Tableau-Based Business Intelligence Analysis For the 4P Strategy and Product Sales KPIs in Vending Machines at Minori Group - Sulaeman, Lambok Rommy; Kumoro, Chowal Jundy; Maulana, Syaban; Rabbani, Davina Clarissa (Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET), 2025)
This study aims to analyze the application of Business Intelligence (BI) using Tableau in supporting data-driven decision making in the marketing mix strategy (4Ps) and Key Performance Indicators (KPIs) for vending machine product sales at Minori Group. With the increasing need for efficiency and competition in the South Cikarang industrial area, Minori Group faces challenges in integrating marketing and sales data scattered across various sources. The research method used is a descriptive quantitative approach with the following stages: data collection from vending machine applications, data cleaning using Excel, integration into Tableau for visual analysis, interpretation of visualization results, and preparation of strategic recommendations. The results show that visualization with Tableau is able to provide a comprehensive picture of product performance based on the aspects of Product, Price, Place, and Promotion. The main findings show that inconsistent product placement per slot (BIN) causes sales analysis to be less accurate, while KPI calculations reveal significant variations in performance between products. Tableau has proven to be effective in helping management identify sales patterns, high-performing products, and areas that need to be optimized through promotional strategies and slot rearrangement. The integration of Marketing Mix theory, Business Intelligence, and Technology Acceptance Model (TAM) confirms that Tableau not only serves as a visualization tool, but also as a strategic platform in building a data-driven organizational culture. The implementation of BI through Tableau is expected to increase marketing effectiveness, operational efficiency, and company profitability.