The Timely Product Recommendation Based on RFM Method

The recent study of recommendation systems and RFM method has been applied to analyze customers’ consumption property and the re-purchasing ability. The RFM method employs Recency(R), Frequency(F), and Monetary(M) to measure customers’ consumption loyalty. And the recommendation systems mainly to promote products for increasing profit. However, there are some problems because they ignore the relationship between product property and purchase periodicity. That is to say that the combination of recommendation system and RFM method did not take the customers product-purchasing timing into consideration. If the periodicity of product-demand can be estimated based on each customer’s buying behavior, then the product recommendation at the right timing shall match the buying requirement. This is the reason why the past product recommendation studies have difficulty of increasing the accuracy. To deal with the product periodicity, this research proposes a Timely RFM (TRFM) module which takes product property and purchase periodicity into consideration. This research is intended to (1) analyze different products to each customer’s demands in different times, (2) provide a recommendation mechanism to satisfy customers’ needs, (3) to improve the deficiency of existing combination with recommendation and RFM. To examine the practicability and to validate the method, the experimentation uses the Foodmart2000 database of Microsoft SQL2000 to verify the accuracy of TRFM. The results prove that our proposed method can provide a timely recommendation and creates better results.