How to see inside the AI funnel | MarTech

"We built funnels, tracked clicks and optimized journeys because we could seewhat was happening. We optimized for the "messy middle": customer journeys we can track on the open web. The premise that we can see it all, track it all is obsolete. The customer journey has migrated to closed AI environments, leaving our analytics stacks blind. The causal link between action and result has evaporated."

"The dashboards and metrics we relied on feel like comfort metrics providing an illusion of control. When an AI assistant recommends a product based on Reddit sentiment, embedded documentatio or the semantic context of a YouTube review, your analytics capture nothing of the journey. The old funnel is dead, and marketers who fail to adapt will be trying to optimize a ghost."

For two decades marketing relied on visible funnels, click tracking and measurable journeys on the open web. That visibility has eroded as customer interactions migrate into closed AI environments and LLM-based assistants, breaking the causal link between identifiable actions and outcomes. Dashboards and traditional attribution become comfort metrics that hide lost diagnostic power when AI recommendations draw on semantic context, Reddit sentiment and embedded documents. A new market of AI tracking tools attempts to restore visibility by combining synthetic lab data from curated prompts with field data. Synthetic testing benchmarks model responses and exposes theoretical presence and failure modes inside LLM outputs.

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