Segmentation Strat Egy of Consumer Interest in Contemporary Coffee Shop Using RFM Model - Passalaras, Raja Aulia; Daulay, Risma Yanti; Heikal, Jerry (Institut Penelitian Matematika Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE), 2024)
Increase customer loyalty by grouping customers into several groups and determining appropriate and effective marketing strategies for each group. Customer segmentation can be done through the clustering method. This research aims to analyze customer Recency, Frequency and Monetary (RFM) from the segmentation results of 5 contemporary coffee shops, namely Janji Jiwa, Kopi Kenangan, Tomoro Coffee, Fore Coffee, and Fami Cafe, from Persona Analysis Research and segmentation of consumer interest in contemporary coffee shops. Previously it could be summarized that cluster 3 or potential customers were the targets of the research by implementing appropriate marketing strategies based on the characteristics and profiles of the respondents. This cluster consists of 31 respondents, most of whom are women aged 24-28 years with a bachelor's degree and work as private employees in Jakarta. Interestingly, cluster 3 is divided between coffee fans and those who don't like coffee. Respondents in this study tended to prefer Tomoro Coffee, while those who didn't like coffee preferred Fami Cafe. In cluster 3, there are 29 people who are active Instagram users. The analysis used includes descriptive analysis where the data used is primary data. The data collection technique used is the observation method and distributing questionnaires to customers who are in cluster 3. The results of the research show that based on the results of the revenue segmentation analysis for the Tomoro Coffee and Fami Cafe coffee shops, it can be concluded that customers in cluster 3 consist of 3 segments. namely recency 3 which consists of 16 active customers who are very loyal and faithful. The strategy to retain these customers is by personalizing customer data to understand product/service shortcomings and knowing customer individual preference needs in order to attract them back. Keywords: Frequency, Monetary, Recency.