Audience signals are suggestions to the PMAX algorithm about who to target. They are not hard targeting constraints — the algorithm can and does serve ads outside your signals if it finds better conversion probability. Strong signals shorten the learning phase by giving the algorithm a conversion-likely population to start from.
Customer match lists (from your CRM or email list) are the highest-quality signals. Website visitor lists (pixel-based) are second. In-market and affinity segments are third. Custom intent segments (built from URLs, apps or keywords) are useful when first-party data is limited. Use all available signal types, layered into a single audience signal per asset group.
PMAX enters a learning phase for the first two to six weeks of a campaign. Strong audience signals can shorten this. During the learning phase, avoid changing budget, bidding or assets — changes restart the learning clock. Budget adequacy (enough to generate 50+ conversions per month) is the more significant factor than signals in reducing learning phase duration.
A Performance Max campaign uses a single campaign with multiple asset groups. Each asset group targets a product category or audience segment. The structure is simple but the asset quality is what drives results.
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TPR Media explains Performance Max audience signals for Australian businesses: signal quality hierarchy from customer match to in-market audiences, layering approach, and how adequate budget (50+ monthly conversions) is the key factor in shortening the learning phase.