Factori US Person Data APIs | 240M+ profiles:40+ attributes|
# | SL.No. |
factori_id |
gender |
age |
dob_year |
dob_month |
dob_day |
address |
street |
city |
state |
country |
zip |
census_tract |
census_block |
phone_sha1 |
phone_sha2 |
phone_md5 |
emailtype |
device_type |
household_id |
household_income |
net_worth |
education_level |
company_name |
job_title |
job_level |
job_function |
work_emails |
company_phones |
company_address |
company_city |
company_state |
company_postal |
company_sic |
company_naics |
company_primary_industry |
recent_job_change |
linkedin_url |
facebook_url |
contact_skills |
|||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx |
2 | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | 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 | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx |
3 | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | 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 | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx |
4 | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | 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 | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx |
5 | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | 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 |
6 | xxxxx | 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 |
7 | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx |
8 | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx |
9 | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx |
10 | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx |
... | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
SL.No.
|
Integer | 1 | |
factori_id
|
String | d23570075ea4e7bb76c7410cc315c14c | |
String | Contact First Name | ||
String | Contact Last Name | ||
gender
|
String | ||
age
|
Integer | ||
dob_year
|
Integer | 2000 | |
dob_month
|
Integer | 2 | |
dob_day
|
Integer | 23 | |
address
|
String | 625 ALMOND ST N | |
street
|
String | ALMOND | |
city
|
String | CANNON FALLS | |
state
|
String | MN | |
country
|
String | US | |
zip
|
Integer | 55009 | |
census_tract
|
Integer | 80600 | |
census_block
|
Integer | 3037 | |
String | Phone Number | ||
phone_sha1
|
String | [fe5f32f8e966f67e4d25237115cd389f52637485] | |
phone_sha2
|
String | [e5deb0ae584e8272021466023dfa4ad6308a3cd800a9dec355bb7c65... | |
phone_md5
|
String | [0b26a21c976f4e834f521f6ff9e94530] | |
String | Email Address | ||
String | Hashed Email Address | ||
String | Hashed Email Address | ||
String | Hashed Email Address | ||
emailtype
|
String | [P] | |
String | MAID | ||
String | MAID | ||
String | MAID | ||
String | MAID | ||
device_type
|
String | [] | |
household_id
|
Integer | 1324986798 | |
household_income
|
String | $10000-$14999 | |
net_worth
|
String | $1-$4999 | |
education_level
|
String | completed high school | |
company_name
|
String | Matheson Tri-Gas | |
job_title
|
String | Manager | |
job_level
|
String | ["Manager"] | |
job_function
|
String | cmo | |
work_emails
|
String | xxxxxxxxxxxx@mathesongas.com | |
company_phones
|
String | (877) xxx-xx27 | |
company_address
|
String | 909 Lake Carolyn Parkway | |
company_city
|
String | Irving | |
company_state
|
String | TX | |
company_postal
|
Integer | 75039 | |
company_sic
|
Integer | 5541 | |
company_naics
|
Integer | 447110 | |
company_primary_industry
|
String | Chemicals | |
recent_job_change
|
Boolean | t | |
linkedin_url
|
String | https://www.linkedin.com/in/xxxxxx-xxxxxxxxx-xxxxxxx | |
facebook_url
|
String | facebook.com/xxx.xxxx.xxx | |
contact_skills
|
Attribute | Type | Example | Mapping |
---|---|---|---|
iid
|
String | ||
hhid
|
String | ||
String | Contact First Name | ||
middle_name
|
String | ||
String | Contact Last Name | ||
suffix
|
String | ||
gender
|
String | ||
age
|
String | ||
dob
|
String | ||
address
|
String | ||
house
|
String | ||
pre_direction
|
String | ||
street
|
String | ||
street_type
|
String | ||
post_direction
|
String | ||
apartment_type
|
String | ||
unit_number
|
String | ||
String | Berlin | City Name | |
String | California | State Name | |
zip
|
String | ||
z4
|
String | ||
dpc
|
String | ||
z4_type
|
String | ||
census_tract
|
String | ||
census_block
|
String | ||
String | Phone Number | ||
phone_sha1
|
String | ||
phone_sha2
|
String | ||
phone_md5
|
String | ||
String | Email Address | ||
String | Hashed Email Address | ||
String | Hashed Email Address | ||
String | Hashed Email Address | ||
emailtype
|
String | ||
String | MAID | ||
String | MAID | ||
String | MAID | ||
String | MAID | ||
device_type
|
String |
Description
Country Coverage
History
Volume
312 million | Consumer ID |
221 million | Phone Number |
222 million | Email ID |
166 million | MAID |
240 million | Profiles |
30.9 million | Email Business |
Pricing
License | Starts at |
---|---|
One-off purchase | Not available |
Monthly License | Not available |
Yearly License | Not available |
Usage-based |
$0.03 / API Call |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Products
Frequently asked questions
What is Factori US Person Data APIs 240M+ profiles:40+ attributes ?
Enhance the potency of your consumer data by integrating Factori’s Person API. Offering an extensive array of over 40 attributes that enrich your understanding of consumers across various dimensions.
What is Factori US Person Data APIs 240M+ profiles:40+ attributes used for?
This product has 5 key use cases. Factori recommends using the data for Retail Site Selection, Real Estate Insights, Government Marketing, Financial Data Enrichment, and Ecommerce Data Enrichment. Global businesses and organizations buy Consumer Behavior Data from Factori to fuel their analytics and enrichment.
Who can use Factori US Person Data APIs 240M+ profiles:40+ attributes ?
This product is best suited if you’re a Enterprise, Medium-sized Business, or Small Business looking for Consumer Behavior 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 US Person Data APIs 240M+ profiles:40+ attributes go?
This product has 1 years of historical coverage. It can be delivered on a real-time basis.
Which countries does Factori US Person Data APIs 240M+ profiles:40+ attributes cover?
This product includes data covering 1 country like USA. Factori is headquartered in United States of America.
How much does Factori US Person Data APIs 240M+ profiles:40+ attributes cost?
Pricing for Factori US Person Data APIs 240M+ profiles:40+ attributes starts at USD0.03 per API Call. Connect with Factori to get a quote and arrange custom pricing models based on your data requirements.
How can I get Factori US Person Data APIs 240M+ profiles:40+ attributes ?
Businesses can buy Consumer Behavior Data from Factori and get the data via REST API. Depending on your data requirements and subscription budget, Factori can deliver this product in .json format.
What is the data quality of Factori US Person Data APIs 240M+ profiles:40+ attributes ?
Factori has reported that this product has the following quality and accuracy assurances: 90% Fill 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 US Person Data APIs 240M+ profiles:40+ attributes ?
This product has 3 related products. These alternatives include Factori Person API USA Shopify + Klaviyo Contact Enrichment Contact,Age,Location, Social Media,Household,Vehicle,DOB,Zipcode, Success.ai B2B Contact Data - Emails & Phone Numbers – APIs - 170M+, Verified Profiles - Best Price Guarantee, and Real-Time Sourced & Verified Recruiting Data Global Coverage 1BN+ Records Personal Emails & Mobile Phone Numbers Access Live Linkedin Data. You can compare the best Consumer Behavior Data providers and products via Datarade’s data marketplace and get the right data for your use case.