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Using location-based social networks as a novel source of marketing data: the case of shopping malls

Author

Listed:
  • Elena B. Pokryshevskaya

    (National Research University Higher School of Economics)

  • Evgeny A. Antipov

    (National Research University Higher School of Economics)

Abstract

In this paper we demonstrate how publicly available data from location-based social networks can be used to model the popularity of different places. Our empirical analysis is based on a sample of 112 shopping malls located in Saint-Petersburg, the second largest city in Russia. Regression models that explain various measures of shopping malls' popularity using the characteristics of a place are built. It appeared that the number of visitors, check-ins, tips and even the frequency of visit can be largely explained by the basic features of a shopping mall, while successful modeling of a place's user rating requires more detailed data. Combining the data on the features of places, text reviews and popularity indicators from social networks is a promising approach for building sales, traffic, satisfaction and loyalty projection models, which are especially useful in business planning.

Suggested Citation

  • Elena B. Pokryshevskaya & Evgeny A. Antipov, 2015. "Using location-based social networks as a novel source of marketing data: the case of shopping malls," Economics Bulletin, AccessEcon, vol. 35(2), pages 1292-1298.
    • Handle: RePEc:ebl:ecbull:eb-14-00708
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    More about this item

    Keywords

    location-based social networks; check-in; shopping mall; robust regression;
    All these keywords.

    JEL classification:

    • M0 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - General
    • D1 - Microeconomics - - Household Behavior

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