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AI-Driven Algorithms for Optimizing Social Media Advertising: Prospects and Challenges
Author(s): Amaresh Jha (University of Petroleum and Energy Studies, India)
Copyright: 2024
Pages: 22
EISBN13: 9798369358443
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Abstract
The social media advertising market is anticipated to witness a surge in ad spending; projections indicate an annual growth rate (CAGR 2023-2028) of 4.31%, leading to a forecasted market volume of US$255.8 billion by the year 2028. AI algorithms can analyze vast amounts of user data to identify patterns and preferences. This study aims to explore the prospects and challenges of using AI-driven algorithms for optimizing social media advertising and also the functions and benefits of five algorithms prominently used in optimizing social media advertising, namely recommendation algorithms, lookalike audience algorithms, A/B testing algorithms, bid optimization algorithms, and ad fraud detection algorithms. The study also aims at analyzing the challenges associated with AI-driven algorithms from the perspective of customer experience.
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