Autonomous acoustic monitoring has become an essential tool for studying wildlife populations across large spatial and temporal scales, yet methodological guidance remains fragmented across software documentation, workshops, and informal knowledge transfer. This manual provides a practical, end-to-end workflow for conducting bioacoustic studies using Arbimon, with an emphasis on reproducible methods, validation of automated detections, and interpretation of acoustic signals in ecological contexts. The guide synthesizes over seven years of applied research experience analyzing autonomous recording unit (ARU) data across diverse habitats and species, with detailed coverage of recorder deployment, recording schedules, template development, automated pattern matching, manual validation, threshold selection, and inference of biological events from acoustic data. While examples are drawn primarily from avian vocalizations, the methods are broadly applicable to other taxa and soundscape analyses. This manual is intended for field biologists, conservation practitioners, and researchers seeking a rigorous but accessible framework for designing, analyzing, and interpreting bioacoustic datasets, and is designed to evolve as tools and best practices advance.