Customer feedback is used to understand customer requirements. Early design phases require the consideration of items including manufacturing, the environment, and sustainability management. Therefore, it is crucial that eco-efficiency is taken into account in the early design phases. Traditionally, eco-efficiency is considered only in terms of eco-design issues, not customer requirements based...

Due to competitive environment, companies want to create a durable relationship with their customers. Building effective customer relationship management, companies should estimate customer lifetime value (CLV). CLV is normally calculated in terms of recency, frequency and monetary (RFM) variables. Allocating resource to customers’ segments regarding to communication channel based on CLV can be...

email marketing is increasingly recognized as an effective internet marketing tool. in this study, a questionnaire is constructed and distributed to a sample of 146 prospects of aditi technologies to find the factors associated with higher response rates. the collected data is analyzed using factor analysis and the 11 factors, from line, subject line, personalization of the subject line, timing...

This paper deals with an overview of predictive modeling approaches adopted by marketers to identify segments in the target market which would have the largest response rates pertaining to a certain product or service being offered. The three approaches in the predictive modeling, which have been discussed are Heuristic approach, Statistical approach and Data Mining approach. However, with refe...

Nowadays, marketing serves the purpose of maximizing customer lifetime value (CLV) and customer equity, which is the sum of the lifetime values of the company’s customers. But, CLV calculation encounters some difficulties which limit the usage of this technique. Nonetheless, companies looking for methods to know how to calculate their customers’ CLV. In this paper, fuzzy classification rules we...

The aims of this research was to identify prospective customers by conducting customer segmentation based on recency, frequency, monetary (RFM) values and demographic variables. step were selected the data normalized. normalized clustered using density spatial clustering applications with noise (DBSCAN) algorithm. k-dist graph utilized RStudio tools best for epsilon MinPts. outcome utilizing 0....

Email marketing is increasingly recognized as an effective Internet marketing tool. In this study, a questionnaire is constructed and distributed to a sample of 146 prospects of Aditi Technologies to find the factors associated with higher response rates. The collected data is analyzed using Factor Analysis and the 11 factors, From Line, Subject Line, Personalization of the subject line, Timing...

a r t i c l e i n f o Keywords: Customer response predictive model Knowledge-based marketing RFM Neural networks Decision tree models Logistic regression Decision support techniques and models for marketing decisions are critical to retail success. Among different marketing domains, customer segmentation or profiling is recognized as an important area in research and industry practice. Various ...

In the field of strategic marketing, recency, frequency and monetary (RFM) variables model has been applied for years to determine how solid a database is in terms spending customer activity. Retailers almost never obtain data related their customers beyond purchase history, if they do, information often out date. This work presents new method, based on fuzzy linguistic 2-tuple definition produ...