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Forecasting the Effects of In-Store Marketing on Conversion Rates for Online Shops

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  • Holger Fink

    (Department of Computer Science and Mathematics, Munich University of Applied Sciences, Lothstrasse 64, 80335 Munich, Germany
    Center for Quantitative Risk Analysis, Department of Statistics, Ludwig-Maximilians-Universität München, Akademiestrasse 1/I, 80799 Munich, Germany)

  • Yvonne Graf

    (Chair of Strategic Industrial Marketing, Institute of Business Administration, University of Regensburg, Universitätsstrasse 31, 93053 Regensburg, Germany)

Abstract

As webstores usually face the issue of low conversion rates, finding ways to effectively increase them is of special interest to researchers and practitioners alike. However, to the best of our knowledge, no one has yet empirically investigated the usefulness of various in-webstore marketing tools like coupons or different types of product recommendations. By analysing clickstream data for a shoe and a bed online store, we are contributing to closing this gap. In particular, we use our present data to build more general hypotheses on how such purchasing incentives might function and on how they could be used in practice.

Suggested Citation

  • Holger Fink & Yvonne Graf, 2018. "Forecasting the Effects of In-Store Marketing on Conversion Rates for Online Shops," Forecasting, MDPI, vol. 1(1), pages 1-20, September.
    • Handle: RePEc:gam:jforec:v:1:y:2018:i:1:p:6-89:d:169664
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    References listed on IDEAS

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