Customer service agents play an important role in bridging the gap between customers’ vocabulary and business terms. In a scenario where organisations are moving into semi-automatic customer service, se- mantic technologies with capacity to bridge this gap become a necessity. In this paper we explore the use of automatic taxonomy extraction from text as a means to reconstruct a customer-agent taxonomic vocabulary. We evaluate our proposed solution in an industry use case scenario in the financial domain and show that our approaches for automated term extraction and using in-domain training for taxonomy construction can improve the quality of automatically constructed taxonomic knowledge bases.