Analytics for Customer Engagement

Tammo H. A. Bijmolt; Peter S. H. Leeflang; Frank Block; Maik Eisenbeiss; Bruce G. S. Hardie; Aurelie Lemmens; Peter Saffert

doi:10.1177/1094670510375603

Analytics for Customer Engagement

Tammo H. A. Bijmolt^*, Peter S. H. Leeflang, Frank Block, Maik Eisenbeiss, Bruce G. S. Hardie, Aurelie Lemmens, Peter Saffert

^*Corresponding author for this work

Marketing

Research output: Contribution to journal › Article › Academic › peer-review

327 Citations (Scopus)

Abstract

In this article, we discuss the state of the art of models for customer engagement and the problems that are inherent to calibrating and implementing these models. The authors first provide an overview of the data available for customer analytics and discuss recent developments. Next, the authors discuss the models used for studying customer engagement, where they distinguish the following stages: customer acquisition, customer development, and customer retention. Finally, they discuss several organizational issues of analytics for customer engagement, which constitute barriers for introducing analytics for customer engagement.

Original language	English
Pages (from-to)	341-356
Number of pages	16
Journal	Journal of Service Research
Volume	13
Issue number	3
DOIs	https://doi.org/10.1177/1094670510375603
Publication status	Published - Aug-2010

Keywords

analytic models
customer equity
customer management
data mining
decision trees
probability models
word of mouth
WORD-OF-MOUTH
RELATIONSHIP MANAGEMENT
LIFETIME VALUE
BASE ANALYSIS
PARETO/NBD MODEL
CLICKSTREAM DATA
AGGREGATED DATA
CONSUMER
BEHAVIOR
RETENTION

Access to Document

10.1177/1094670510375603

Handle.net

Persistent link

Embargoed Document

Analytics for Customer Engagement
Final publisher's version, 198 KB
Request copy

Cite this

@article{3f7116dfb4ce48c7830a0600b9f9126f,

title = "Analytics for Customer Engagement",

abstract = "In this article, we discuss the state of the art of models for customer engagement and the problems that are inherent to calibrating and implementing these models. The authors first provide an overview of the data available for customer analytics and discuss recent developments. Next, the authors discuss the models used for studying customer engagement, where they distinguish the following stages: customer acquisition, customer development, and customer retention. Finally, they discuss several organizational issues of analytics for customer engagement, which constitute barriers for introducing analytics for customer engagement.",

keywords = "analytic models, customer equity, customer management, data mining, decision trees, probability models, word of mouth, WORD-OF-MOUTH, RELATIONSHIP MANAGEMENT, LIFETIME VALUE, BASE ANALYSIS, PARETO/NBD MODEL, CLICKSTREAM DATA, AGGREGATED DATA, CONSUMER, BEHAVIOR, RETENTION",

author = "Bijmolt, {Tammo H. A.} and Leeflang, {Peter S. H.} and Frank Block and Maik Eisenbeiss and Hardie, {Bruce G. S.} and Aurelie Lemmens and Peter Saffert",

year = "2010",

month = aug,

doi = "10.1177/1094670510375603",

language = "English",

volume = "13",

pages = "341--356",

journal = "Journal of Service Research",

publisher = "SAGE Publications Inc.",

number = "3",

}

TY - JOUR

T1 - Analytics for Customer Engagement

AU - Bijmolt, Tammo H. A.

AU - Leeflang, Peter S. H.

AU - Block, Frank

AU - Eisenbeiss, Maik

AU - Hardie, Bruce G. S.

AU - Lemmens, Aurelie

AU - Saffert, Peter

PY - 2010/8

Y1 - 2010/8

N2 - In this article, we discuss the state of the art of models for customer engagement and the problems that are inherent to calibrating and implementing these models. The authors first provide an overview of the data available for customer analytics and discuss recent developments. Next, the authors discuss the models used for studying customer engagement, where they distinguish the following stages: customer acquisition, customer development, and customer retention. Finally, they discuss several organizational issues of analytics for customer engagement, which constitute barriers for introducing analytics for customer engagement.

AB - In this article, we discuss the state of the art of models for customer engagement and the problems that are inherent to calibrating and implementing these models. The authors first provide an overview of the data available for customer analytics and discuss recent developments. Next, the authors discuss the models used for studying customer engagement, where they distinguish the following stages: customer acquisition, customer development, and customer retention. Finally, they discuss several organizational issues of analytics for customer engagement, which constitute barriers for introducing analytics for customer engagement.

KW - analytic models

KW - customer equity

KW - customer management

KW - data mining

KW - decision trees

KW - probability models

KW - word of mouth

KW - WORD-OF-MOUTH

KW - RELATIONSHIP MANAGEMENT

KW - LIFETIME VALUE

KW - BASE ANALYSIS

KW - PARETO/NBD MODEL

KW - CLICKSTREAM DATA

KW - AGGREGATED DATA

KW - CONSUMER

KW - BEHAVIOR

KW - RETENTION

U2 - 10.1177/1094670510375603

DO - 10.1177/1094670510375603

M3 - Article

VL - 13

SP - 341

EP - 356

JO - Journal of Service Research

JF - Journal of Service Research

IS - 3

ER -

Analytics for Customer Engagement

Abstract

Keywords

Access to Document

Handle.net

Embargoed Document

Fingerprint

Cite this