TARGETED INTERNET CLICKS

A targeted click is a classification decision.

Before a click happens, the system has already decided who the user is likely to be. Location, device, browsing history, inferred interests, prior behavior — these signals are combined to determine whether a click is worth purchasing, serving, or ignoring.

Targeting is presented as precision. In practice, it is exclusion.

Most users never see most links. They are filtered out upstream, not because they lack interest, but because they fail to match a profile. Attention is not merely captured; it is pre-sorted.

This sorting is framed as efficiency. Budgets are optimized by avoiding “wasted” clicks — users who do not convert, linger, or behave predictably. What counts as waste is defined by the system’s goals, not the user’s.

Targeted clicks also shape messaging. Content is adjusted to align with the profile that triggered the delivery. Tone, language, imagery, and urgency are altered dynamically. The user experiences this as relevance. The system experiences it as confirmation.

Over time, the targeting loop reinforces itself. Clicks train models. Models refine targeting. Targeting narrows exposure. The system becomes better at predicting behavior within the slice it already understands, while the rest fades from view.

From a laundering perspective, the click is not the transaction.
The classification that precedes it is.