In the current competitive marketing world, it is notably significant for decision makers to have intelligent tools that support decisions making quickly, rightly and accurately. Marketing is one of the areas in which decisions are taken on complex marketing environment based on uncertain, inaccurate and ambiguous information. In addition, the problem could have multiple criteria on which the decisions are made. In this dissertation, first Formal Specification Notation is proposed. The proposed notation is robust, convenient and suitable for varying nature problems. It deals both crisp and fuzzy data, for requirement specification, that leads to minimization of ambiguity and uncertainty arising from manifold market or other sources. Secondly, concept of Hypothetical Database is used to develop What-if database constructor. It allows the decision makers to analyse the data/information from the original database by generating what-if scenarios to evaluate the future strategies for marketing. Lastly, a new algorithm is proposed for decision support system based on Fuzzy Analytic Hierarchy Process (FAHP) approach and Area ranking of fuzzy numbers based on positive and negative ideal point’s method. Area ranking method captures the risk attitude of decision makers. For the validation of proposed algorithm and 5P’s marketing mix elements, a case study of a company is conducted as an example.