Tolerance allocation during detail design aims to identify a combination of tolerances which are tight enough to ensure total product functionality but also as wide as possible to minimize the resultant manufacturing costs. Optimization techniques automatize and thus significantly accelerate the complex search for suitable tolerance values taking both the design and manufacturing perspective into account. While sampling techniques became well-established for tolerance analysis, statistical approximative approaches, e.g. the root sum square method, are still commonly used for tolerance-cost optimization. However, this leads to a limited applicability and validity of the optimization which currently prevents its successful implementation in industry. Thus, the article discusses the direct and indirect effects of sampling methods on the definition and solution of the optimization problem and reveals the benefits and drawbacks of sampling-based tolerance-cost optimization in terms of effectiveness and efficiency using an illustrative case study. In addition, guidelines as well as recommendations for its proper application in research and industry are given. In doing so, this article shows that the use of sampling-based techniques can significantly contribute to a shift of tolerance-cost optimization from an expert tool for tolerance specialists with in-depth knowledge in statistics, optimization and programming, to a user-friendly engineering design tool with an enhanced usability, which enables solving problems of industrial complexity.