Knowledge-based information systems are advanced tools in the hands of the marketer, enabling him to take evidence-based decisions in complex situations. In this paper, advanced data analysis, neural networks and knowledge representation technologies are brought together towards an intelligent information system for tourist destination marketing. In previous work, knowledge engineering methods were proposed for the extraction and modeling from market survey data of factors, associations, clusters and hidden patterns that explain a market phenomenon or customer behavior. The feasibility of managing these findings in a Knowledge-Base, as reusable, sharable and machine understandable knowledge was shown using preliminary results from primary surveys on the tourism of Thessaloniki. In the current work, we present the continuation of these developments, including: (a) the final results of the survey on the tourism of Thessaloniki, (b) a refined Knowledge Base filled with real and validated content derived from the analysis of the full-scale survey data, (c) the extension of the methods with an artificial neural network classifier and (d) the deployment of an inference engine and a query mechanism in order to exercise the knowledge content for decision support. Pilot trials showed that the intelligent system was able to assist users who are not experts in analysis to solve typical destination marketing problems