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Extrapolation
Only a fraction of the population is observed, so counts are scaled up to represent everyone. The scaling is based on market share: how many of an area's residents we observe, compared with the area's population. Devices are counted by their likely home area, and the market share is updated continuously, so the scaling follows the panel as it changes over time rather than relying on a fixed factor. Where a model produces the estimates, as for Foot Traffic on places, its output is also calibrated against ground-truth visitation data. The result reflects real-world visit volume rather than the size of the underlying sample.
Signal density
For GPS-based data, the scaling also corrects for signal density. Not all GPS sources observe devices continuously through the day: some only record a device's whereabouts at certain times, and this varies between sources and over time. A device that is observed for less of the day is seen at fewer places, even if its owner's behavior is unchanged. We therefore measure how much activity is recorded per device each day and correct for changes in it, so differences in reporting frequency do not read as differences in visits.