AI Without Context Won't Drive Commerce Outcomes | AdExchanger

"The answer often comes down to connection, or the lack of it. Many AI tools are designed to optimize one piece of the performance puzzle - bidding, targeting or measurement - without understanding how the parts fit together. Metrics may improve in isolation, but that doesn't always translate into outcomes. The missing link is moving from AI that can tell you what to do for a specific case to AI that understands why, so it can be replicated in other similar situations."

"To bridge that gap, marketers need AI models that truly understand performance, which requires two dimensions. The first is integration to connect data, tools and decisioning across the full shopper journey. The second is domain expertise that gives AI a foundational understanding of how commerce actually works, including how products move, shoppers behave and intent becomes purchase. When those two layers come together, models evolve from task optimizers to performance drivers."

Performance marketers use AI to personalize creative, sharpen targeting and optimize in real time, producing metric improvements across key indicators. Many AI tools improve isolated tasks like bidding, targeting or measurement but fail to translate those metric gains into business outcomes due to a lack of connection across systems. Effective performance AI requires integration of data, tools and decisioning across the full shopper journey plus domain expertise about commerce dynamics, product movement, shopper behavior and intent-to-purchase. When integration and domain knowledge combine, models move from optimizing tasks to driving overall performance.

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