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Dynamic Conversion Behavior at E-Commerce Sites

Author

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  • Wendy W. Moe

    (Department of Marketing, McCombs School of Business, University of Texas at Austin, 1 University Station, B6700, Austin, Texas 78712)

  • Peter S. Fader

    (Department of Marketing, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

This paper develops a model of conversion behavior (i.e., converting store visits into purchases) that predicts each customer's probability of purchasing based on an observed history of visits and purchases. We offer an individual-level probability model that allows for different forms of customer heterogeneity in a very flexible manner. Specifically, we decompose an individual's conversion behavior into two components: one for accumulating visit effects and another for purchasing threshold effects. Each component is allowed to vary across households as well as over time. Visit effects capture the notion that store visits can play different roles in the purchasing process. For example, some visits are motivated by planned purchases, while others are associated with hedonic browsing (akin to window shopping); our model is able to accommodate these (and several other) types of visit-purchase relationships in a logical, parsimonious manner. The purchasing threshold captures the psychological resistance to online purchasing that may grow or shrink as a customer gains more experience with the purchasing process at a given website. We test different versions of the model that vary in the complexity of these two key components and also compare our general framework with popular alternatives such as logistic regression. We find that the proposed model offers excellent statistical properties, including its performance in a holdout validation sample, and also provides useful managerial diagnostics about the patterns underlying online buyer behavior.

Suggested Citation

  • Wendy W. Moe & Peter S. Fader, 2004. "Dynamic Conversion Behavior at E-Commerce Sites," Management Science, INFORMS, vol. 50(3), pages 326-335, March.
    • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:3:p:326-335
    DOI: 10.1287/mnsc.1040.0153
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    References listed on IDEAS

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    1. David C. Schmittlein & Donald G. Morrison, 2003. "A Live Baby or Your Money Back: The Marketing of In Vitro Fertilization Procedures," Management Science, INFORMS, vol. 49(12), pages 1617-1635, December.
    2. Dellaert, B.G.C. & Arentze, T. & Bierlaire, M. & Borgers, A. & Timmermans, H.J.P., 1997. "Investigating consumers' tendency to combine multiple shopping purposes and destinations," Discussion Paper 1997-94, Tilburg University, Center for Economic Research.
    3. David R. Bell & Jeongwen Chiang & V. Padmanabhan, 1999. "The Decomposition of Promotional Response: An Empirical Generalization," Marketing Science, INFORMS, vol. 18(4), pages 504-526.
    4. Johnson, Eric J & Russo, J Edward, 1984. "Product Familiarity and Learning New Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 11(1), pages 542-550, June.
    5. Janiszewski, Chris, 1998. "The Influence of Display Characteristics on Visual Exploratory Search Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(3), pages 290-301, December.
    6. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
    7. Seetharaman, P B & Chintagunta, Pradeep K, 2003. "The Proportional Hazard Model for Purchase Timing: A Comparison of Alternative Specifications," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 368-382, July.
    8. Jeongwen Chiang, 1991. "A Simultaneous Approach to the Whether, What and How Much to Buy Questions," Marketing Science, INFORMS, vol. 10(4), pages 297-315.
    9. Park, C Whan & Iyer, Easwar S & Smith, Daniel C, 1989. "The Effects of Situational Factors on In-Store Grocery Shopping Behavior: The Role of Store Environment and Time Available for Shopping," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(4), pages 422-433, March.
    Full references (including those not matched with items on IDEAS)

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