Digital marketing implementation using python programming for ad campaign optimization and data analysis

Abstract

The use of technology in digital marketing has grown rapidly, especially in terms of data processing and analysis of advertising campaigns. Python, as a powerful programming language, offers an effective solution for optimizing digital marketing campaigns through in-depth data analysis. This research aims to explore the application of Python in digital marketing, especially in advertising campaign optimization and data analysis. Using libraries such as Pandas, Matplotlib, and NumPy, Python enables efficient processing of large data, calculating important metrics such as Cost Per Click (CPC), Cost Per Conversion (CPCo), and Return on Investment (ROI), and generating campaign performance visualizations. The results of this analysis provide deeper insights for advertisers to design more targeted and efficient strategies. Through the application of Python, advertisers can automate the data analysis process, improve calculation accuracy, and make better data-driven decisions in ad budget allocation. This research is expected to contribute to the development of more optimal data-based digital marketing strategies and analysis.