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AI software for personalized marketing automation in SMEs: Enhancing customer experience and sales

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Wagobera Edgar Kedi 1, *, Chibundom Ejimuda 2, Courage Idemudia 3 and Tochukwu Ignatius Ijomah 4

1 Senior Software Engineer - Hubspot Inc, USA.
2 Software Engineer, Boston, MA, USA.
3 Independent Researchers, London, ON, Canada.
4 Independent Researcher, Australia.

Review Article
 

World Journal of Advanced Research and Reviews, 2024, 23(01), 1981–1990
Article DOI: 10.30574/wjarr.2024.23.1.2159
DOI url: https://doi.org/10.30574/wjarr.2024.23.1.2159

Received on 08 June 2024; revised on 18 July 2024; accepted on 20 July 2024

This review paper explores the role of AI software in personalized marketing automation and its impact on customer experience and sales in Small and Medium-sized Enterprises (SMEs). By examining key AI technologies such as machine learning, natural language processing, and predictive analytics, the paper highlights how these tools enable businesses to deliver personalized content and recommendations, enhancing customer engagement and retention. The study also discusses the significant improvements in sales performance and return on investment (ROI) that SMEs can achieve through AI-driven marketing strategies. It includes case examples of successful implementations and outlines emerging trends and future opportunities for leveraging AI. The paper concludes with implications for SMEs and recommendations for future research, emphasizing the need for ongoing innovation and ethical considerations in AI adoption.

AI in Marketing; Customer Experience; SMEs; Sales Performance; Predictive Analytics

https://wjarr.co.in/sites/default/files/fulltext_pdf/WJARR-2024-2159.pdf

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Wagobera Edgar Kedi, Chibundom Ejimuda, Courage Idemudia and Tochukwu Ignatius Ijomah. AI software for personalized marketing automation in SMEs: Enhancing customer experience and sales. World Journal of Advanced Research and Reviews, 2024, 23(01), 1981–1990. Article DOI: https://doi.org/10.30574/wjarr.2024.23.1.2159

Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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