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Measuring Brand Performance With AI Tools
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Author(s): Ansuman Samal (Siksha 'O' Anusandhan University, India), Jajjara Bhargav (Chalapathi Institute of Engineering and Technology, India), Manikandan S. K. (Velalar College of Engineering and Technology, India), P. Selvakumar (Nehru Institute of Technology, India), Mohit Sharma (Maharshi Dayanand University, India)and Manjunath T. C. (Rajarajeswari College of Engineering, India)
Copyright: 2025
Pages: 24
Source title:
Strategic Brand Management in the Age of AI and Disruption
Source Author(s)/Editor(s): Zahid Hussain (Khadim Ali Shah Institute of Technology, Karachi, Pakistan), Mohamad-Noor Salehhuddin Sharipudin (Universiti Putra Malaysia, Malaysia), Ahmad Albattat (Management and Science University, Malaysia)and Arman Khan (Shaheed Benazir Bhutto University, Pakistan)
DOI: 10.4018/979-8-3693-9461-8.ch011
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Abstract
This approach transcends traditional metrics, offering a more nuanced understanding of consumer behavior, brand impact, and market dynamics.Traditional methods often rely on periodic surveys and historical data, which can be limited in scope and slow to capture emerging trends. In contrast, AI systems can continuously ingest data from diverse sources, including social media, online reviews, and sales transactions, enabling brands to gain immediate and comprehensive insights into their performance. This involves natural language processing (NLP) techniques that interpret the emotional tone and context of written content. For example, an AI system might detect a surge in positive sentiment following a successful marketing campaign or identify emerging issues from negative feedback before they escalate. This real-time analysis allows brands to respond more swiftly and effectively to changes in public perception. This enables brands to tailor their strategies with greater precision, targeting specific segments with personalized messages and offers.
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