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Towards Improving E-commerce Users Experience Using Personalization & Persuasive Technology

Author:

Ifeoma AdajiAuthors Info & Claims

UMAP '17: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization

Pages 318 - 321

https://doi.org/10.1145/3079628.3079707

Published: 09 July 2017 Publication History

Abstract

With the increase in the number of e-commerce companies over the last decade, there is stiffer competition for e-businesses to win and retain customers. Companies have to give clients reasons to shop with them and become return customers. The use of personalization strategies and persuasive technology have been identified as means through which e-businesses can engage their clients and give them a unique shopping experience. To con-tribute to ongoing research in personalization and persuasive technology in e-commerce, my thesis proposes a framework that can create a personalized shopping experience for clients using the consumers' personality and shopping type. This paper presents the results of the first stage of my research which is a user study carried out on 324 e-commerce shoppers to identify the persuasive strategies and its implementation in an e-commerce site, Amazon, and to evaluate the persuasiveness of these strategies to consumers. The result of this thesis can contribute to ongoing research in development of personalization and persuasive strategies that work in e-commerce especially for new companies.

References

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Ifeoma Adaji and Julita Vassileva. 2017. Perceived Effectiveness, Credibility and Continuance Intention in E-commerce. A Study of Amazon. In Proceedings of 12th International Conference on Persuasive Technology.

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Cited By

K K SNarayan S VK S M(2024)Applications of Artificial Intelligence in E-Commerce – From Clicks to ConvictionsAsian Journal of Management10.52711/2321-5763.2024.00032(205-210)Online publication date: 21-Jun-2024
https://doi.org/10.52711/2321-5763.2024.00032
Alslaity AChan GOrji R(2023)A panoramic view of personalization based on individual differences in persuasive and behavior change interventionsFrontiers in Artificial Intelligence10.3389/frai.2023.11251916Online publication date: 29-Sep-2023
https://doi.org/10.3389/frai.2023.1125191
Nti Koranteng FBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Personalizing Persuasive Principles to Improve CredibilityProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3534359(331-334)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3534359
Show More Cited By

Index Terms

Towards Improving E-commerce Users Experience Using Personalization & Persuasive Technology
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User models

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Information

Published In

cover image ACM Conferences

UMAP '17: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization

July 2017

420 pages

ISBN:9781450346351

DOI:10.1145/3079628

General Chairs:
Maria Bielikova
Slovak University of Technology in Bratislava, Slovakia
,
Eelco Herder
L3S Research Center, Germany and Radboud Universiteit Nijmegen, The Netherlands
,
Program Chairs:
Federica Cena
University of Torino, Italy
,
Michel Desmarais
Polytechnique University, Montreal, Canada

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 09 July 2017

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NSERC

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UMAP '17

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UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization

July 9 - 12, 2017

Bratislava, Slovakia

Acceptance Rates

UMAP '17 Paper Acceptance Rate 29 of 80 submissions, 36%;

Overall Acceptance Rate 162 of 633 submissions, 26%

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UMAP '25

Sponsor:
sigchi
sigchi

33rd ACM Conference on User Modeling, Adaptation and Personalization

June 16 - 19, 2025

New York City , NY , USA

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Citations

Cited By

K K SNarayan S VK S M(2024)Applications of Artificial Intelligence in E-Commerce – From Clicks to ConvictionsAsian Journal of Management10.52711/2321-5763.2024.00032(205-210)Online publication date: 21-Jun-2024
https://doi.org/10.52711/2321-5763.2024.00032
Alslaity AChan GOrji R(2023)A panoramic view of personalization based on individual differences in persuasive and behavior change interventionsFrontiers in Artificial Intelligence10.3389/frai.2023.11251916Online publication date: 29-Sep-2023
https://doi.org/10.3389/frai.2023.1125191
Nti Koranteng FBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Personalizing Persuasive Principles to Improve CredibilityProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3534359(331-334)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3534359
Mongadi JVan Biljon JVan der Merwe R(2022)Persuasive technology and user experience design guidelines to motivate users for autonomous learning on a digital learning platform in the context of a corporate environment in South Africa2022 Conference on Information Communications Technology and Society (ICTAS)10.1109/ICTAS53252.2022.9744690(1-6)Online publication date: Mar-2022
https://doi.org/10.1109/ICTAS53252.2022.9744690
Arshad UYasir TShakeel T(2021)Web Usability and User Experience for Pakistani E-commerce websites2021 International Conference on Innovative Computing (ICIC)10.1109/ICIC53490.2021.9693036(1-7)Online publication date: 9-Nov-2021
https://doi.org/10.1109/ICIC53490.2021.9693036
Adib AOrji R(2021)A Systematic Review of Persuasive Strategies in Mobile E-Commerce Applications and Their ImplementationsPersuasive Technology10.1007/978-3-030-79460-6_18(217-230)Online publication date: 23-Jun-2021
https://doi.org/10.1007/978-3-030-79460-6_18
Sharma SMahajan SRana V(2018)A semantic framework for ecommerce search engine optimizationInternational Journal of Information Technology10.1007/s41870-018-0232-yOnline publication date: 31-Jul-2018
https://doi.org/10.1007/s41870-018-0232-y

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