Visit Data

Our Visit Data connects people's movements to over 200M+ physical locations globally. These are aggregated and anonymized data that are only used to offer context for the volume and patterns of visits to certain locations. This data feed is compiled from different data sources around the world.

Visit Data Reach

Visit Data data brings the POI/Place/OOH level insights calculated on the basis of Factori’s Mobility & People Graph data aggregated from multiple data sources globally. In order to achieve the desired foot-traffic attribution, specific attributes are combined to bring forward the desired reach data.
For instance, in order to calculate the foot traffic for a specific location, a combination of location ID, day of the week, and part of the day can be combined to give specific location intelligence data. There can be a maximum of 30 data records possible for one POI based on the combination of these attributes.

Data Export Methodology
Since we collect data dynamically, we provide the most updated data and insights via a best-suited method at a suitable interval (daily/weekly/monthly).

Use Cases

Credit Scoring
Financial services can use alternative data to score an underbanked or unbanked customer by validating locations and persona.
Retail Analytics
Analyze footfall trends in various locations and gain understanding of customer personas.
Market Intelligence
Study various market areas, the proximity of points or interests, and the competitive landscape
Urban Planning
Build cases for urban development, public infrastructure needs, and transit planning based on fresh population data.

Schema

Attribute Name	Attribute Description	Sample
Location ID	STRING	Geographic Identifier (Quad Key 17, Geohash or Hex, POI Id, OOH Id)
n_visitors	INTEGER	Extrapolated count of distinct devices observed in the relevant time frame
day_of_week	STRING	Day of the week (eg : Monday, tuesday etc)
distance_from_home	DOUBLE	Distance from geoid to home in meters
do_date	DATE	Start date of month when we generated the data (Static date for the entire month)
month	STRING	Month to which the data pertains
part_of_day	STRING	Time of the Day : Will have values like Morning - 6AM to 12 PM, Afternoon 12 PM to 6 PM, Evening 6 PM to 10PM, Night 10 PM to 6 AM
travelled_countries	JSON	For Devices seen in specific Quad key in a given time frame - Proportion of travel to different countries
Visitor_country_origin	JSON	For Devices seen in specific Quad key in a given time frame - Proportion of home country
Visitor_home_origin	JSON	For Devices seen in specific Quad key in a given time frame - Proportion of quad keys with their home location
Visitor_work_origin	JSON	For Devices seen in specific Quad key in a given time frame - Proportion of quad keys with their work location
year	STRING	Year to which date pertains
Carrier	JSON	Proportion of devices enrolled with different
Brand Visited	JSON	Relative brand affinity for devices observed in a given quad Key in a given time frame
Place _Categories	JSON	Relative place category affinity for devices observed in a given quad Key in a given time frame
Geo _ behaviour	JSON	Relative Geo- behavioural interests for devices observed in a given quad Key in a given time frame
make	JSON	proportion of devices with different smartphone brands
model	JSON	proportion of devices with different smartphone models
OS_versions	JSON	proportion of devices with different smartphone OS versions
ratio_age_18_24	FLOAT	Ratio of geoID visitors age 18-24
ratio_age_25_34	FLOAT	Ratio of geoID visitors age 24-34
ratio_age_35_44	FLOAT	Ratio of geoID visitors age 35-44
ratio_age_45_54	FLOAT	Ratio of geoID visitors age 45-54
ratio_age_55_64	FLOAT	Ratio of geoID visitors age 55-64
ratio_age_65	FLOAT	Ratio of geoID visitors age >= 65
ratio_female	FLOAT	Ratio of geoID visitors gender (female)
ratio_male	FLOAT	Ratio of geoID visitors gender (male)
ratio_residents	FLOAT	Ratio of geoID devices who are considered resident in that geoID
ratio_workers	FLOAT	Ratio of geoID devices who are considered working in that geoID
ratio_others	FLOAT	Ratio of geoID devices who are considered niether resident nor working in that geoID