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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 et al. (2022) have also further indicated that cloud-based IoT platforms have made it easier for SMEs to access advanced analytics and machine learning features for processing the huge data volumes resulting from IoT devices.”
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“Artificial Intelligence (AI) — the broad concept of computers thinking and executing tasks like humans through software and algorithms — is welcomed across various industries (Kumar et al., 2019).”
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Hoffman, D. L., & Novak, T. P. (2025) · Journal of Product Innovation Management · doi:10.1111/jpim.12767 · Cited by 6
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“Several classic text mining and information extraction studies have been taken into account in this study, integrating machine learning and multiscale modeling and making some recommendations for practical applications (Giordano et al., 2021; Ren et al., 2021; Alber et al., 2019; Kumar et al., 2019; Dong et al., 2016).”
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“According to Kumar et al. [31], artificial intelligence (AI) possesses the capability to tailor services to the specific requirements of individual customers.”
BackgroundAdoption of Smart Speakers for Voice Shopping
Bawack, R. E., Wamba, S. F., & Carillo, K. (2021) · Lecture notes in information systems and organisation · doi:10.1007/978-3-030-87842-9_3 · Cited by 7
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“…in widely-used practical applications such as Spotify's innovative "Discover Weekly" algorithm and eBay's sophisticated predictive modeling systems [13] with notable extensions into healthcare contexts specifically designed for adapting and optimizing medical information delivery mechanisms [14].”
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“Their human-like physical appearance, personality, identity, life history, and even ability to think and perform tasks as humans do are based on the use of computer software and machine learning algorithms, which uniquely distinguish them as AI from humans (Kumar et al. 2019; Robinson 2020).”
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“The deployment of recommendation and persuasive technologies could reduce this negative aspect (Kumar, Rajan, Gupta et al., 2019; Kumar, Rajan, Venkatesan et al., 2019).”
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Random Walk Generation and Classification Within an Online Learning Platform
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Role of Artificial Intelligence in Marketing
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Digital Marketing and Artificial Intelligence
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Artificial Intelligence vs Human in Advertisement Text Writing
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“Kumar et al. (2019) Provide a comprehensive overview of AI applications in digital marketing, highlighting how machine learning models can enhance personalization and customer engagement rates.”
AI ETHICS IN BUSINESS – A BIBLIOMETRIC APPROACH
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“Finally, there is the third category of studies focused on the interaction between business environments that use AI and customers (Kumar et. al., 2019).”
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PAZARLAMADA YAPAY ZEKÂ KAVRAMININ BİBLİYOMETRİK ANALİZİ
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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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