Broad targeting means selecting only basic parameters like age, gender, and location and letting the delivery system's machine learning find the people most likely to convert, rather than layering on interests or behaviors. With enough conversion data feeding the algorithm, broad targeting frequently outperforms narrow interest-based targeting because it gives the system a larger pool to find its own best-fit users in.
It performs best on accounts with strong, high-volume conversion signal (rich CAPI data, healthy EMQ) since the algorithm needs good data to know who to find; on accounts with thin or noisy tracking, broad targeting can underperform more manually curated audiences.
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