Artificial Intelligence Model of the User Patterns and Behaviors Analysis on Social Media to Become Customers in Smart Marketing

Nuanmeesri, Sumitra; Poomhiran, Lap; Sriurai, Wongkot

doi:10.14445/22315381/ijett-v70i10p238

Cited by 1 publication

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“…Similarly, Nuanmeesri et al sought to analyze patterns and behaviors of social media users, aiming to determine the likelihood of these users becoming customers [26]. Their findings showed that a model combining Multi-Layer Perceptron Neural Network and Correlation-based Feature Selection yielded the highest performance, achieving an accuracy rate of 89.80%.…”

Section: Social Media Clustermentioning

confidence: 99%

Artificial Intelligence in Digital Marketing: Insights from a Comprehensive Review

Ziakis,

Vlachopoulou

2023

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Artificial intelligence (AI) has rapidly emerged as a transformative force in multiple sectors, with digital marketing being a prominent beneficiary. As AI technologies continue to advance, their potential to reshape the digital marketing landscape becomes ever more apparent, leading to profound implications for businesses and their digital outreach strategies. This research seeks to answer the pivotal question: “How could AI applications be leveraged to optimize digital marketing strategies”? Drawing from a systematic literature review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, this study has identified 211 pertinent articles. Through a comprehensive bibliometric analysis, the findings were categorized into distinct clusters, namely: AI/ML (Machine Learning) Algorithms, Social Media, Consumer Behavior, E-Commerce, Digital Advertising, Budget Optimization, and Competitive Strategies. Each cluster offers insights into how AI applications can be harnessed to augment digital marketing efforts. The conclusion synthesizes key findings and suggests avenues for future exploration in this dynamic intersection of AI and digital marketing. This research contributes to the field by providing a comprehensive bibliometric analysis of AI in digital marketing, identifying key trends, challenges, and future directions. Our systematic approach offers valuable insights for businesses and researchers alike, enhancing the understanding of AI’s evolving role in digital marketing strategies.

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Section: Social Media Clustermentioning

confidence: 99%