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Online Purchase Paths and Conversion Dynamics across Multiple Websites

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  • Park, Chang Hee

Abstract

Low transportation costs online allow shoppers to visit multiple e-commerce sites for a purchase decision. This research investigates online shoppers’ visit and purchase behaviors across competing websites. To consider that shoppers’ longitudinal cross-site visit data may consist of several unobserved shopping episodes, we propose a modeling approach to probabilistically clustering and relating online visits to latent shopping episodes, based on the temporal patterns of the visit events. The inferences are then used to examine shoppers’ visit-to-purchase behavior across websites. Using Internet clickstream data on individual-level browsing and transaction records at major air travel sites, we find that online shoppers’ cross-site visit patterns tend to be clustered and the purchase propensity is significantly higher at later visits within a visit cluster, compared to earlier visits. As our results suggest the possibility that visit clusters can serve as a reasonable proxy for shopping episodes, we look further into shoppers’ website choice and purchase behaviors within a cluster. We discuss how the cluster-based analysis can help managers tailor online marketing and advertising strategies based on shoppers’ cross-site visit and purchase patterns.

Suggested Citation

  • Park, Chang Hee, 2017. "Online Purchase Paths and Conversion Dynamics across Multiple Websites," Journal of Retailing, Elsevier, vol. 93(3), pages 253-265.
  • Handle: RePEc:eee:jouret:v:93:y:2017:i:3:p:253-265
    DOI: 10.1016/j.jretai.2017.04.001
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    References listed on IDEAS

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    2. Wagner, Gerhard & Schramm-Klein, Hanna & Steinmann, Sascha, 2020. "Online retailing across e-channels and e-channel touchpoints: Empirical studies of consumer behavior in the multichannel e-commerce environment," Journal of Business Research, Elsevier, vol. 107(C), pages 256-270.
    3. Franz Hackl & Michael Hölzl‐Leitner & Rudolf Winter‐Ebmer & Christine Zulehner, 2021. "Successful retailer strategies in price comparison platforms," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(5), pages 1284-1305, July.
    4. Meihua Zuo & Spyros Angelopoulos & Zhouyang Liang & Carol X. J. Ou, 2023. "Blazing the Trail: Considering Browsing Path Dependence in Online Service Response Strategy," Information Systems Frontiers, Springer, vol. 25(4), pages 1605-1619, August.
    5. Franz Hackl & Michael Hölzl-Leitner & Rudolf Winter-Ebmer & Christine Zulehner, 2018. "Success of firm strategies in e-commerce," Economics working papers 2018-10, Department of Economics, Johannes Kepler University Linz, Austria.
    6. Mahfouz, Ahmed Y. & Joonas, Kishwar & Opara, Emmanuel U., 2020. "An overview of and factor analytic approach to flow theory in online contexts," Technology in Society, Elsevier, vol. 61(C).
    7. Herhausen, Dennis & Kleinlercher, Kristina & Verhoef, Peter C. & Emrich, Oliver & Rudolph, Thomas, 2019. "Loyalty Formation for Different Customer Journey Segments," Journal of Retailing, Elsevier, vol. 95(3), pages 9-29.
    8. Miguel Angel de la Llave Montiel & Fernando López, 2020. "Spatial models for online retail churn: Evidence from an online grocery delivery service in Madrid," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1643-1665, December.
    9. Reutterer, Thomas & Platzer, Michael & Schröder, Nadine, 2021. "Leveraging purchase regularity for predicting customer behavior the easy way," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 194-215.

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    More about this item

    Keywords

    Electronic commerce; Online retail business; Multi-site shopping behavior; Pattern analysis;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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