Analisis Segmentasi Recency dan Customer Value Pada AVANA Indonesia Dengan Algoritma K-Means dan Model RFM (Recency, Frequency and Monetary)

Avana Indonesia is a social commerce startup headquartered in Malaysia. Wanting to expand their business and enter the Indonesian market, they still don't have best marketing strategy place, so service sales deal not enough. That's why we need that focuses on customers with customer relationship management, one of which segmentation. Customer segmentation can be done by implementing data mining process carried out using K-Means clustering algorithm based RFM (Recency, Frequency, Monetary) model. The number clusters determined elbow method. Cluster analysis value recency method reveals active, warm, cold, inactive customers. Then two from frequency (customer value) produce common, ultra-high, low, high clusters.