Component maintenance, repair and overhaul is often performed under long-term service agreements with service providers. After receiving a request for quotation, the provider can quote a price for the contract. When the contract is awarded, the profit depends on the quoted price. To gain such contracts and make profit, service providers have to make an accurate estimation of the value of the contract. Therefore, it is crucial to collect attributes from multiple sources that improve the knowledge about the specific contract. However, due to time and effort investment, it is preferred to collect this information in a smart and dynamic way, i.e., responsive to the available collected information. This paper introduces a model of optimal information acquisition for profit maximization that can be used for such situations. Moreover, we introduce a specific model refinement that can be used for quotation optimization. The model utilizes a function that includes the information attributes as variables and returns the profit. Each piece of information is modelled as an attribute for which the true value can be retrieved and the corresponding retrieval effort is translated in a cost. We introduce three heuristic policies with different levels of dynamism for the order and the number of information attributes to be retrieved. We find out that fixing the order in which attributes are retrieved decreases the expected profit by only 4%, while also fixing the number of attributes has much worse consequences.