Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda

Douglas Cirqueira; Markus Hofer; Dietmar Nedbal; Markus Helfert; Marija Bezbradica

doi:10.1007/978-3-030-48861-1_8

Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda

Douglas Cirqueira
, Markus Hofer
, Dietmar Nedbal
, Markus Helfert
, Marija Bezbradica

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

45 Citations (Scopus)

Abstract

Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online.

Original language	English
Title of host publication	New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers
Editors	Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras
Publisher	Springer
Pages	119-136
Number of pages	18
ISBN (Print)	9783030488604
DOIs	https://doi.org/10.1007/978-3-030-48861-1_8
Publication status	Published - 2020
Event	8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019 - Würzburg, Germany Duration: 16 Sept 2019 → 16 Sept 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11948 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Workshop

Workshop	8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019
Country/Territory	Germany
City	Würzburg
Period	16.09.2019 → 16.09.2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 12 Responsible Consumption and Production

Keywords

Behavior analytics
Consumer behavior
Data mining
Digital retail
E-commerce
Machine learning
Purchase prediction

Access to Document

10.1007/978-3-030-48861-1_8

Cite this

Cirqueira, D., Hofer, M., Nedbal, D., Helfert, M., & Bezbradica, M. (2020). Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. In M. Ceci, C. Loglisci, G. Manco, E. Masciari, & Z. Ras (Eds.), New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers (pp. 119-136). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11948 LNAI). Springer. https://doi.org/10.1007/978-3-030-48861-1_8

Cirqueira, Douglas ; Hofer, Markus ; Nedbal, Dietmar et al. / Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers. editor / Michelangelo Ceci ; Corrado Loglisci ; Giuseppe Manco ; Elio Masciari ; Zbigniew Ras. Springer, 2020. pp. 119-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{8f84abdcc47642728a9e0b71cb768ccf,

title = "Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda",

abstract = "Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online.",

keywords = "Behavior analytics, Consumer behavior, Data mining, Digital retail, E-commerce, Machine learning, Purchase prediction, Behavior analytics, Consumer behavior, Data mining, Digital retail, E-commerce, Machine learning, Purchase prediction",

author = "Douglas Cirqueira and Markus Hofer and Dietmar Nedbal and Markus Helfert and Marija Bezbradica",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019 ; Conference date: 16-09-2019 Through 16-09-2019",

year = "2020",

doi = "10.1007/978-3-030-48861-1\_8",

language = "English",

isbn = "9783030488604",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "119--136",

editor = "Michelangelo Ceci and Corrado Loglisci and Giuseppe Manco and Elio Masciari and Zbigniew Ras",

booktitle = "New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers",

address = "Germany",

}

Cirqueira, D, Hofer, M, Nedbal, D, Helfert, M & Bezbradica, M 2020, Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. in M Ceci, C Loglisci, G Manco, E Masciari & Z Ras (eds), New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11948 LNAI, Springer, pp. 119-136, 8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019, Würzburg, Germany, 16.09.2019. https://doi.org/10.1007/978-3-030-48861-1_8

Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. / Cirqueira, Douglas; Hofer, Markus; Nedbal, Dietmar et al.
New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers. ed. / Michelangelo Ceci; Corrado Loglisci; Giuseppe Manco; Elio Masciari; Zbigniew Ras. Springer, 2020. p. 119-136 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11948 LNAI).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

TY - GEN

T1 - Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda

AU - Cirqueira, Douglas

AU - Hofer, Markus

AU - Nedbal, Dietmar

AU - Helfert, Markus

AU - Bezbradica, Marija

PY - 2020

Y1 - 2020

N2 - Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online.

AB - Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online.

KW - Behavior analytics

KW - Consumer behavior

KW - Data mining

KW - Digital retail

KW - E-commerce

KW - Machine learning

KW - Purchase prediction

KW - Behavior analytics

KW - Consumer behavior

KW - Data mining

KW - Digital retail

KW - E-commerce

KW - Machine learning

KW - Purchase prediction

UR - https://www.scopus.com/pages/publications/85085734132

U2 - 10.1007/978-3-030-48861-1_8

DO - 10.1007/978-3-030-48861-1_8

M3 - Conference contribution

SN - 9783030488604

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 119

EP - 136

BT - New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers

A2 - Ceci, Michelangelo

A2 - Loglisci, Corrado

A2 - Manco, Giuseppe

A2 - Masciari, Elio

A2 - Ras, Zbigniew

PB - Springer

T2 - 8th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2019, held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2019

Y2 - 16 September 2019 through 16 September 2019

ER -

Cirqueira D, Hofer M, Nedbal D, Helfert M, Bezbradica M. Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. In Ceci M, Loglisci C, Manco G, Masciari E, Ras Z, editors, New Frontiers in Mining Complex Patterns - 8th International Workshop, NFMCP 2019, held in Conjunction with ECML-PKDD 2019, Revised Selected Papers. Springer. 2020. p. 119-136. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-48861-1_8

Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda

Abstract

Publication series

Workshop

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this