Segmenting and Targeting the Potential Markets of a Muslim Fashion Company

The increasing use of technology in the big data world enables companies to use consumers' information, which leads to increased competition in the muslim fashion industry in Indonesia. Muslim fashion business brands need the correct strategy to gain the market. The combination of marketing and data mining is translating consumers' data into marketing strategies. This study selects a muslim fashion company in Indonesia to explore the market segment and target the segment to determine the marketing strategy. The segmentation is based on Length, Recency, Frequency, and Monetary (LFRM) variable. It applies K-means algorithm to cluster consumers and Davies Bouldin (DB) validation index to determine the best K value. Once the cluster is established, the analysis is conducted to find potential customer segments. The main target of the company marketing activities is those potential segments. The study grouped into five clusters of customers. From those five clusters, two clusters are selected as market targets for applying marketing activities.