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Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing
Abstract
This article explores the role of artificial intelligence (AI) in aiding personalized engagement marketing—an approach to create, communicate, and deliver personalized offerings to customers. It proposes that consumers are ready for a new journey in which AI is a tool for endless options and information that are narrowed and curated in a personalized way. It also provides predictions for managers regarding the AI-driven environment on branding and customer management practices in both developed and developing countries.
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“Kumar, V. et al. [8] Businesses and human civilization have been interdependent for a very long time.”
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“Farquad et al. (2012) identifient l’apport de la technologie en matière de CRM. Kumar et al. (2019) étudient comment l’IA favorise l’engagement du client.”
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Jhaveri, M., Chirputkar, A., & Ashok, P. (2023) · International Conference on Innovative Data Communication Technologies and Application (ICIDCA) · doi:10.1109/icidca56705.2023.10100132 · Cited by 13
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BackgroundMethodApplying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms
Gallego, V., Lingan, J., Freixes, A., et al. (2024) · Information · doi:10.3390/info15070368 · Cited by 13
“In non-digital contexts, such as Starbucks’ use of predictive analytics, the technology is applied to tailor marketing offers and product recommendations at an individual level [40].”
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Salameh, R. S., & Lutfi, K. M. (2021) · Accounting · doi:10.5267/j.ac.2021.2.024 · Cited by 15
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Increasing Customer Engagement in Digital Marketing Campaigns in a Time of AI
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“The major articles like [55] and [78] (see Table 1), explore how these technologies can be used to create personalized customer engagement strategies and derive insights from complex data sets.”
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Metadata
- Authors
- Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J.
- Affiliations
- Georgia State University (US)
- University of Virginia (US)
- Northwestern University (US)
- Venue
- California Management Review
- Publisher
- SAGE Publications
- Published
- 2019-07-04
- Volume
- 61
- Issue
- 4
- Pages
- 135-155
- ISSN
- 0008-1256 (ISSN-L)
- 2162-8564
- OpenAlex
- W2953773016
- Cited by
- 797
- References
- 0
- Citations by year
- 2026: 136 · 2025: 154 · 2024: 208 · 2023: 111 · 2022: 76 · 2021: 73 · 2020: 33 · 2019: 4
- FWCI
- 21.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- California Management Review (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
- Keywords
- artificial intelligence, personalized marketing, customer engagement, personalization, customer management, branding, consumer behavior, information curation, AI-driven marketing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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