How happy is your web browsing? A model to quantify satisfaction of an Internet user searching for desired information

We feel happy when web browsing operations provide us with necessary information; otherwise, we feel bitter. How to measure this happiness (or bitterness)? How does the profile of happiness grow and decay during the course of web browsing? We propose a probabilistic framework that models the evolution of user satisfaction, on top of his/her continuous frustration at not finding the required information. It is found that the cumulative satisfaction profile of a web-searching individual can be modeled effectively as the sum of a random number of random terms, where each term is a mutually independent random variable, originating from ‘memoryless’ Poisson flow. Evolution of satisfaction over the entire time interval of a user’s browsing was modeled using auto-correlation analysis. A utilitarian marker, a magnitude of greater than unity of which describes happy web-searching operations, and an empirical limit that connects user’s satisfaction with his frustration level—are proposed too. The presence of pertinent information in the very first page of a website and magnitude of the decay parameter of user satisfaction (frustration, irritation etc.) are found to be two key aspects that dominate the web user’s psychology. The proposed model employed different combinations of decay parameter, searching time and number of helpful websites. The obtained results are found to match the results from three real-life case studies.

► Evolution of satisfaction profile of an Internet searcher is modeled.
► Satisfaction was modeled as a random number of random terms, in a Poisson flow.
► (||Satisfaction retention quotient||(a marker proposed here)>1>1) denotes satisfactory web searching.
► Relevant information on first page of a site and low-degree initial irritation level of user determine satisfaction.
► Three different real-life case studies tend to support the theoretical model.