Branding In Digital Transformation: Optimizing Multichannel Marketing Strategies With Big Data And Consumer Behavioral Analytics

Abstract

In the current competitive environment of the digital era, branding has become a key factor for enterprises to maintain their competitive advantage. This study aims to explore how to optimize multichannel marketing strategies using big data and consumer behavior analysis to enhance brand image and brand equity. Using quantitative research methods, this study collects and analyzes consumer behavior data from multiple online and offline channels, including purchase records, website browsing records, and social media interaction data. By applying structural equation modeling and data mining techniques, the study finds that consumers' brand awareness, brand image perception and brand loyalty are significantly affected by multi-channel marketing activities. The results suggest that consistent marketing messaging that integrates online and offline channels is essential for creating a favorable brand image and improving brand equity. In addition, personalized marketing content and precisely targeted ads based on consumer behavioral data also have a positive impact on increasing consumer engagement and brand loyalty. Overall, this study provides empirical evidence to illustrate how branding in the digital era should make use of big data and consumer behavior analysis to optimize multichannel marketing strategies, and provides theoretical guidance and practical suggestions for companies to develop effective branding strategies.