The human microbiome is a complex biological ecosystem, comprising diverse communities of archaea, bacteria and viruses that play essential roles in human health, and whose disturbance has been implicated in various pathologies. Advances in bacterial culturing techniques has enabled in vitro characterisation of these microbiota, and while an overwhelming majority of the functional repertoire within the human microbiome remains to be characterised, it has become apparent that slight genomic differences can have disproportionately significant impacts on large-scale phenotypes. The current taxonomic standards used to describe and compare microbiota do not always capture precise genomic relationships, and may not be sufficient to accurately recapitulate these different phenotypes being observed between similar microbes. Phylogenetics provides an alternative framework for investigating microbiome composition and functional potential. In particular, clade-based analyses resolve the hierarchical differences between microbial genomes. We developed and tested a phylogenetic approach “expam” to culture-free shotgun metagenomic sequencing pipelines, enabling high-throughput characterisation of microbial communities at unprecedented resolution. Our benchmarking on 140 simulated metagenomes demonstrates that expam achieves state-of-the-art precision and recalls of 84.0% and 55.8% respectively when translated into the taxonomic setting, while also performing classification within a phylogenetic tree that provides a resolution beyond current taxonomic standards. The increasing depth of -omics analyses is rapidly revealing not only the immense genotypic and phenotypic diversity of the microbiome, but also the vast milieu of cells and environments within the human host with which the microbiome interacts with and relies upon. This apparent diversity of interactions between the microbiome and host environment underscores the importance of clade-specific associations based on precise genomic relationships, as such associations lay the foundation for generating mechanistic hypotheses and informing our investigation into the complex host-microbiome relationship.