| dc.contributor.author | Bhuvaneshwar, D. | |
| dc.contributor.author | Amrutha, S. | |
| dc.contributor.author | Niranjana Devi, G. | |
| dc.date.accessioned | 2025-12-16T03:44:11Z | |
| dc.date.available | 2025-12-16T03:44:11Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | http://drr.vau.ac.lk/handle/123456789/1607 | |
| dc.description.abstract | The research examines how Artificial Intelligence (AI) functions as a strategic component in social media marketing approaches. Digital platforms have transformed into powerful marketing ecosystems because AI tools including chatbots and predictive analytics and sentiment analysis and personalized content systems now serve essential roles in processing large datasets and enhancing user engagement. The study ascertains how applications of artificial intelligence affect consumer interactions, satisfaction levels, and the success rates of marketing campaigns. Based on data from 134 respondents, the study employed correlation analysis with SPSS to assess the relationships between AI usage and perceived utility, convenience of use, and marketing outcomes. The research demonstrates that AI usage does not strongly correlate with key performance metrics but requires proper implementation and usability and AI literacy for marketing success. The research demonstrates that AI offers beneficial opportunities to digital marketers yet its achievement depends on proper implementation and training and ethical deployment. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Marketing Management, Faculty of Business Studies, University of Vavuniya | en_US |
| dc.subject | Artificial intelligence | en_US |
| dc.subject | Social media marketing | en_US |
| dc.subject | Customer engagement | en_US |
| dc.subject | Predictive analytics | en_US |
| dc.subject | Chatbots | en_US |
| dc.title | A Study on Effectiveness of AI in Social Media Marketing Strategies | en_US |
| dc.type | Conference abstract | en_US |
| dc.identifier.proceedings | 1st Undergraduate Research Symposium on Marketing (URSM) - 2025 | en_US |