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The combination of DNA barcoding and high-throughput (next-generation) sequencing (metabarcoding) provides many promises but also serious challenges. Generating a reliable comparable estimate of biodiversity remains a central challenge to the application of the technology. Many approaches have been used to turn millions of sequences into distinct taxonomic units. However, the extent to which these methods impact the outcome of simple ecological analyses is not well understood. Here we performed a simple analysis of dietary overlap by skinks and shrews on Ile Aux Aigrettes, Mauritius. We used a combination of filtering thresholds and clustering algorithms on a COI metabarcoding dataset and demonstrate that all bioinformatics parameters will have interacting effects on molecular operational taxonomic unit (MOTU) recovery rates. These effects generated estimates covering two orders of magnitude. However, the effect on a simple ecological analysis was not large and, despite the wide variation in estimates of niche overlap, the same ecological conclusion was drawn in most cases. We advise that a conservative clustering programme coupled with larger sequence divergences to define a cluster, the removal of singletons, rigorous length filtering, and stringent match criteria for Molecular Identifier tags are preferable to avoid MOTU inflation and that the same parameters be used in all comparative analyses.