Customer relationship management using Web personalisation initiatives have gained much attention. The most important strategy of Web personalisation is to provide the customers with correct information or services based on the knowledge about the customers' preferences. With the help of data mining technologies, the above strategy can be implemented. Computational intelligence technologies are investigated in this paper to provide interaction through Web personalisation. This paper proposed two algorithms for the personalisation of the online shopping websites. It uses the radial basis function (RBF) neural network. The algorithms first model the customer's preferences as a complex nonlinear function. It personalises the information presented to customers based on their preferences. The second is the preference learning algorithm. It learns the customer's preferences implicitly from the customer's behaviours by using a RBF neural network.