An effective marketing strategy is a method to identify the customers well. One of methods by performing customer segmentation. This study provided an illustration segmentation based on RFM (Recency, Frequency, Monetary) analysis using machine learning clustering that can be combined with demography, geography, and habit through data warehouse-based business intelligence. The purpose classifyin...

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 re...

Avana Indonesia is a social commerce startup headquartered in Malaysia. Wanting to expand their business and enter the Indonesian market, they still don't have best marketing strategy place, so service sales deal not enough. That's why we need that focuses on customers with customer relationship management, one of which segmentation. Customer segmentation can be done by implementing data mining...

Abstract Digitalization allows retailers to target customers with personalized promotions when they enter the store. Although traditional promotional retailer objectives, such as store visit, become obsolete once shopper is already in store, still tend based on indicators that drive recency, frequency, and monetary value (RFM). In order improve efficiency, authors propose targeting shoppers inf...

Since the increased importance is placed on customer equity in today’s business environment, many firms are focusing on the notion of customer loyalty and profitability to increasing market share. Building successful customer relationship management (CRM), a firm starts from identifying customers’ true value and loyalty since customer value can provide basic information to deploy more targeted ...

Target selection in direct marketing is an important data mining problem for which several modeling techniques can be used. Several data mining techniques have been applied in the last years to target selection. Logistic regression, neural networks, decision trees and fuzzy modeling methods are the most utilized techniques. However, they have never been explicitly compared up to know. This pape...

Product recommendation is a business activity that is critical in attracting customers. Accordingly, improving the quality of a recommendation to fulfill customers’ needs is important in fiercely competitive environments. Although various recommender systems have been proposed, few have addressed the lifetime value of a customer to a firm. Generally, customer lifetime value (CLV) is evaluated i...

<span lang="EN-US">We proposed an approach of retailer segmentation using a hybrid swarm intelligence algorithm and recency frequency monetary (RFM)-location model to develop tailored marketing strategy for pharmacy industry distribution company. We used sales data plug it into MATLAB implement ant clustering K-means, then the results were analyzed RFM-location calculate each clusters’ cu...

RFM and CLV: Using Iso-value Curves for Customer Base Analysis We present a new model that links the well-known RFM (recency, frequency, monetary value) paradigm with customer lifetime value (CLV). While previous researchers have connected the two conceptually, none has presented a formal model that requires nothing more than RFM inputs to make specific lifetime value projections for a set of c...

This paper proposes a new weighted mining frequent pattern based on customer’s RFM(Recency, Frequency, Monetary) score for personalized u-commerce recommendation system under ubiquitous computing. An existing recommendation system using traditional mining has the problem, such as delay of processing speed from a cause of frequent scanning a large data, considering equal weight value of every it...