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Exploring the strategic role of Marketer-Generated-Content analytics towards Airbnb hosts sales optimization

Chattopadhyay Manojit|Pal Debdatta
한국마케팅과학회 (Korean Scholars of Marketing Science)|2024.03|Journal of Global Scholars of Marketing Science(마케팅과학연구) (全球营销科学学报)|제34권 제2호|pp. 253-282|DOI 10.1080/21639159.2023.2292636

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참고문헌

키워드

value co-creationMarketer generated content (MGCs)linguistic cuesAirbnb title descriptionmultivariate adaptive regression spline model
주제분류경영학

초록

Although user-generated content is reported to improve Airbnb host’s sales, the impact of Marketer-Generated Content (MGC) on the minimum sales generated from the reviewers who have reviewed the MGC is yet to be explored. This study examines MGC of title descriptions analysis from the City of Los Angeles listing data to understand their importance in predicting hosts’ net sales. The analysis employs two complementary econometric approaches: parametric multiple regression and the nonparametric multivariate adaptive regression spline model across three neighbourhood groups and two price groups. The findings indicate hosts can employ MGC to optimize sales and should highlight feature words in the title that best reflect the property characteristics and appeal to a target group that may be locationspecific, price-sensitive, or both. The title should be informative and detailed within a limit of 10 words. The novelty of the work is to identify the influence of total sales for respective feature words from the title description of Airbnb property and to analyze their uses in marketing communications. The practical implications indicate that host-generated feature words are crucial in maximizing net sales for the property.

Abstract

Although user-generated content is reported to improve Airbnb host’s sales, the impact of Marketer-Generated Content (MGC) on the minimum sales generated from the reviewers who have reviewed the MGC is yet to be explored. This study examines MGC of title descriptions analysis from the City of Los Angeles listing data to understand their importance in predicting hosts’ net sales. The analysis employs two complementary econometric approaches: parametric multiple regression and the nonparametric multivariate adaptive regression spline model across three neighbourhood groups and two price groups. The findings indicate hosts can employ MGC to optimize sales and should highlight feature words in the title that best reflect the property characteristics and appeal to a target group that may be locationspecific, price-sensitive, or both. The title should be informative and detailed within a limit of 10 words. The novelty of the work is to identify the influence of total sales for respective feature words from the title description of Airbnb property and to analyze their uses in marketing communications. The practical implications indicate that host-generated feature words are crucial in maximizing net sales for the property.

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