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Multichannel Marketing Attribution Using Markov Chains

Author

Listed:
  • Lukáš Kakalejč

    (Technical University of Košice, Slovakia)

  • Jozef Bucko

    (Technical University of Košice, Slovakia)

  • Paulo A. A. Resende

    (University of Brasília, Brasil)

  • Martina Ferencova

    () (Constitutional Court of the Slovak Republic, Slovakia)

Abstract

The objective of this paper is to analyze the data of a selected company using Markov chains. The data about online customer journeys were analyzed. The authors found that Markov model decreases the credit assigned to channels favored by last-touch heuristic models and assigns more credit to channels favored by first-touch or linear heuristic models. By using Markov order estimator GDL the authors also found that order 4 was the most suitable for analysis of buyer journeys. Approximately 40% of revenue was generated by journeys with less than 5 interactions and thus indecisive customers have small incremental effect on the overall conversions.

Suggested Citation

  • Lukáš Kakalejč & Jozef Bucko & Paulo A. A. Resende & Martina Ferencova, 2018. "Multichannel Marketing Attribution Using Markov Chains," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 7(1), pages 49-60, February.
  • Handle: RePEc:ods:journl:v:7:y:2018:i:1:p:49-60
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    References listed on IDEAS

    as
    1. Joel Barajas & Ram Akella & Marius Holtan & Aaron Flores, 2016. "Experimental Designs and Estimation for Online Display Advertising Attribution in Marketplaces," Marketing Science, INFORMS, vol. 35(3), pages 465-483, May.
    2. repec:eee:ijrema:v:33:y:2016:i:3:p:457-474 is not listed on IDEAS
    3. Peterson, Robert A., 2005. "Response construction in consumer behavior research," Journal of Business Research, Elsevier, vol. 58(3), pages 348-353, March.
    4. Massara, Francesco & Liu, Sandra S. & Melara, Robert D., 2010. "Adapting to a retail environment: Modeling consumer-environment interactions," Journal of Business Research, Elsevier, vol. 63(7), pages 673-681, July.
    5. repec:pcz:journl:v:6:y:2012:i:1:p:17-24 is not listed on IDEAS
    6. Beata Œlusarczyk & Sebastian Kot, 2012. "Principles Of The Supply Chain Performance Measurement," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 6(1), pages 17-24, December.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    attribution modeling; multichannel attribution; Markov chains; digital analysis; web analytics;

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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