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Developing a conversion rate optimization framework for digital retailers—case study

Author

Listed:
  • Robert Zimmermann

    (University of Applied Sciences Upper Austria)

  • Andreas Auinger

    (University of Applied Sciences Upper Austria)

Abstract

To stay competitive against e-commerce, many retailers started to adopt a digital retail strategy, leveraging a myriad of online and offline touchpoints to increase their customer experience and, as a result, their sales. However, currently, no guidelines exist on how digital retailers can identify, evaluate, and influence sales impacting touchpoints along the customer journey. Hence, this study derives key elements of a conversion rate optimization framework, which can be used to increase sales of a digital retailer. Additionally, the derived framework is tested with the Austrian subsidiary of an international sports appeal and equipment retailer giving insights into its practical applicability. Results indicate that the developed framework can indeed be used to identify sales influencing touchpoints, which can be altered by specific marketing actions to increase sales of a digital retailer.

Suggested Citation

  • Robert Zimmermann & Andreas Auinger, 2023. "Developing a conversion rate optimization framework for digital retailers—case study," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 233-243, June.
  • Handle: RePEc:pal:jmarka:v:11:y:2023:i:2:d:10.1057_s41270-022-00161-y
    DOI: 10.1057/s41270-022-00161-y
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    References listed on IDEAS

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    1. Rosenbaum, Mark S. & Otalora, Mauricio Losada & Ramírez, Germán Contreras, 2017. "How to create a realistic customer journey map," Business Horizons, Elsevier, vol. 60(1), pages 143-150.
    2. Verhoef, Peter C. & Kannan, P.K. & Inman, J. Jeffrey, 2015. "From Multi-Channel Retailing to Omni-Channel Retailing," Journal of Retailing, Elsevier, vol. 91(2), pages 174-181.
    3. Grewal, Dhruv & Roggeveen, Anne L., 2020. "Understanding Retail Experiences and Customer Journey Management," Journal of Retailing, Elsevier, vol. 96(1), pages 3-8.
    4. Parise, Salvatore & Guinan, Patricia J. & Kafka, Ron, 2016. "Solving the crisis of immediacy: How digital technology can transform the customer experience," Business Horizons, Elsevier, vol. 59(4), pages 411-420.
    5. Anderl, Eva & Becker, Ingo & von Wangenheim, Florian & Schumann, Jan Hendrik, 2016. "Mapping the customer journey: Lessons learned from graph-based online attribution modeling," International Journal of Research in Marketing, Elsevier, vol. 33(3), pages 457-474.
    6. Lizhen Xu & Jason A. Duan & Andrew Whinston, 2014. "Path to Purchase: A Mutually Exciting Point Process Model for Online Advertising and Conversion," Management Science, INFORMS, vol. 60(6), pages 1392-1412, June.
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