Meta's Advantage+ is now the default for most brands. In 2026, it finds conversions faster than any human media buyer. But there is a split forming in how brands use it.
The first group lets Meta's Andromeda engine handle the matching. The system optimises for conversion probability, which usually means finding people already in the brand's funnel. The ROAS looks strong. The learning compounds inside the platform, not inside the brand.
The second group is moving back to manual targeting because new customer acquisition costs inside Advantage+ are rising in competitive verticals. They are right that the black box is getting expensive. But they are solving a system problem with manual labour. They are working harder to manage a tool designed to move away from them.
The third group uses Advantage+ for scale but captures every output into their own stack. While the platform identifies creative patterns, these brands identify behavioural patterns. They correlate performance data against their own models to find signals Andromeda cannot see: weather, payday, local events. They warehouse the output and deploy it across paid channels, web, app, email, and stores.
Group three builds compound intelligence. Every campaign trains their own models. Every result is validated against a performance spine that belongs to the brand. The platform does the optimisation. The brand keeps the learning. That is the difference between using a tool well and building a system you own.
If you are a brand looking for an independent view of where your marketing intelligence is accumulating and what it would take to own it, book a conversation.
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