Paid-media agencies and AdTech platforms want to move beyond generic demographic lookalikes and instead build prospecting audiences based on the actual real-world visitation behavior of their best customers. This use case ingests device-level or panel-based visitation and dwell patterns at POIs (visit frequency, dwell time, repeat-visit cadence, and cross-visitation to competitor or complementary venues) captured at daily cadence across the U.S. and Canada, joins that mobility signal to firmographic attributes of the visited businesses (category, brand, chain affiliation), and layers in block-group or ZIP-level demographic and lifestyle segmentation to build statistically similar 'lookalike' cohorts. The resulting audience segments are structured for direct activation into DSPs, social ad platforms, and programmatic exchanges, letting media buyers prospect against people who behave like existing high-value customers rather than people who merely share census-tract demographics. The workflow supports refreshable audience builds so segments can be re-scored monthly as visitation patterns shift and campaigns are re-targeted.