11th International Conference on ICTIS

Authors - Purva Trivedi, Arun Parakh, Shurbhit Surage
Abstract - Awareness regarding consumer sentiments will benefit a business en tity and/or a company in making their marketing strategies more effective and engaging in the current digital marketing context. In traditional marketing sce narios, since there is a lack of actual emotional aspect in expressing views in real time contexts, it has always been challenging for a business to perform a signifi cant adjustment in their marketing campaigns and achieve a greater success rate. The proposed idea focuses on AI and ML-based approaches for sentiment analy sis in digital marketing. The framework is made up of seven core steps: data collection, preprocessing and data cleaning, sentiment analysis models, feature extraction and model train ing, sentiment classification and analysis, insights and decision-making, and ap plication in digital marketing. From social media to e-commerce reviews to online discussions, consumer sentiment data comes from many digital sources. The text for analysis is standardized, and noise is cleaned in data prepara tion. Then, apart from other artificial intelligence-based sentiment classification models, sentiments are classified as positive, negative, or neutral using lexicon based, machine learning, and deep learning approaches. The learned knowledge enables businesses to react dynamically to consumer sentiment, target advertise ments, and adjust marketing strategies. Businesses will be able to conduct more profitable promotions, communicate with customers better, and monitor real-time sentiment through this AI-driven sentiment analysis platform. The paper emphasizes the benefit of incorporating artificial intelligence in decision-making within digital marketing, even in ad dressing issues like ambiguous sentiment expression management and multi-lan guage data. This paper provides a strategic way towards maximum customer in teraction and brand loyalty and also emphasizes the need for sentiment analysis that is sustained by available data in modern digital marketing.