What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features

75 Pages Posted: 31 May 2017 Last revised: 2 Jul 2021

See all articles by Shunyuan Zhang

Shunyuan Zhang

Harvard University; Harvard University - Business School (HBS)

Dokyun Lee

Boston University - Questrom School of Business

Param Vir Singh

Carnegie Mellon University - David A. Tepper School of Business

Kannan Srinivasan

Carnegie Mellon University - David A. Tepper School of Business

Date Written: May 25, 2017

Abstract

We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel dataset spanning 7,423 properties over 16 months, we find that properties with verified images had 8.98% higher occupancy than properties without verified images (images taken by the host). To explore what constitutes a good image for an Airbnb property, we quantify 12 human-interpretable image attributes that pertain to three artistic aspects—composition, color, and the figure-ground relationship—and we find systematic differences between the verified and unverified images. We also predict the relationship between each of the 12 attributes and property demand, and we find that most of the correlations are significant and in the theorized direction. Our results provide actionable insights for both Airbnb photographers and amateur host photographers who wish to optimize their images. Our findings contribute to and bridge the literature on photography and marketing (e.g., staging), which often either ignores the demand side (photography) or does not systematically characterize the images (marketing).

Keywords: sharing economy, Airbnb, property demand, computer vision, deep learning, image feature extraction, content engineering

JEL Classification: M3

Suggested Citation

Zhang, Shunyuan and Zhang, Shunyuan and Lee, Dokyun and Singh, Param Vir and Srinivasan, Kannan, What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features (May 25, 2017). Available at SSRN: https://ssrn.com/abstract=2976021. or http://dx.doi.org/10.2139/ssrn.2976021

Shunyuan Zhang

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan 270C
Boston, MA 02163
United States

Dokyun Lee

Boston University - Questrom School of Business ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States

Param Vir Singh (Contact Author)

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States
412-268-3585 (Phone)

Kannan Srinivasan

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

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