
Identity Data | Consumer Identity Graph
# | Consumer |
---|---|
1 | xxxxxxxxxx |
2 | Xxxxxxxxx |
3 | xxxxxx |
4 | xxxxxxxxxx |
5 | Xxxxx |
6 | Xxxxxx |
7 | Xxxxxxxxxx |
8 | Xxxxxx |
9 | Xxxxxxxxx |
10 | Xxxxxxxxxx |
... | xxxxxxxxx |
# | individualid |
first_name |
middle_name |
last_name |
name_suffix |
address |
city |
state |
zip |
zip4 |
dpbc |
carrier_route |
fips_state_code |
fips_county_code |
county_name |
address_type |
cbsa |
census_tract |
census_block_group |
census_block |
gender |
addr_primary |
addr_pre |
addr_street |
addr_post |
addr_suffix |
addr_abrev |
addr_secy |
prop_type |
address_id |
household_id |
scf |
dma |
msa |
congressional_district |
urbanicity_code |
addeddate |
updatedate |
confidencelevel |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | 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 |
3 | 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 | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx |
4 | 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 |
5 | 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 |
6 | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | 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 | Xxxxxxxx | Xxxxxxx |
7 | 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 | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx |
8 | 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 |
9 | 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 |
10 | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | 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 | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
Consumer
|
String | individualid |
Attribute | Type | Example | Mapping |
---|---|---|---|
individualid
|
Integer | 2741734770 | |
first_name
|
String | ||
middle_name
|
|||
last_name
|
String | ||
name_suffix
|
|||
address
|
String | **** ****** ** | |
city
|
String | *********** | |
state
|
String | CA | |
zip
|
Integer | 93301 | |
zip4
|
Integer | 3325 | |
dpbc
|
Integer | 128 | |
carrier_route
|
String | C004 | |
fips_state_code
|
Integer | 6 | |
fips_county_code
|
Integer | 29 | |
county_name
|
String | Kern | |
address_type
|
String | S | |
cbsa
|
Integer | 12540 | |
census_tract
|
Integer | 1700 | |
census_block_group
|
Integer | 3 | |
census_block
|
|||
gender
|
String | ||
addr_primary
|
String | **** ****** ** | |
addr_pre
|
|||
addr_street
|
String | ****** | |
addr_post
|
|||
addr_suffix
|
String | ** | |
addr_abrev
|
String | *********** | |
addr_secy
|
|||
prop_type
|
|||
address_id
|
Integer | 24183558 | |
household_id
|
Integer | 2261053251 | |
scf
|
Integer | 933 | |
dma
|
Integer | 800 | |
msa
|
Integer | 680 | |
congressional_district
|
Integer | 20 | |
urbanicity_code
|
String | U | |
addeddate
|
String | 5/24/2023 | |
updatedate
|
String | 12/6/2023 | |
confidencelevel
|
Integer | 2 |
Attribute | Type | Example | Mapping |
---|---|---|---|
varies per audience
|
Description
Country Coverage
History
Pricing
License | Starts at |
---|---|
One-off purchase | Available |
Monthly License | Available |
Yearly License | Available |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Identity Data Consumer Identity Graph?
Datasys provides one of the largest consumer data sets with over 350M Consumer Profiles, having 500+ demographic and psychographic key elements, and 4,000+ online behavior segments.
What is Identity Data Consumer Identity Graph used for?
This product has 5 key use cases. Datasys recommends using the data for Audience Segmentation, Consumer Profiling, Audience Creation, Audience Activation, and Data Driven Marketing. Global businesses and organizations buy Identity Graph Data from Datasys to fuel their analytics and enrichment.
Who can use Identity Data Consumer Identity Graph?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Identity Graph Data. Get in touch with Datasys to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Identity Data Consumer Identity Graph go?
This product has 2 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, and on-demand basis.
Which countries does Identity Data Consumer Identity Graph cover?
This product includes data covering 1 country like USA. Datasys is headquartered in United States of America.
How much does Identity Data Consumer Identity Graph cost?
Pricing information for Identity Data Consumer Identity Graph is available by getting in contact with Datasys. Connect with Datasys to get a quote and arrange custom pricing models based on your data requirements.
How can I get Identity Data Consumer Identity Graph?
Businesses can buy Identity Graph Data from Datasys and get the data via S3 Bucket, SFTP, and Email. Depending on your data requirements and subscription budget, Datasys can deliver this product in .csv, .xls, and .txt format.
What is the data quality of Identity Data Consumer Identity Graph?
Datasys has reported that this product has the following quality and accuracy assurances: 95% accuracy. You can compare and assess the data quality of Datasys using Datarade’s data marketplace. Datasys appears on selected Datarade top lists ranking the best data providers, including Top 10 Identity & Device Graph Data Providers In the US.
What are similar products to Identity Data Consumer Identity Graph?
This product has 3 related products. These alternatives include Consumer Marketing Data, Audience Targeting Data- B2C Consumer Audience Builder USA - Identity Graph Data, Consumer Behavior Data B2C Individual Consumer US 300 Million Records Identity Graph, Linkage, Modeling, AI, Propecting, Audience, and Audience Data 750M+ User Profiles 300M+ Updates a Month, Accurate Consumer Behavior & Identity Insights. You can compare the best Identity Graph Data providers and products via Datarade’s data marketplace and get the right data for your use case.