Marketing Analytics on EAZER's Product Performance

Abstract

This paper analyzes the business performance of EAZER, a retail company specializing in cleaning tools that emphasizes user convenience under the slogan “make your life easier.” The analysis focuses on evaluating the company’s product performance using key business analysis models. Specifically, the RFM (Recency, Frequency, Monetary) model is applied to identify the target product; regression analysis is used to assess sales trends; and correlation and sentiment analysis are conducted to investigate the causes of product returns and customer complaints. Findings reveal that among EAZER’s 13 products, Product 2 dominates in sales and demonstrates significant seasonal fluctuations. RFM analysis indicates a generally consistent customer engagement across products, while return and complaint patterns are concentrated at the product level and exhibit a negative correlation. These insights suggest a need for targeted strategies during low-demand seasons and a more responsive approach to managing negative customer feedback. Recommendations are developed using the 7Ps marketing mix and SMART objective frameworks. They include implementing dynamic promotional strategies during off-peak periods and establishing measurable, data-driven mechanisms to address negative sentiment and improve customer satisfaction. The analysis is based on 2023 data covering sales, returns, and customer complaints, and utilizes multiple statistical tools including t-tests and sentiment classification. Overall, the paper provides actionable insights to enhance EAZER’s performance and competitive standing in the B2C market.