Phylogenetic hypotheses using whole genome sequences have the potential for unprecedented accuracy, yet a failure to understand issues associated with discovery bias, character sampling, and strain sampling can lead to highly erroneous conclusions. For microbial pathogens, phylogenies derived from whole genome sequences are becoming more common, as large numbers of characters distributed across entire genomes can yield extremely accurate phylogenies, particularly for strictly clonal populations. The availability of whole genomes is increasing as new sequencing technologies reduce the cost and time required for genome sequencing. Until entire sample collections can be fully sequenced, harnessing the phylogenetic power from whole genome sequences in more than a small subset of fully sequenced strains requires the integration of whole genome and partial genome genotyping data. Such integration involves discovering evolutionarily stable polymorphic characters by whole genome comparisons, then determining allelic states across a wide panel of isolates using high-throughput genotyping technologies. Here, we demonstrate how such an approach using single nucleotide polymorphisms (SNPs) yields highly accurate, but biased phylogenetic reconstructions and how the accuracy of the resulting tree is compromised by incomplete taxon and character sampling. Despite recent phylogenetic work detailing the strengths and biases of integrating whole genome and partial genome genotype data, these issues are relatively new and remain poorly understood by many researchers. Here, we revisit these biases and provide strategies for maximizing phylogenetic accuracy. Although we write this review with bacterial pathogens in mind, these concepts apply to any clonally reproducing population or indeed to any evolutionarily stable marker that is inherited in a strictly clonal manner. Understanding the ways in which current and emerging technologies can be used to maximize phylogenetic knowledge is advantageous only with a complete understanding of the strengths and weaknesses of these methods.