Factori Location Intelligence with Profile|POI + People Data|
| # | id |
name |
address |
postcode |
do_date |
year |
month |
day_of_week |
part_of_day |
n_visitors |
distance_from_home |
travelled_countries |
visitor_country_origin |
visitor_home_origin |
visitor_work_origin |
carrier |
brand_visited |
place_categories |
geo_behaviour |
make |
model |
os_version |
ratio_age_18_24 |
ratio_age_25_34 |
ratio_age_35_44 |
ratio_age_45_54 |
ratio_age_55 |
ratio_female |
ratio_male |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx |
| 2 | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx |
| 3 | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx |
| 4 | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx |
| 5 | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx |
| 6 | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx |
| 7 | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx |
| 8 | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx |
| 9 | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx |
| 10 | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx |
| ... | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx |
Data Dictionary
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
id
|
Integer | 108135561 | |
|
name
|
String | Walmart @ Miami 9191 W. Flagler St, Miami, FL 33174, USA | |
|
address
|
String | 9191 W. Flagler St, Miami, FL 33174, USA | |
|
postcode
|
Integer | 33172 | |
|
do_date
|
String | 01-08-2021 | |
|
year
|
Integer | 2021 | |
|
month
|
Integer | 8 | |
|
day_of_week
|
String | Thursday | |
|
part_of_day
|
String | Evening | |
|
n_visitors
|
Integer | 77 | |
|
distance_from_home
|
Float | 19877.16 | |
|
travelled_countries
|
String | {"CAN": 0.5, "MEX": 0.5} | |
|
visitor_country_origin
|
String | {"USA": 1.0} | |
|
visitor_home_origin
|
String | {"03202312110113033": 0.114, "03202310332330223": 0.057, ... | |
|
visitor_work_origin
|
String | {"03202312110113033": 0.114, "03202310332330223": 0.057, ... | |
|
carrier
|
String | {"t-mobile usa": 0.743, "at&t wireless": 0.229, "verizon ... | |
|
brand_visited
|
String | {"Walmart Visitors": 100, "Subway Visitors": 100, "Teavan... | |
|
place_categories
|
String | {"Convenience Store Visitors": 100, "Burger Restaurant Vi... | |
|
geo_behaviour
|
String | {"DIY Enthusiasts": 100, "Foodies": 78, "Frequent Pizza R... | |
|
make
|
String | {"apple": 0.4, "samsung": 0.4, "generic": 0.057, "oneplus... | |
|
model
|
String | {"iphone": 0.4, "sm-g950u": 0.057, "sm-g960u1": 0.057, "a... | |
|
os_version
|
String | {"14": 0.2, "10.0": 0.143, "10": 0.114, "9": 0.114, "14.7... | |
|
ratio_age_18_24
|
Float | 0.25 | |
|
ratio_age_25_34
|
Float | 0.25 | |
|
ratio_age_35_44
|
Float | 0.188 | |
|
ratio_age_45_54
|
Integer | 0 | |
|
ratio_age_55
|
Float | 0.313 | |
|
ratio_female
|
Float | 0.233 | |
|
ratio_male
|
Float | 0.767 |
| Attribute | Type | Example | Mapping |
|---|---|---|---|
| String | STRING | Location ID | |
|
n_visitors
|
INTEGER | ||
|
day_of_week
|
STRING | ||
|
distance_from_home
|
DOUBLE | ||
|
do_date
|
DATE | ||
|
month
|
STRING | ||
|
part_of_day
|
STRING | ||
|
travelled_countries
|
JSON | ||
|
Visitor_country_origin
|
JSON | ||
|
Visitor_home_origin
|
JSON | ||
|
Visitor_work_origin
|
JSON | ||
|
year
|
STRING | ||
|
Carrier
|
JSON | ||
|
Brand Visited
|
JSON | ||
|
Place _Categories
|
JSON | ||
|
Geo _ behaviour
|
JSON | ||
|
make
|
JSON | ||
|
model
|
JSON | ||
|
OS_versions
|
JSON | ||
|
ratio_age_18_24
|
FLOAT | ||
|
ratio_age_25_34
|
FLOAT | ||
|
ratio_age_35_44
|
FLOAT | ||
|
ratio_age_45_54
|
FLOAT | ||
|
ratio_age_55_64
|
FLOAT | ||
|
ratio_age_65
|
FLOAT | ||
|
ratio_female
|
FLOAT | ||
|
ratio_male
|
FLOAT | ||
|
ratio_residents
|
FLOAT | ||
|
ratio_workers
|
FLOAT | ||
|
ratio_others
|
FLOAT |
Description
Geography
History
Volume
| 5 million | POI's |
| 420 million | MAU |
Pricing
| License | Starts at |
|---|---|
| One-off purchase | Not available |
| Monthly License | Not available |
| Yearly License |
$97,500$87,750 / year |
| Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Factori Location Intelligence with Profile POI + People Data ?
We provide Location Intelligence Data/POI with identity data, which helps power geographical information system (GIS) tools and provides data-driven insights across a wide range of use cases, from marketing to public planning and fraud detection.
What is Factori Location Intelligence with Profile POI + People Data used for?
This product has 5 key use cases. Factori recommends using the data for Demographic Segmentation, Urban Mobility Analysis, Store Visit Tracking, Location Planning, and Location Insights. Global businesses and organizations buy Store Location Data from Factori to fuel their analytics and enrichment.
Who can use Factori Location Intelligence with Profile POI + People Data ?
This product is best suited if you’re a Medium-sized Business, Enterprise, or Small Business looking for Store Location Data. Get in touch with Factori to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Factori Location Intelligence with Profile POI + People Data go?
This Tabular Data has 1 years of historical coverage. It can be delivered on a monthly, quarterly, and yearly basis.
Which countries does Factori Location Intelligence with Profile POI + People Data cover?
This product includes data covering 249 countries like USA, China, Japan, Germany, and India. Factori is headquartered in United States of America.
How much does Factori Location Intelligence with Profile POI + People Data cost?
Pricing for Factori Location Intelligence with Profile POI + People Data starts at USD97,500 per year. Factori offers a 10% discount when you buy data from them through Datarade. Connect with Factori to get a quote and arrange custom pricing models based on your data requirements.
How can I get Factori Location Intelligence with Profile POI + People Data ?
Businesses can buy Store Location Data from Factori and get the data via S3 Bucket, UI Export, and Feed API. Depending on your data requirements and subscription budget, Factori can deliver this product in .xml, .csv, and .xls format.
What is the data quality of Factori Location Intelligence with Profile POI + People Data ?
Factori has reported that this product has the following quality and accuracy assurances: 90% horizontal accuracy, 90% match rate. You can compare and assess the data quality of Factori using Datarade’s data marketplace. Factori has received 2 reviews from clients. Factori appears on selected Datarade top lists ranking the best data providers, including 10 Best Data Providers for 360 Customer View, 10 Best Data Providers for Customer Segmentation, and Best Data Providers For Location-Based Marketing.
What are similar products to Factori Location Intelligence with Profile POI + People Data ?
This Tabular Data has 3 related products. These alternatives include Factori Global Location Intelligence Data Geospatial:Foot Print:Places Data , Location Data Global Store Location Data on 51M+ POI SafeGraph Places, and The Data Appeal Places Data API, Dataset 200 Million+ POI Data Mapped. You can compare the best Store Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.
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