduces bookings that require CS support.
title Predicting Potential Customer Support Needs and Optimizing Search Ranking in a Two-Sided Marketplace
topic Machine Learning
url https://arxiv.org/abs/2503.17329