The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Understanding Customers' Behaviour through Web Data Mining Models
Abstract
Companies have realized that the customer knowledge contained in web marketing database represent one of the main key to forecast business performance in today's competitive landscape. Appropriate web data mining models are one the best supporting approach to make different marketing decision. Analysing and understanding in advance customers' behaviour can represent the main corporation's strength in planning marketing forecasting. This research want to demonstrate as predictive web data mining models are accurate patterns in predicting marketing performance compared to traditional statistical methods in global business. In addition, particular attention is paid on the identification of the main marketing drivers performed by potential customers before purchasing a given service online. Finally, the criteria based on the loss functions confirm the high predictive power of the web data mining models in detecting the probability of customer conversion.
Related Content
Nitesh Behare, Rashmi D. Mahajan, Meenakshi Singh, Vishwanathan Iyer, Ushmita Gupta, Pritesh P. Somani.
© 2024.
36 pages.
|
Shikha Mittal.
© 2024.
21 pages.
|
Albérico Travassos Rosário.
© 2024.
31 pages.
|
Carla Sofia Ribeiro Murteira, Ana Cristina Antunes.
© 2024.
23 pages.
|
Mario Sierra Martin, Alvaro Díaz Casquero, Marina Sánchez Pérez, Bárbara Rando Rodríguez.
© 2024.
17 pages.
|
Poornima Nair, Sunita Kumar.
© 2024.
18 pages.
|
Neli Maria Mengalli, Antonio Aparecido Carvalho.
© 2024.
16 pages.
|
|
|