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Asset groups in Performance Max should map distinct products, services, audiences, and intents into separate clusters rather than using one catch-all structure. This targeted grouping guides Google's algorithm to serve the right assets for specific user intents.

Diagnosing brand cannibalization in Performance Max requires comparing PMax traffic against Search campaigns to determine whether brand traffic is incremental, neutral, or being substituted. This analysis informs whether to apply account-level brand exclusions.

Audience signals and search themes in PMax guide machine learning without restricting targeting. You configure non-restrictive signals to steer the algorithm toward desired user profiles, avoiding common mistakes that artificially limit reach.

You can recover reporting data from Performance Max by using search terms insights, brand vs. non-brand bucketing, new customer acquisition reporting, and listing group reviews to extract useful signals despite PMax's limited native reporting.

This Performance Max diagnostic approach works across ecommerce, lead generation, local, and app campaigns. It applies to any PMax campaign needing asset group planning, audience guidance, cannibalization analysis, or listing group review.

Brand traffic substitution in Performance Max happens when PMax captures existing brand demand instead of driving incremental conversions. Comparing PMax against Search campaign data identifies whether traffic is incremental, neutral, or substituted.