The development of software-defined networking (SDN) and sentiment analysis-based marketing is of special significance to the realization of efficient, customer-centric retail marketing strategies. This study aims to develop a comprehensive evaluation framework to evaluate the factors that influence the intention of using SDN-driven sentiment analysis in retail marketing, combining the variables found in the Technology Acceptance Model (TAM) with other external variables such as real-time data processing, adaptability and customization, predictive insights, security and privacy compliance, and marketing performance efficiency. To obtain an accurate estimate, we propose a hybrid analytical approach based on the Analytic Hierarchy Process (AHP) and sentiment analysis techniques. Data compiled from retail companies in diverse regional markets are used to test the formulated hypotheses. This article first analyzes the structural components of SDN-integrated marketing frameworks, studies the moderating effect of customer sentiment insights on the level of personalization of marketing campaigns, and analyzes the direct effect of real-time data analytics on the effectiveness of retail marketing strategies. The results of this study reflect what technological and consumer-driven factors should be considered and how they are interwoven in marketing decision-making. The results of the combined SDN and sentiment analysis approach also provide a reference for further investigation on the long-term adoption and evolution of data-driven retail marketing under the background of digital transformation and competitive market dynamics. Hence, we may conclude that our proposed framework deserves more empirical validation and industry-wide implementation.