Few Shot Learning

Design an experiment to determine empirically whether few-shot prompting outperforms zero-shot for a specific task on your production model.

You're prompting GPT-5.5 for English-to-Spanish translation. The zero-shot version works fine. When would adding few-shot examples reliably outperform the zero-shot prompt?