Utilizing Data Analytics to Improve Search Engine Marketing (SEM) Strategy in the Retail Industry - Farizki, Rafi (Journal of Digital Marketing and Search Engine Optimization, 2025)
In the competitive digital era, retail companies face the challenge of optimizing digital marketing strategies to increase visibility and conversions. One increasingly important approach is the integration of data analytics in Search Engine Marketing (SEM) strategies. This research aims to analyze how the implementation of multi-level data analytics can increase the effectiveness of SEM campaigns in retail companies. The method used is descriptive qualitative research with data collection techniques through in-depth interviews, observation, and documentation of retail companies that have implemented data-based SEM strategies. The results show that the comprehensive use of descriptive, predictive, and prescriptive analytics improves SEM performance, which is characterized by an increase in Click-Through Rate (CTR) of 128%, an increase in Conversion Rate of more than 100%, and a decrease in Cost Per Acquisition (CPA) by 42%. The integration of data analytics also encourages faster, more accurate, and responsive decision-making to changes in consumer behavior. In conclusion, the application of data analytics in SEM has a significant impact on improving the effectiveness of digital campaigns and the efficiency of using marketing budgets. The implications of this research emphasize the importance of developing analytics capacity and strengthening data infrastructure in companies to deal with the dynamics of the evolving digital market. This research also contributes to enriching the literature on data-driven marketing strategies in the digital era.