The purpose of this study is to analyse customer segmentation and capable-to-promise functionality in a demand fulfilment process. This is done through a literature review and a case study, the case showing that the company has experienced good results from using an advanced planning system based on customer segmentation and capable-topromise functionality.

The emergence of many business competitors has engendered severe rivalries among competing businesses in gaining new customers and retaining old ones. Due to the preceding, the need for exceptional customer services becomes pertinent, notwithstanding the size of the business. Furthermore, the ability of any business to understand each of its customers’ needs will earn it greater leverage in pro...

Market segmentation is critical for a good marketing and customer relationship management program. Traditionally, a marketer segments a market using general variables such as customer demographics and lifestyle. However, several problems have been identified and make the segmentation result unreliable. This paper develops a novel market segmentation methodology based on product specific variabl...

Recommendation and repurchase intentions are the two most important dimensions of customer loyalty. Latent satisfaction thresholds at the individual level, if obtained, can function as an additional valid and effective criterion to satisfaction ratings in determining customer behavior. Hence, customer segmentation based on these thresholds can help firms optimize their resources to improve cust...

Customer behavior modeling is important for businesses in order to understand, attract and retain customers. It is critical that the models are able to track the dynamics of customer behavior over time. We propose FC-CSM, a Customer Segmentation Model based on a Fragmentation-Coagulation process, which can track the evolution of customer segmentation, including the splitting and merging of cust...

Using the customer relationship management perspective to investigate customer behavior, this study differentiates between customers through customer segmentation, tracks customer shifts from segment to segment over time, discovers customer segment knowledge to build an individual transition path and a dominant transition path, and then predicts customer segment behavior patterns. By using real...

One of the most well-studied problems in data mining is mining for association rules. There was also research that introduced association rule mining methods to conduct classification tasks. These classification methods, based on association rule mining, could be applied for customer segmentation. Currently, most of the association rule mining methods are based on a supportconfidence structure,...

A huge number of customer data was collected by using of information technology in healthcare context. It is very important for healthcare providers to analyze this type of big data following the logic of customer relationship management. So here we propose an integration framework which can realize the customer segmentation and customer churn prediction together. To efficiently segment the cus...