Edutech Digital Start-Up Customer Profiling Based on RFM Data Model Using K-Means Clustering

Digital start-up is companies with a high risk because they are still looking for the most fitting business model and right market. The company's growth primary goal of start-up. As newly established company, digital start-ups have one challenge, it ineffectiveness marketing process strategic schemes in terms maintaining customer loyalty, same goes edutech start-ups. Ineffective inefficient plans can waste resources. Hence, method needed to find out optimal solution understanding characteristic. Business Intelligence needed, profiling using transaction data based on RFM (Retency, Frequency, Monetary) K-Means algorithm. In this study, comes from an education platform assisted by STIKOM Bali incubator. Based three metrics, namely Elbow Method, Silhouette Scores, Davis Bouldin Index, sales retency, frequency, monetary be analyzed solution. For case, K = 2 optimum cluster solution, where first who needs more engagement, second best