Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms

Ramazan Esmeli; Alaa Mohasseb; Mohamed Bader-El-Den

doi:10.5220/0010176803330340

Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms

Ramazan Esmeli, Alaa Mohasseb, Mohamed Bader-El-Den

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Abstract

Predicting future consumer browsing and purchase behaviour has become crucial to many marketing platforms. Consumer purchase intention is one of the main inputs used as a measurement for consumer demand for new products. In addition, identifying consumers' purchase intent play an important role in recommender systems. In this paper, the effect of using different platforms on users' behaviours is explored. In addition, the effect of users' platforms and their purchase intentions behaviours are investigated. We conduct computational experiments using different machine learning algorithms in order to investigate the using users' operating system and platform types as features. The results showed that the users' purchase intention and behaviours are correlated with these features.

Original language	English
Title of host publication	Proceedings of the 12th International Joint Conference on Knowledge Discovery
Subtitle of host publication	KDIR
Editors	Ana Fred, Joaquim Filipe
Publisher	SciTePress
Pages	333-340
Number of pages	8
Volume	1
ISBN (Print)	9789897584749
DOIs	https://doi.org/10.5220/0010176803330340
Publication status	Published - 12 Nov 2020
Event	12th International Joint Conference on Knowledge Discovery - Duration: 2 Nov 2020 → 4 Nov 2020 http://www.kdir.ic3k.org/

Conference

Conference	12th International Joint Conference on Knowledge Discovery
Abbreviated title	KDIR
Period	2/11/20 → 4/11/20
Internet address	http://www.kdir.ic3k.org/

Keywords

purchase intention
Customer browsing behaviour
Purchase behaviour prediction
noissn

Access to Document

10.5220/0010176803330340

KDIRAccepted author manuscript (Post-print), 174 KB

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Esmeli, R., Mohasseb, A., & Bader-El-Den, M. (2020). Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms. In A. Fred, & J. Filipe (Eds.), Proceedings of the 12th International Joint Conference on Knowledge Discovery: KDIR (Vol. 1, pp. 333-340). SciTePress. https://doi.org/10.5220/0010176803330340

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title = "Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms",

abstract = "Predicting future consumer browsing and purchase behaviour has become crucial to many marketing platforms. Consumer purchase intention is one of the main inputs used as a measurement for consumer demand for new products. In addition, identifying consumers' purchase intent play an important role in recommender systems. In this paper, the effect of using different platforms on users' behaviours is explored. In addition, the effect of users' platforms and their purchase intentions behaviours are investigated. We conduct computational experiments using different machine learning algorithms in order to investigate the using users' operating system and platform types as features. The results showed that the users' purchase intention and behaviours are correlated with these features.",

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Esmeli, R, Mohasseb, A & Bader-El-Den, M 2020, Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms. in A Fred & J Filipe (eds), Proceedings of the 12th International Joint Conference on Knowledge Discovery: KDIR. vol. 1, SciTePress, pp. 333-340, 12th International Joint Conference on Knowledge Discovery, 2/11/20. https://doi.org/10.5220/0010176803330340

Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms. / Esmeli, Ramazan; Mohasseb, Alaa ; Bader-El-Den, Mohamed.
Proceedings of the 12th International Joint Conference on Knowledge Discovery: KDIR. ed. / Ana Fred; Joaquim Filipe. Vol. 1 SciTePress, 2020. p. 333-340.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms

AU - Esmeli, Ramazan

AU - Mohasseb, Alaa

AU - Bader-El-Den, Mohamed

N1 - No embargo No ISSN

PY - 2020/11/12

Y1 - 2020/11/12

N2 - Predicting future consumer browsing and purchase behaviour has become crucial to many marketing platforms. Consumer purchase intention is one of the main inputs used as a measurement for consumer demand for new products. In addition, identifying consumers' purchase intent play an important role in recommender systems. In this paper, the effect of using different platforms on users' behaviours is explored. In addition, the effect of users' platforms and their purchase intentions behaviours are investigated. We conduct computational experiments using different machine learning algorithms in order to investigate the using users' operating system and platform types as features. The results showed that the users' purchase intention and behaviours are correlated with these features.

AB - Predicting future consumer browsing and purchase behaviour has become crucial to many marketing platforms. Consumer purchase intention is one of the main inputs used as a measurement for consumer demand for new products. In addition, identifying consumers' purchase intent play an important role in recommender systems. In this paper, the effect of using different platforms on users' behaviours is explored. In addition, the effect of users' platforms and their purchase intentions behaviours are investigated. We conduct computational experiments using different machine learning algorithms in order to investigate the using users' operating system and platform types as features. The results showed that the users' purchase intention and behaviours are correlated with these features.

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KW - Customer browsing behaviour

KW - Purchase behaviour prediction

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DO - 10.5220/0010176803330340

M3 - Conference contribution

SN - 9789897584749

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EP - 340

BT - Proceedings of the 12th International Joint Conference on Knowledge Discovery

A2 - Fred, Ana

A2 - Filipe, Joaquim

PB - SciTePress

T2 - 12th International Joint Conference on Knowledge Discovery

Y2 - 2 November 2020 through 4 November 2020

ER -

Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms

Abstract

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Keywords

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