Indicators for evaluating the efficiency of page management in social networks

Abstract

The purpose of the study is to characterize the features of assessing the effectiveness of maintaining a page in social networks. The object of the study is pages in social networks as a subject of marketing. The methodology of the article involves the use of induction and deduction methods, comparison and systematization, synthesis and analysis, morphological analysis, graphic and tabular methods, and abstract-logical method. The main task of the article is to determine the key indicators of assessing the effectiveness of maintaining a page in social networks. The article considers the process of assessing the effectiveness of maintaining a page in social networks, which is extremely important in the current conditions of rapid digitalization and high competition in the market. The main emphasis is placed on the fact that systematic monitoring and analysis of key indicators allows not only to timely adjust the marketing strategy, but also to plan long-term brand development taking into account the real needs and preferences of the target audience. The article also emphasizes that ignoring the process of assessing effectiveness threatens the loss of competitive advantages, since the dynamics of change in the digital environment is extremely high. Four key performance indicators were identified: reach, engagement level, conversion rate, and retention rate. They provide a wide range of information about brand interaction: from the scale of the impact on the audience to the ability to generate targeted actions and long-term loyalty. The study identified two main effects of evaluation: strategic and tactical. The strategic effect concerns global goals and objectives related to reputation management, long-term planning, and brand development. The tactical effect allows for prompt influence on processes by changing content plans, adjusting advertising campaigns, and quickly responding to consumer needs. Three key areas for improving the evaluation process were also identified: integration of multi-channel analytics, application of modern technologies, including artificial intelligence technologies, and regular revision of performance indicators and their adaptation to current tasks.