Online wildlife trade is widespread and affects thousands of species. Yet, attempts to quantify online wildlife trade have mainly focused on a few platforms and taxonomic groups. Here, we study the prevalence of wildlife trade using automated data collection and filtering methods. We analyze trade across five digital platforms and 156 animal and plant species of conservation concern from a global biodiversity hotspot, the Philippines. We identified approximately 5000 highly relevant instances of trade in 1.47 million posts, focusing on 108 species, 79 of which are classified as threatened. Trade mainly occurred on webpages indexed in Google and on Twitter. We found that manual validation is essential, as animals obtained a higher proportion of hits prior to validation. Following manual validation, we observed a shift toward plant-related trade hits. Scaling up these approaches to a global level is key to understanding the extent of digital wildlife trade across the globe.