An Analysis of Customer Agrotourism Resort Behaviour based on RFM and Mean Shift Clustering

Abstract

This paper presents an analysis study of customer reservation behavior in Agrotourism N8 based on recency, frequency and monetary (RFM) method. The historical data from January to December 2016 were collected from Rancabali tour and used for RFM analysis. Prior to the RFM analysis, the data were grouped into frequency and monetary using mean shift clustering. This analysis will provide the guideline to Agrotourism N8 to predict the customer needs in the future based on historical data. The RFM method shows that Rancabali tour always crowded with visitors until the end of each month. The highest number of visitors occurred in January, July, and December. Moreover, The highest revenue earned in December. The mean shift shows the income-based cluster by the frequency of customer.