Fajar Ari Sabtono

Project List

• Project 1: Dunhummby Sales Data Analysis
  Background: The project analyzed sales data for the past year to identify trends. View Project
  Overview: A grocery retailer, grappling with diminishing sales amidst tough competition and lack of data-driven insights, undertook an initiative to understand customer behavior and optimize their strategies. They leveraged RFM (Recency, Frequency, Monetary) analysis to segment customers into distinct groups such as "Champions," "Loyal Customers," and "At-Risk Customers," while also analyzing product affinity, basket composition, and category-level performance using Python and SQL. The analysis revealed that "Champions" and "Loyal Customers" were key revenue drivers, whereas "At-Risk" customers, despite their large numbers, contributed minimally. Insights from product affinity analysis highlighted cross-selling and up-selling opportunities. Consequently, the retailer implemented targeted promotions for "Champions," personalized offers for "Loyal Customers," and re-engagement strategies, including loyalty programs and personalized promotions, for "At-Risk" customers, to increased sales, improved customer retention.
• Project 2: Quick Commerce EDA
  Background: Dashboard in funnel analysis of customer behaviour quick commerce industry. View Project
  Overview: Indonesia's quick commerce market is booming, driven by increasing internet penetration, a large young population, and a strong consumer demand for speed and convenience, intensifying competition among both new and established e-commerce players. The objective was to comprehensively analyze this market, identifying its key growth drivers, competitive landscape, and future trends, to provide actionable strategies for success. Performing a detailed market analysis, covering market size, growth drivers, and a competitive assessment of major players like GrabMart, GoMart, and Astro, while also integrating crucial consumer behavior insights such as the preference for same-day delivery and the impact of promotions. The analysis projected the Indonesian quick commerce market to reach $1.8 billion by 2027 with a 15% CAGR, identifying key success factors as optimizing delivery times, efficient inventory management, and offering competitive pricing and promotions. The market trend points to an increased demand for immediate delivery of groceries and essentials, emphasizing the critical role of dark stores and micro-fulfillment centers. Strategic recommendations include focusing on niche markets, expanding product categories, and leveraging data analytics for personalized customer experiences.
• Project 3: Loan Analysis
  Background: Loan performance analysis of customer behaviour shifting. View Project
  Overview: RevoFin sought to improve strategic decision-making and business performance through real-time data analysis. Facing a Q4 2022 revenue decline, high operational costs, and questions about credit card unit profitability, their objective was to increase revenue, manage costs efficiently, and improve product utilization. Through analysis of financial performance metrics like Gross Profit, Net Profit, Operational Expense, Customer Acquisition Cost, and Customer Retention Rate, and after data cleaning and visualization, they found a significant decrease in profits and a sharp increase in operational expenses in Q4 2022. The credit card business unit was identified as the most profitable, while other units suffered from high customer acquisition costs. Recommendations included optimizing credit card interest rates, enhancing customer retention through engagement, and potentially increasing investment in the highly profitable credit card business.
• Project 4: RevoMedika HR Analysis
  Background: Monitoring dashboard for Hasna Medika HR Performance. View Project
  Overview: RevoMedika undertook an analysis of its HR performance and customer demographics to bolster strategic decision-making and service improvement. The core objective was to pinpoint hiring and resignation trends, understand employee demographics (composition and age), and analyze revenue across business units, by disease severity, and customer age groups, culminating in actionable recommendations. The analysis revealed a hiring surge since 2021, indicating expansion, with a slight rise in resignations from 2023. It highlighted a need for additional healthcare and non-healthcare support staff per doctor and noted that the majority of employees were young (20-30), potentially lacking extensive experience. Revenue analysis showed the Pharmacy business unit as the most productive, most customers presenting with non-severe conditions, and a significant portion of customers being aged 46 and above. Based on these insights, recommendations included offering tiered pricing for loyal, multi-service customers, launching campaigns focused on heart health given the prevalence of non-severe conditions, and tailoring campaign methods for different age demographics.
• Project 5: Medical Services Analysis
  Background: RevoMedika Monitoring dashboard for prescription efficiency to BPJS patiens. View Project
  Overview: RevoMedika sought a real-time, data-driven system to analyze the efficiency of its outpatient BPJS prescription services for improved strategic decision-making. The project aimed to identify service profitability, monitor repeat patient trends, manage pharmacy costs, analyze BPJS patients, and integrate doctor prescriptions with pharmacy productivity. Through data cleaning, metric selection, and data exploration/visualization using Python and Power BI, the analysis revealed that certain doctors, notably at the highly profitable Cardiac Clinic in Kuningan, significantly contribute to profit, while others, particularly some Cardiac Polyclinic doctors, are unprofitable due to inefficiencies. It was also found that total prescriptions don't always correlate with cost, with the Kuningan branch and JKN drugs driving most drug costs, and Nitrokaf and Concor dominating prescription expenses, with nearly balanced costs for chronic and non-chronic conditions. Recommendations included limiting frequent patient visits, evaluating unprofitable services, and re-evaluating BPJS policy changes.