A Study on Online Advertising Data Collection Method and Effectiveness Analysis based on Real Search Activities

This study presents a data-driven approach to evaluating the effectiveness of online advertising media by incorporating actual user search behavior, addressing the limitations of existing methods that depend solely on platform-provided data. As online advertising continues to grow and the distribution of information becomes increasingly complex due to the rise of user-generated content (UGC), accurately assessing media performance has become critical. Focusing on Naver, which accounts for over 70% of the Korean search engine market, the study establishes a comprehensive data collection framework encompassing structured, semi-structured, and unstructured data. A calculation formula was developed to quantify the exposure rankings of various advertising media by reflecting user behavior patterns and search logic. These exposure scores were then analyzed through multiple regression to determine their influence on actual customer inflow. The results enable advertisers to make more informed decisions regarding media selection, strategy development, and budget allocation based on the measurable impact of each advertising medium.