Authors:
Thet Htar Shwe Sin Myint, Mya Thida Aung, Thin Zar Aung, Hlaing Htake Khaung Tin, Chan Chi-Ming, Lee Ka-Yan
Addresses:
Faculty of Information Science, University of Information Technology, Yangon, Yangon Region, Myanmar. Department of Trading, Harbour Trade Ltd., Trading Tower, Kowloon Bay, Hong Kong. Department of Trading, Golden Lion Trading Co., To Kwa Wan, Kowloon City, Hong Kong.
Abstract:
Principles of marketing have consistently progressed from classical marketing oriented towards products to marketing oriented towards customers and technologies. Problems related to understanding consumer needs, branding and managing long-term relationships continue to arise in today's highly competitive digital environment. This research aims to develop a marketing strategy framework based on data analysis, integrating traditional marketing principles such as market segmentation, targeting, positioning, the marketing mix, customer relationship management and brand equity. While building the framework, the research will examine how modern digital technologies and techniques enhance marketing decision-making and customer engagement. The study will use a quantitative methodology, drawing on survey data from consumers and marketing professionals. The research model focuses on the relationships among marketing strategy implementation, digital marketing capabilities, customer engagement, brand perceived value and purchase intentions. Structural Equation Modeling would be used to test the framework and relationships between constructs. The research makes contributions to marketing theory by extending classical marketing principles to the digital environment. The research also offers practical insights into improving customer experience and promotion, and into gaining competitive advantage through data-driven marketing decisions.
Keywords: Customer Relationship Management; Brand Equity; Customer Engagement; Perceived Brand Value; Purchase Intention; Data-Driven Marketing; Traditional Marketing.
Received on: 17/04/2025, Revised on: 28/06/2025, Accepted on: 11/08/2025, Published on: 05/06/2026
DOI: 10.64091/ATITP.2026.000333
AVE Trends in Intelligent Technoprise Letters, 2026 Vol. 3 No. 2 , Pages: 77-88