[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82489-en":3,"doc-seo-82489-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},82489,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","Understanding Guest Preferences and Optimizing Two-sided Marketplaces: Airbnb as an Example","Airbnb is a two-sided community built on connection and belonging, enabling hosts to share their worlds while helping guests feel at home. It supports marketplace matching by providing tools that help hosts choose competitive prices and by personalizing guest experiences to surface listings aligned with needs. Economic modeling and causal inference estimate how bookings respond to host-set prices and how that response varies by guest and listing. These insights guide demand–supply balance and host and guest personalization decisions.","Understanding Guest Preferences and Optimizing Two-sided Marketplaces: Airbnb as an Example  \nYufei Wu  \nAirbnb, Inc. San Francisco, California, USA  \n[yufei.wu@airbnb.com](yufei.wu@airbnb.com)  \nDaniel Schmierer  \nAirbnb, Inc. San Francisco, California, USA [daniel.schmierer@airbnb.com](daniel.schmierer@airbnb.com)  \narXiv :2607 .00280v 1 [ cs .LG] 1 Jul 2026  \nAbstract  \nAirbnb is a community based on connection and belonging—many hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home; Airbnb strives to connect people and places. Among our efforts to connect guests and hosts, we provide tools to enable hosts to set competitive prices, which helps improve affordability for guests while helping hosts get more bookings. We also personalize the guest experience to show them the listings that match their needs.  \nTo help inform these efforts, we combine economic modeling and causal inference techniques to understand how guests book stays based on the prices hosts set, among other factors, and how that preference varies across different guests and listings. Such understanding helps us identify opportunities for Airbnb to support the marketplace and better connect guests and hosts. For example, understanding how much guests respond to different prices helps optimize the tools that we provide to hosts, in order to enable hosts to choose and set competitive prices that further balance demand and supply. As another example, understanding heterogeneity in guest preferences helps us personalize the guest experience and better match them with the listings that meet their needs, based on how much they respond to different prices and other factors.  \nKeywords  \nTwo-Sided Marketplaces, Demand Modeling, Price Elasticity, Preference Heterogeneity, Observational Causal Inference, Instrumental Variables  \n1 Introduction  \nAirbnb is a community based on connection and belonging—a community that was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million Hosts who have welcomed over 1.5 billion guest arrivals to over 100,000 cities and towns in almost every country and region across the globe. Hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home. We strive to connect people and places.  \nFor two-sided marketplaces, pricing is generally an important lever to balance supply and demand. But Airbnb does not set the prices that guests pay. Instead, hosts set prices for their places, while Airbnb sets service fees, which are a percentage of the value of a booking. There are several reasons why it can be challenging for hosts to know what is the right price to set for their place. First, the listings on Airbnb are highly heterogeneous, in terms of location,  \n© 2024 Airbnb, Inc. All rights reserved.  \nhome design, and amenities, making the pricing problem unique for each host. Second, some hosts may have limited experience hosting. Finally, because travel and accommodation is not an everyday occurrence, bookings may come only relatively infrequently, providing hosts with little feedback about the appropriateness of prices.  \nAs part of our efforts to connect guests and hosts, we provide tools that help hosts to choose and set competitive prices, in order to best meet the demand from guests. By providing the tools, Airbnb can not only provide better value to guests but also help hosts attract more business. For example, Ye, Qian, Chen, Wu, Zhou, De Mars, Yang, and Zhang [1], a prior paper that Airbnb’s Pricing Modeling team presented at KDD, discusses a predictive pricing model that empowered price suggestions to help hosts choose and set competitive prices. We also personalize guest experience and host tools to better match guests with the listings that tailor to their needs. For instance, Grbovic [2] and Grbovic and Cheng [3], two papers that Airbnb’s","cbCaisjD1AL6d39u","https://ap.wps.com/l/cbCaisjD1AL6d39u","pdf",1621991,1,5,"English","en",105,"# Abstract\n# Introduction\n# Experimental vs Observational Methods","[{\"question\":\"How does Airbnb help hosts set competitive prices?\",\"answer\":\"Airbnb provides pricing tools that help hosts choose and set competitive prices. This improves affordability for guests while increasing the likelihood of bookings for hosts.\"},{\"question\":\"What modeling approach does Airbnb use to understand guest booking behavior?\",\"answer\":\"Airbnb combines economic modeling with causal inference. It estimates how guests book stays based on the prices hosts set and other factors, and how sensitivity varies across guests and listings.\"},{\"question\":\"How does understanding guest preference heterogeneity improve guest experience?\",\"answer\":\"By identifying how preference for affordability differs across guest segments, Airbnb can personalize the guest experience. This enables better matching between guests and listings that meet their needs.\"}]",1784180886,13,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"understanding-guest-preferences-and-optimizing-two-sided-marketplaces-airbnb-as-an-example","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/understanding-guest-preferences-and-optimizing-two-sided-marketplaces-airbnb-as-an-example/82489/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-16",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"How does Airbnb help hosts set competitive prices?","Question",{"text":74,"@type":75},"Airbnb provides pricing tools that help hosts choose and set competitive prices. This improves affordability for guests while increasing the likelihood of bookings for hosts.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What modeling approach does Airbnb use to understand guest booking behavior?",{"text":79,"@type":75},"Airbnb combines economic modeling with causal inference. It estimates how guests book stays based on the prices hosts set and other factors, and how sensitivity varies across guests and listings.",{"name":81,"@type":72,"acceptedAnswer":82},"How does understanding guest preference heterogeneity improve guest experience?",{"text":83,"@type":75},"By identifying how preference for affordability differs across guest segments, Airbnb can personalize the guest experience. 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