Advances in Data Analytics for Influencer Marketing: An Interdisciplinary Approach / / edited by Soumi Dutta, Álvaro Rocha, Pushan Kumar Dutta, Pronaya Bhattacharya, Ramanjeet Singh

• Autore: Dutta Soumi
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (434 pages)
• Disciplina: 620.00285
• Soggetto topico: Engineering - Data processing; Computational intelligence; Marketing; Data Engineering; Computational Intelligence
• Altri autori: RochaÁlvaro DuttaPushan Kumar BhattacharyaPronaya SinghRamanjeet
• Nota di contenuto: -- 1: Introduction to Influencer Marketing and Data Analytics. -- 2: The Evolution of Influencer Marketing. -- 3: From Word-of-Mouth to AI-Powered Engagement: The Dynamic Evolution of Influencer Marketing in the Digital Era. -- 4: Revolutionizing Influencer Marketing: Harnessing the Power of Data Analytics and Artificial Intelligence (AI). -- 5: Influencer Marketing Unleashed: Leveraging Data Analytics for Success. -- 6: Data analytics and AI for influencer marketing. -- 7: Interdisciplinary Data Analytics Transforming Influencer Marketing Strategies. -- 8: Influencer Marketing Evolution: Unveiling the Power of Data Analytics and AI for Strategic Campaign Ex-cellence. -- 9: Sustainability and Influencer Marketing: Measuring the Gap between Consumer Attitudes and Purchase Behavior. -- 10: An Audience Threshold in the Millions: Exploring Influencer Marketing Activations Online. -- 11: Metaverse: A New Frontier for Influencer Marketing. -- 12: Influencer Marketing on New Platforms and the Metaverse for Male Grooming Brands. -- 13: Impact of Influencer Marketing through Instagram among Youth: A Study. -- 14: E-commerce Platforms Extend Beyond Sell-ing... A Case Study on India. -- 15: Analyzing the Effectiveness of Influencer Campaigns in Driving Customer Acquisition and Retention: Perspectives from Unilever Pakistan. -- 16: Analysing the impact of hosting influencer giveaways on purchase intention of luxury items by Generation Z. -- 17: Innovative Fusion: Attention-Augmented Support Vector Machines for Superior Text Classification for Social Marketing. -- 18: Fuzzy Artificial Intelligence as a Technique to Find Relative Desirability for Fake Review Detection. -- 19: A Study on the Influence of Artificial Intelligence on Brain Plasticity with Reference to Consumer Behaviour and Workplace Dynamics. -- 20: Influential Asanas: An In-depth Study Exploring the Dynamics of Yoga Influencers. -- 21: Online User Choices Data Analytics and Privacy in Digital Marketing: Legal-Ethical Landscapes in the Digital- Futuristic Arena Projecting Multiple Layers of Artificial Intelligence and Blockchain. -- 22: The pinnacle of influence: unveiling the evolution, global dynamics, and multidisciplinary tapestry of social media influencer marketing (2016-2024).
• Sommario/riassunto: In the ever-evolving landscape of digital marketing, influencer marketing has emerged as a game-changer, captivating audiences and driving brand engagement like never before. However, success in this dynamic field requires more than just intuition—it demands a mastery of data analytics and an interdisciplinary approach. Introducing this groundbreaking book equips marketers, analysts, and business leaders with the tools and strategies to navigate the complexities of influencer marketing with precision and confidence. Written by leading experts in the field, this comprehensive book explores the intersection of data analytics, consumer behavior, and influencer marketing, offering a holistic perspective on this powerful marketing technique. This book equips the readers with the knowledge and tools to stay ahead of the curve and drive unparalleled success in the ever-evolving world of influencer marketing.
• Titolo autorizzato: Advances in Data Analytics for Influencer Marketing: An Interdisciplinary Approach
• ISBN: 3-031-65727-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910882896203321
• Lo trovi qui: Univ. Federico II
• Serie: Information Systems Engineering and Management, . 3004-9598 ; ; 9