Marketing Ads Using Decision Tree Analysis

Abstract

This study aims to analyze the effectiveness of digital marketing advertisements in the fashion industry by applying Decision Tree Analysis to compare the performance of TikTok and Instagram based on engagement rate, conversion rate, and potential purchase outcomes. The research method used is a qualitative approach through documentation and library research methods by collecting and analyzing secondary data from academic journals, statistical reports, and relevant digital marketing sources. The collected data were processed using the Decision Tree Analysis method to identify the most effective social media platform and content format in generating consumer engagement and purchase conversion. The results show that TikTok provides higher purchase potential compared to Instagram despite having a lower engagement rate. Based on the analysis using a fixed 8,000 views comparison, TikTok generated 326 engaged users and 11 estimated purchases, while Instagram posts generated 812 engaged users but only 8 estimated purchases. Furthermore, TikTok achieved a higher conversion rate of 3.40% compared to Instagram’s 1.08%, indicating stronger effectiveness in encouraging direct purchasing behavior. The findings suggest that TikTok is a more suitable platform for businesses aiming to increase sales conversion, while Instagram remains beneficial for improving brand awareness due to its higher engagement performance. In conclusion, Decision Tree Analysis can assist businesses in making data-driven marketing decisions by identifying the most effective advertising platforms and content strategies for optimizing digital marketing performance.

Keywords: Decision Tree Analysis, Digital Marketing, Fashion Industry, Social Media