Three Essays on Analyzing and Managing Online Consumer Behavior

149 Pages·2014·2.53 MB·English

Three Essays on
Analyzing and Managing
Online Consumer Behavior

Inaugural-Dissertation
zur Erlangung des Doktorgrades
des Fachbereichs Wirtschaftswissenschaften
an der Wirtschaftswissenschaftlichen Fakultät
der Universität Passau

vorgelegt von

Eva Maria Anderl M.A.
geboren am 21. Mai 1981 in München

Prinzregentenstr. 83
81675 München

Dissertation an der
Wirtschaftswissenschaftlichen Fakultät
der Universität Passau

Erstgutachter: Prof. Dr. Jan H. Schumann
Lehrstuhl für Betriebswirtschaftslehre mit Schwerpunkt
Marketing und Innovation
Universität Passau

Zweitgutachter: Prof. Dr. Florian von Wangenheim
Professur für Technologiemarketing
ETH Zürich

Datum der Disputation: 20. November 2014

Summary V

Summary
Summary
Over the last two decades, the Internet has fundamentally changed the ways firms
and consumers interact. The ongoing evolution of the Internet-enabled market
environment entails new challenges for marketing research and practice, including
the emergence of innovative business models, a proliferation of marketing channels,
and an unknown wealth of data. This dissertation addresses these issues in three
individual essays.
Study 1 focuses on business models offering services for free, which have
become increasingly prevalent in the online sector. Offering services for free raises
new questions for service providers as well as marketing researchers: How do
customers of free e-services contribute value without paying? What are the nature
and dynamics of nonmonetary value contributions by nonpaying customers? Based
on a literature review and depth interviews with senior executives of free e-service
providers, Study 1 presents a comprehensive overview of nonmonetary value
contributions in the free e-service sector, including not only word of mouth, co-
production, and network effects but also attention and data as two new dimensions,
which have been disregarded in marketing research. By putting their findings in the
context of existing literature on customer value and customer engagement, the
authors do not only shed light on the complex processes of value creation in the
emerging e-service industry but also advance marketing and service research in
general.
Studies 2 and 3 investigate the analysis of online multichannel consumer
behavior in times of big data. Firms can choose from a plethora of channels to reach
consumers on the Internet, such that consumers often use a number of different
channels along the customer journey. While the unprecedented availability of
individual-level data enables new insights into multichannel consumer behavior, it
also makes high demands on the efficiency and scalability of research approaches.
Study 2 addresses the challenge of attributing credit to different channels
along the customer journey. Because advertisers often do not know to what degree
each channel actually contributes to their marketing success, this attribution
challenge is of great managerial interest, yet academic approaches to it have not
found wide application in practice. To increase practical acceptance, Study 2
introduces a graph-based framework to analyze multichannel online customer path
data as first- and higher-order Markov walks. According to a comprehensive set of
Summary VI

criteria for attribution models, embracing both scientific rigor and practical
applicability, four model variations are evaluated on four, large, real-world data sets
from different industries. Results indicate substantial differences to existing
heuristics such as “last click wins” and demonstrate that insights into channel
effectiveness cannot be generalized from single data sets. The proposed framework
offers support to practitioners by facilitating objective budget allocation and
improving team decisions and allows for future applications such as real-time
bidding.
Study 3 investigates how channel usage along the customer journey
facilitates inferences on underlying purchase decision processes. To handle
increasing complexity and sparse data in online multichannel environments, the
author presents a new categorization of online channels and tests the approach on
two large clickstream data sets using a proportional hazard model with time-varying
covariates. By categorizing channels along the dimensions of contact origin and
branded versus generic usage, Study 3 finds meaningful interaction effects between
contacts across channel types, corresponding to the theory of choice sets. Including
interactions based on the proposed categorization significantly improves model fit
and outperforms alternative specifications. The results will help retailers gain a
better understanding of customers’ decision-making progress in an online
multichannel environment and help them develop individualized targeting
approaches for real-time bidding.
Using a variety of methods including qualitative interviews, Markov graphs,
and survival models, this dissertation does not only advance knowledge on
analyzing and managing online consumer behavior but also adds new perspectives
to marketing and service research in general.
Acknowledgments VII

Acknowledgments
Acknowledgments
This project would not have been possible without the support of many. First and
foremost, I want to express my deepest gratitude to my advisor Jan Schumann for
his continuous support, encouragement, and inspiration. I count myself incredibly
lucky to have you as a mentor. Many thanks also go to my second advisor Florian
von Wangenheim for his invaluable guidance and for immediately welcoming me
into the DTM “family.”
Without my colleagues in Munich and Passau this dissertation would not be
the same—and writing it would have been much less fun. Thank you so much to all
of you! Armin März deserves a special mention for being a great partner in crime
and roommate from day one. I would also like to thank my other co-authors Ingo
Becker, Werner Kunz, and Sebastian Klapdor, as well as my cooperation partners at
intelliAd, Feld M, and ValueClick. It was a pleasure to work with you.
I gratefully acknowledge the institutional support I have received during my
dissertation. My study was conducted in the context of the project “Fre(E)S:
Produktivität kostenfreier E-Services” (FKZ: 01FL10038), which was funded by the
German Federal Ministry of Education and Research (BMBF) and supported by the
German Aerospace Center (DLR). A big thank you also goes to Passau University
for providing me with the means to finish this dissertation and to Technische
Universität München, the University of Massachusetts Boston, and the Cambridge
Public Library for giving me shelter. Special thanks to Werner Kunz for inviting me to
Boston and being a great mentor during my time in the US and beyond!
I sincerely thank my friends and family for pushing me to take on this
challenge and keeping my spirit up along the way. Finally, thank you, Sebastian, for
accompanying me on this journey—and for all the rest.

Short Table of Contents IX

Short Table of Contents
Short Table of Contents

Summary ................................................................................................................. V

Acknowledgments .................................................................................................. VII

Short Table of Contents .......................................................................................... IX

Table of Contents ................................................................................................... XI

List of Figures ....................................................................................................... XIV

List of Tables ......................................................................................................... XV

List of Abbreviations.............................................................................................. XVI

1 Introduction ........................................................................................................... 1

2 There Is No Such Thing as a Free Lunch: Nonmonetary Customer Value

Contributions in Free E-Services ......................................................................... 11

3 Mapping the Customer Journey: A Graph-Based Framework for Online

Attribution Modeling ............................................................................................. 33

4 Analyzing Multichannel Online Customer Journeys for an Online Retailer: A

Categorization Approach ..................................................................................... 65

5 Conclusion .......................................................................................................... 99

6 References ........................................................................................................ 105