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Case study
Publication date: 13 November 2015

Shea Gibbs and Rajkumar Venkatesan

Hundreds of thousands of would-be hoteliers have been popping up all around the world, hoping to rent their own homes and apartments to complete strangers through a service called…

Abstract

Hundreds of thousands of would-be hoteliers have been popping up all around the world, hoping to rent their own homes and apartments to complete strangers through a service called Airbnb. The goal of Airbnb’s aspiring hosts was to use the company’s website to attract guests who were willing to pay the highest rates to stay in their homes for a short time. For Airbnb, the goal was to improve customer review performance so it could, in turn, increase profits. How could the company achieve its goal? Enter text mining, a technique that allowed businesses to scour Internet pages, decipher the meaning of groups of words, and assign the words a sentiment proxy through the use of a software package.

In order for text mining to be useful for Airbnb, its marketing professionals first had to gain access to customer review data on the company’s own website. The team then had to analyze the data to find ways to improve property performance. Was the team going to be able to leverage this large amount of data to determine a strategy going forward?

Details

Darden Business Publishing Cases, vol. no.
Type: Case Study
ISSN: 2474-7890
Published by: University of Virginia Darden School Foundation

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