A method to optimally define hub consumers in a social network is addressed in this presentation. These are the leaders that will enable a company to effectively address marketing campaigns on a social network and those who will provide online ways to defend the company or the brand from attacks in the net. Traditional procedures, such as judicial measures, from the point-of-view of speed of action are useless to defend the brand and can even amplify the damage.
The paper performs a comparison of data mining tools with conventional tools. It is focused on the analysis of issues such as if the new techniques are better than the older ones if so in which sense and when we should apply them. The effort is concentrated on neural networks automatic interaction detection memory based reasoning and genetic algorithms. These techniques are compared with multiple linear regression and logistic regression using as a standard for comparison a simulated 2 interview magazine customer satisfaction survey.
This paper describes a two stage customer satisfaction methodology that identifies the relevant attributes in products or services, evaluates their importance degree, qualifies the attributes from the point of view of their nature, evaluates the current performance, sets performance goals and finally identifies and evaluates the performance of the relevant competitors.