Geopath Road, Transit & Point-of-Interest Network Data

Geopath uses several data sources to inform its model of audiences and traffic across all media types.

First, to understand where OOH inventory exists in the USA, we leverage Geopath’s proprietary database of OOH signage which contains precise latitude/longitude coordinates of the signage, the size of the signage, the height of the signage, the illumination of the signage, and the orientation of the signage (as well as other relevant metadata like OOH ‘layout’ and ‘share of voice’ where multiple ad units can be seen concurrently or over time). Each particular piece of OOH inventory is linked to a road ‘segment’ or a specific ‘place’, which is then augmented with information about the population that views the inventory.

Geopath uses Terralytics' “Streetlytics” data to inform how many vehicle trips traverse a particular path as well as vehicle occupancy for each trip, so as to understand the complete portion of ‘person-level circulation’ for each roadway. Each trip is ‘uni-modal’ (meaning that it is a single origin to a single destination that is measured using this method rather than ‘multi-modal’, where vehicles are tracked from their origin to multiple destinations before returning to their origin).

Geopath also uses HERE Maps to create an updated map of all roadways in the USA, along with HERE Speeds to determine the average speed of vehicles traversing each roadway.

Geopath leverages MotionWorks to provide information on several areas, including:

1. ‘Synthetic populations’ (i.e. models of real people with specific demographics based on mobile device data) that travel along roadways and pedestrian thoroughfares in the USA. Information on vehicular trips from Streetlytics are augmented with MotionWorks data to inform the most recent patterns of traffic increase or decrease along roadways and thoroughfares, allowing Geopath to determine the most recent seasonal changes that enhance the precision of the circulation data provided by Teralytics. Motionworks also provides information about specific pedestrian visits within/around specific ‘places’ outside of roadways using its mobile device data set so that Geopath can accomplish place-based measurement.

2. Data about the census blocks and census tracts that are the ‘origins’ of each vehicle and pedestrian ‘trip’, which informs the demography of each person in the synthetic population that traverses a physical area

3. Data about actual observations of mobile device collections that traverse multiple areas, which is used to tune a predictive neural network that drives reach/frequency estimates for dynamic collections of OOH inventory (in order to deliver de-duplicated reach and frequency at the person level with high precision)

Finally, Geopath uses GTFS data to understand the scheduled routes and exposure of major metropolitan transit systems. A transit fleet ‘routing engine’ (OSRM) is also applied against this map of transit fleet networks in order to understand the shortest routes between two points which the transit fleet traverses.