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How to Win More Bookings on Airbnb
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How to Win More Bookings on Airbnb
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<p>Columbia Business School research shows that an Airbnb host’s smile reduces uncertainty and increases demand, especially for less experienced hosts and shared accommodations.</p>
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Whether you’re crashing at a stranger’s home or getting a ride in their car, participating in the sharing economy involves a substantial amount of unc
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<p dir="ltr">Whether you’re crashing at a stranger’s home or getting a ride in their car, participating in the sharing economy involves a substantial amount of uncertainty and an eventual leap of faith on the part of the consumer. When booking an Airbnb, for example, you can learn only so much before you decide to take a chance and stay there, sometimes sharing the space with a host you’ve never met before. </p><p dir="ltr">You’re not flying totally blind, however. Airbnb listings include some knowable facts about where you’ll be spending the night. You can see the property’s price, location, and amenities, and you can check out other customers’ reviews. These details, known to researchers of consumer behavior as informational cues, make up a good portion of the investigation a consumer does before booking their stay. The rest involves a typically less quantifiable process of sussing out the overall <em>vibe</em> of the place. Does the host look warm and inviting? Will this be a pleasant place to spend the night? This involves relying on noninformational cues, which provide no explicit information but instead appeal to emotions, humor, or aesthetics. For her recent paper published in the <em>Journal of Consumer Research,</em> <a href="https://business.columbia.edu/faculty/people/elizabeth-friedman">Elizabeth Friedman</a>, assistant professor of business in the Marketing Division at Columbia Business School, examined the effect of one specific noninformational cue on Airbnb listings: the host’s smile — or lack thereof.</p><p dir="ltr">In customer service, smiles are a known boon, at least to in-person interactions. Prior research has shown smiling increases perceptions of warmth and improves the mood of both people in the interaction, leading to greater consumer satisfaction, higher employee evaluations, and repeat customers. The new study explores the effects of smiling in an e-commerce setting, where face-to-face interaction is impossible.</p><p dir="ltr"><strong>Key Takeaways</strong></p><ul><li dir="ltr">When an Airbnb host posts a profile picture where they are smiling, it increases the likelihood of a consumer booking their property by an average of 3.5 percent.</li><li dir="ltr">The increase in demand is driven by a smile’s effect of decreasing a consumer’s uncertainty about staying at a stranger’s property, regarding both the quality of the accommodations and how their interactions with the host will go.</li><li dir="ltr">The effect is greater for hosts who are male, as well as for hosts who are less experienced. Smiling profile photos also proved beneficial for properties with features that increase consumer uncertainty: shared spaces, no provided parking, and higher crime neighborhoods.</li><li dir="ltr">The findings have implications for how people present themselves online, extending to the broader hospitality industry, to other professions like medicine and law, and even to online dating.</li></ul><p dir="ltr"><strong>How Smiles Impact Consumer Choices</strong></p><p dir="ltr">To quantify the effect of an Airbnb host’s smile on property demand, Friedman and her co-researchers used large-scale observational data gleaned from more than 9,000 hosts across eight months in seven major cities, including New York, Los Angeles, Austin, and Seattle. They relied on machine learning to automatically identify whether a host was smiling in their profile picture and then estimated an econometric model to track demand for the property, measuring demand by how frequently the property was booked. To control for other variables among the properties — like the price, the host’s level of experience, and the neighborhood — the researchers applied inverse probability of treatment weighting (IPTW) to create a matched sample where the smiling condition of the host was separated from other variables. <br><br><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXd7CHs-QmVdV498xFR5r5yrlpb7ycWLjMkShP8q7izosZ2JYD5fLgkDTsZtn-1vl2qnS5z1OI91Dgtzq4us0UwZwz20dmJojlDwPTLmhvUpIHySjxh1bTpzQwj953nA_Lb0gjS1Ew?key=zh6EvgCvaoiGnvTfbjA06w" data-entity-uuid="" data-entity-type="" alt="Airbnb property listings study" width="1600" height="838"></p>
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