The importance of customer-oriented marketing has increased for companies in recent
decades. With the advent of one-customer strategies, especially in e-commerce, traditional …

For new product development, previous segmentation methods based on demographic,
psychographic, and purchase behavior information cannot identify a group of customers with …

Even though machine learning (ML) applications are not novel, they have gained popularity
partly due to the advance in computing processing. This study explores the adoption of ML …

Big social data and user-generated content have emerged as important sources of timely
and rich knowledge to detect customers' behavioral patterns. Revealing customer …

Providing the right products, at the right place and time, according to their customer's
preferences, is a problem-seeking solution, especially for companies operating in the retail …

Nowadays, every business focuses on customer relationship management (CRM) to deliver
their customers better services and to establish a competitive advantage over their …

Previous research on RFM (recency, frequency, and monetary value) models focused on
only one type of user behavior data, ie, the purchase behavior, without considering the …

The recency/frequency/monetary value (RFM) segmentation framework remains a mainstay
in the retailing industry to quantify consumer values. However, the RFM model does not …

In recent years, as digital transformation picked up stream, the volume of customer
transactional data that become available to companies has increased. By making use of …

In an increasingly globalized market, the relationship between the customer and the brand
goes beyond the purchasing process. It is very important to understand the customer, to …