Two approaches to vector-based call-routing are described, one based on matching queries to routes and the other on matching queries directly to stored queries. We argue that there are some problems with the former approach, both when used directly and when latent semantic analysis (LSA) is used to reduce the dimensionality of the vectors. However, the second approach imposes a higher computational load than the first and we have experimented with reducing the number of reference vectors (using the multi-edit and condense algorithm) and the dimensionality of the vectors (using linear discriminant analysis (LDA)). Results are presented for the task of routing queries on banking and financial services to one of thirty-two destinations. Best results (5.1% routing error) were obtained by first using LSA to smooth the query vectors followed by LDA to increase discrimination and reduce vector dimensionality.