"Conversion" means something specific in OOH measurement, and understanding the mechanics is the difference between trusting the numbers and dismissing them.

Whatever outcome you define: website visits, signups, purchases, app installs, or physical store visits. The measurement approach adapts to the conversion type. Web pixels for online actions, location data for store visits, and app measurement partners for installs.

A device is observed within the viewshed of your units while your creative was running, which makes it exposed. If that same device later performs the conversion action, the two are matched through privacy-compliant device identity.

Each exposure carries its own thirty days. A device exposed on day one of the flight is watched until day thirty-one; a device first exposed on the last day gets its own thirty days from that point. This is not a single window that opens when the campaign ends. See the attribution window article for what the thirty days is measured from and why.

Raw counts of exposed people who converted are correlation. Causality comes from the control group, a matched population that was not exposed. Lift is the difference in conversion rate between the exposed group and the control, and that difference, rather than the raw count, is the number to trust.

Someone who drove past a billboard and would have converted anyway is exactly what the control group corrects for. Baseline converters exist in both groups, and lift isolates the increment above that baseline.

Lift varies widely by category, creative, frequency, and conversion type, so treat any universal benchmark skeptically. What matters is the comparison between your exposed and control groups on this campaign, not a comparison against an industry figure.

Online conversions need a pixel or analytics integration configured before launch. Store-visit measurement needs your location list. See the pixel tracking article for implementation detail and timing.