The growing relevance of data quality has revealed the need for adequate measurement since quantifying data quality is essential for planning quality measures in an economic manner. This paper analyzes how data quality can be quantified with respect to particular dimensions. Firstly, several requirements are stated (e.g. normalization, interpretability) for designing adequate metrics. Secondly, we analyze metrics in literature and discuss them with regard to the requirements. Thirdly, based on existing approaches new metrics for the dimensions correctness and timeliness that meet the defined requirements are designed. Finally, we evaluate our metric for timeliness in a case study: In cooperation with a major German mobile services provider, the approach was applied in campaign management to improve both success rates and profits.