Industrial Marketing Strategy Formulation Based on RFM-Data Analytics and Fuzzy Database

Customer behaviour in purchasing products at a retail store could be analysed from the pattern of the product purchase data. However, the data for the analysis must be large in size so that the pattern of the data is stable and truly reflects customer behaviour. This study combined a purchasing product analysis method: Recency, Frequency, and Monetary (RFM) with the fuzzy SQL. The RFM method produces customer clusters as a basis to develop marketing strategy by generalising customer profile in each cluster. However, this general marketing strategy might be not suitable for customers from other clusters, especially who fall in around cluster borders area. A fuzzy database was used to develop a better marketing strategy, especially for the customers who lay around the border area. The fuzzy database model is built by creating fuzzy-SQL which generated views in the database which the data could be updated upon data retrieval. Results show that based on marketing expert’s justification, the proposed RFM technique could be used as the basis for customers analysis-based marketing, while the fuzzy-SQL could encourage more customers who have similar behaviour to make purchases.