With the current globalization drive, most firms rely on Competitive Intelligence to help position them strategically through effective decision-making based on Customer Relationship Management (CRM), marketing activities and competitors' vulnerability. It is of interest therefore to make decisions based on accurate inferences. Association rules have been widely used in data mining to find patterns in data that reveal combinations that occur at the same time which are called rules. The rules are sometimes too numerous to be used in decision making, hence, the interestingness of the rules are used to select the subset to act upon.

This paper aims at evaluating the interestingness of rules gotten from applying association rule mining algorithm to data received from questionnaires of mobiles phone users in Nigeria. A pattern is interesting if it is easily understood by humans, potentially useful and novel. The evaluation of the rule is done objectively using statistical independence and correlation analysis. This research has helped to reduce the uncertainty and inaccuracy of rules from which decisions are based towards the competitive advantage of an organization. Findings from the research revealed the areas of strength and weakness of mobile phone manufacturers and this understanding is used to provide competitive business decisions, which will in turn contribute to the profit of the organization.