Foot Traffic & Mobility Data

Using foot traffic to understand human mobility patterns is a key component of spatial analysis for use cases in Retail, Tourism, Events, Out of Home Media & many more areas. Using POIs to estimate people movement & crowd dynamics is no longer enough to provide accurate insights. Discover why using CARTO.

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Human Mobility Datasets

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Example of Foot Traffic Analysis

Local governments

Local governments (such as New York City) rely on GPS data to gain insights that measure the risk of overcrowding by station. In this example, NYC was able to blend MTA turnstile data with Safegraph’s human mobility data to identify which subway stations were at higher risk during the COVID-19 outbreak.

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Example of Foot Traffic Analysis

QSR chains & retailers

QSR (quick service restaurant) chains & retailers use mobility data to understand catchment areas to their locations. In this case, we can see an OD (origin destination) matrix around a McDonald’s location in Brooklyn, enabling expansion planners to identify opportunities for growth & consolidation.

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Example of Foot Traffic Analysis

Tourism organizations & local governments

Tourism organizations & local governments rely on anonymized & aggregated human mobility data to understand tourism patterns, both for national & international travellers. Through Vodafone’s mobility data, tourism decision-makers can understand where tourists come from, how long and where they stay, as well as which leisure destinations they choose.

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