Model of an Information System for Analysis and Evaluation of Advertising in Social Networks

This study examines different models for evaluating advertising effectiveness on social media, focusing specifically on the factors that drive successful campaigns on Facebook. Our analysis revealed shortcomings in three prevalent models frequently used by marketing and SMM professionals when developing ad materials. We determined that the quality of online advertising assessment critically depends on both the volume and the quality of the metrics gathered for analysis. Therefore, the central aim of this research was to create an improved model that overcomes the limitations of existing tools by systematically updating and refreshing data pulled from social media platforms. The paper details the unique features of this new model in comparison to similar programs and provides a thorough analysis of how its components interact, both internally and with external systems. During the model’s development, we identified the key tasks required to build the accompanying application and specified the technologies involved. We outline the model’s core operational principles, which are organized into four main blocks, each handling the processing and analysis of advertising effectiveness metrics. Additionally, we assessed how the proposed model addresses a significant challenge – keeping data from social networks continuously updated – and proposed methods to resolve this. The potential of the developed software to enhance the evaluation of digital advertising strategies was also analyzed, considering its importance across different business sectors and its value for marketers who rely on precise data insights. The application was tested using an active SMM agency’s Facebook account, and its performance in gathering metrics was compared against alternative programs. Future enhancements could include more in-depth analysis of the collected data and expanded features for visualizing the findings.