The methods presented in this article were created to model and describe the behaviour of the web users of a bank institution web portal. The source dataset is represented by a log file of the commercial bank web server. The analysis is oriented on examining the behaviour of visitors over an extended period (2009-2012). The years 2009-2010 represent the years of the financial crisis, and the years 2011-2012 represent the years after the financial crisis. The following method describes the sequence of steps necessary to pre-process the raw log file and model the web user behaviour using the multinomial logit model. The introduced methods can be used also for other domains in the case of appropriate data preparation.•Data preparation- data cleaning, user/session identification, path completion, variables determination;•Data analysis- model definition, parameters estimation, logits estimation, probabilities estimation;•Results evaluation- comparison of empirical and theoretical values in term of counts, probabilities and logits.
Keywords: Data pre-processing; Multinomial logit model; Web usage mining.
© 2021 The Authors. Published by Elsevier B.V.