Objective: This study focuses on the design and conceptualization of a cross-media marketing process model in the life insurance industry and examines its impact on improving marketing and communication processes. With the rapid growth of digital media, the internet, and social networks, insurance companies need to adopt innovative marketing strategies to enhance customer interactions and increase their market share. The objective of this study is to present a comprehensive and practical model for cross-media marketing in the life insurance industry, assisting organizations in formulating optimal strategies to achieve customer loyalty and enhance marketing efficiency.
Methods: This research employs a qualitative research approach, combining grounded theory analysis and Interpretive Structural Modeling (ISM). Data were collected through semi-structured interviews with industry experts, university professors, and marketing managers of insurance companies. The research sample consisted of 15 experts in the fields of marketing and insurance management, selected using purposive and snowball sampling methods. The collected data underwent open, axial, and selective coding, leading to the development of the final model. Subsequently, ISM was used to determine the relationships between key variables and their hierarchical classification.
 Results: The study's findings indicate that the cross-media marketing process is influenced by various factors classified into five main dimensions. The causal factors include managerial aspects, financial potential, communication potential, customer characteristics, and convenience, which were identified as key elements affecting cross-media marketing. The intervening conditions encompass environmental challenges, technological changes, and legal constraints that may impact the effectiveness of marketing strategies. The contextual conditions involve digital capabilities, communication infrastructure, and the level of customer awareness and knowledge regarding insurance services. Key strategic approaches include business improvement, knowledge development and training, and promoting innovation and creativity, which were identified as the most critical strategies for optimizing cross-media marketing. Finally, the ultimate outcomes include increased customer loyalty, enhanced word-of-mouth and viral advertising, higher brand engagement, and improved customer satisfaction with insurance services.
Conclusions: This study demonstrates that implementing a cross-media marketing model can significantly enhance marketing performance in the life insurance industry. Utilizing digital marketing techniques and integrating multiple communication channels enable insurance companies to optimize customer interactions, gain a deeper understanding of customer needs, and create a better user experience. These strategies lead to increased customer trust, higher market share, and reduced advertising costs compared to traditional marketing methods. Ultimately, the research findings indicate that the success of cross-media marketing implementation depends on data-driven decision-making, optimizing digital infrastructure, and increasing customer awareness of insurance services