Amazon's ad auction increasingly rewards advertisers who give its AI-driven matching more room to substitute and expand rather than constraining it tightly — the same underlying claim is extended to other AI-driven ad platforms (Facebook, YouTube, Google). A concrete data point: one account's pancake batter dispenser listing recorded a 56% ACoS on the exact term 'pancake batter dispenser' under exact match, versus a 20% ACoS on the identical term surfaced through broad match — evidence that loosening targeting control can improve profitability rather than hurt it. This is the same mechanism behind Broad Match Modifier (Undocumented Fourth Match Type) superseding phrase match: giving the algorithm a widened but still-bounded search space can outperform forcing it into a narrow literal box.
Auto-targeting campaigns, historically treated as a way to waste PPC budget, are argued to now be capable of top performance because 'Amazon's algorithm wants leeway in 2025 and beyond' — the same logic behind broad-match/automated-targeting gains on Meta, Google, and YouTube ad platforms, where giving the algorithm more targeting latitude, rather than tightly hand-restricting it, tends to improve results as the underlying models mature.
Framed on Amazon Sponsored Products specifically as: 'Amazon's algorithm wants leeway in 2025 and beyond — it wants the flexibility to show your ad when and where it wants.' Used to justify combining all four auto-targeting match types into one campaign via targeting groups (see Combined Auto-Targeting Campaign (Set Bids by Targeting Group)) rather than splitting them, and to explain why campaign types that give Amazon more discretion (e.g. expanded self-targeting, broad match) tend to outperform tightly constrained ones.
Из тем: PPC Campaign Structure & Bidding