Stakeholder Identification Strategies in Social Media Marketing: A Qualitative Study in the Telecommunications Sector

Social media marketing allows businesses to reach a wide audience and encourage direct interaction between brands and consumers, facilitating two-way communication and relationship building. This approach not only lowers the overall cost of marketing through advanced targeting capabilities, but also allows companies to deliver personalized content to specific demographics, interests and behaviors. However, in order to optimize customer service and accurately measure results, the benefits of social media marketing should be understood in the context of stakeholders, the individuals or groups who have a vested interest in the success or failure of a business. These stakeholders include employees, customers, investors, suppliers, communities and government agencies. While it is often easy for companies to identify their key stakeholders, this process can be more challenging for third parties. We argue that thematic analysis (TA) can be used to identify companies' key stakeholders, as the case study of three Azerbaijani telecommunications companies shows. We focused on social media content explicitly aimed at stakeholders on Facebook and published by mobile operators, in particular corporate social responsibility (CSR) messages. Using text-based and computer-assisted methods, we reduced large data sets to manageable chunks of qualitative data representing specific stakeholder groups as reflected in the companies' social media communications. In our analysis of 1,428 Facebook posts between 2017 and 2024, we identified eleven key stakeholder groups and examined in detail how these groups were distributed across the three mobile operators. Our text-based analysis revealed that children and younger generations were at the center of marketing efforts on social media, while retail and corporate customers were the least directly targeted. Through qualitative coding, we also identified key thematic connections to each stakeholder group through a co-occurrence analysis or overlap maps. In addition, we have made recommendations for stakeholder identification based on the data collected from social media photos and user comments. We believe that our findings will help researchers and practitioners who have limited access to sentiment analysis or advanced data analysis to identify stakeholders using publicly available social media data.