A common industrial challenge is that of analyzing large legacy free text test suites in order to comprehend their functional content. The analysis results are used for different purposes, such as dividing the test suite into disjoint functional parts for automation and management purposes, identifying redundant test cases, and extracting models for combinatorial test generation while reusing the legacy test suite. Currently the analysis is performed manually, which hinders the ability to analyze many such large test suites due to time and resource constraints. We report on our practical experience in automated analysis of real-world free text test suites from six different industrial companies. Our novel, cluster-based approach provides significant time savings for the analysis of the test suites, varying from a reduction of 35% to 97% compared to the human time required, thus enabling functional analysis in many cases where manual analysis is infeasible in practice.