Datastream Group Insurance Industry Data | Leading Data-as-a-Service Platform
# | LeadQuality |
zip_code |
year |
make |
model |
submodel |
owned_or_leased |
distance |
annual_distance |
deductible |
deductible2 |
Prefered level of coverage |
has_coverage |
former_insurer |
months_insured |
expiration_date |
relationship |
birthdate |
gender |
marital_status |
Military experience |
occupation |
driver_state |
license_status |
sr22 |
incidentpop |
address |
city |
state |
own_or_rent |
credit_rating |
primary_phone |
email |
address2 |
county |
years_at_address |
secondary_phone |
contact_method |
age |
occupation_years |
highest_level |
revoked |
repossessions |
licensed_age |
bankruptcy |
at_home_student |
IsGoodStudent |
days_used |
use |
location_parked |
antitheft |
VinInPolk |
type |
bodilyinjury_person |
bodilyinjury_accident |
propertydamage |
ip_address |
||
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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 | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx |
2 | 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 | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx |
3 | 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 | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx |
4 | 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 | 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 |
5 | 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 | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx |
6 | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | 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 |
7 | 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 |
8 | xxxxxx | xxxxxxxx | Xxxxxxxx | 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 | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx |
9 | 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 |
10 | 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 | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxx |
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Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
LeadQuality
|
String | PREFERRED | |
zip_code
|
Integer | 98408 | |
year
|
Integer | 2012 | |
make
|
String | VOLKSWAGEN | |
model
|
String | PASSAT | |
submodel
|
String | 1VWBM7A30CC000000*PASSAT-Sedan | |
owned_or_leased
|
String | Owned | |
distance
|
Integer | 9 | |
annual_distance
|
Integer | 12500 | |
deductible
|
Integer | 500 | |
deductible2
|
Integer | 500 | |
Prefered level of coverage
|
String | Standard Coverage | |
has_coverage
|
Boolean | t | |
former_insurer
|
String | Other | |
months_insured
|
Integer | 12 | |
expiration_date
|
String | 2/8/2022 | |
relationship
|
String | Self | |
String | Contact First Name | ||
String | Contact Last Name | ||
birthdate
|
String | 5/1/1968 | |
gender
|
String | ||
marital_status
|
String | Single | |
Military experience
|
Boolean | f | |
occupation
|
String | Unknown | |
driver_state
|
String | WA | |
license_status
|
String | Valid | |
sr22
|
Boolean | f | |
incidentpop
|
Boolean | f | |
address
|
String | 7646 s c st Tacoma wa | |
city
|
String | Tacoma | |
state
|
String | WA | |
own_or_rent
|
String | OWN | |
credit_rating
|
String | Good | |
primary_phone
|
String | 253-228-6062 | |
email
|
String | ||
address2
|
|||
county
|
|||
years_at_address
|
Integer | 1 | |
secondary_phone
|
String | 253-228-6062 | |
contact_method
|
String | phone | |
age
|
Integer | ||
occupation_years
|
Integer | 3 | |
highest_level
|
String | HighSchoolDiploma | |
revoked
|
Boolean | f | |
repossessions
|
Boolean | f | |
licensed_age
|
Integer | 16 | |
bankruptcy
|
Boolean | f | |
at_home_student
|
Boolean | f | |
IsGoodStudent
|
Integer | 1 | |
days_used
|
Integer | 5 | |
use
|
String | Commute_Work | |
location_parked
|
String | No Cover | |
antitheft
|
String | Alarm | |
VinInPolk
|
Integer | 1 | |
type
|
String | PREFERRED | |
bodilyinjury_person
|
Integer | 100000 | |
bodilyinjury_accident
|
Integer | 300000 | |
propertydamage
|
Integer | 50000 | |
ip_address
|
String |
Attribute | Type | Example | Mapping |
---|---|---|---|
varies by vertical
|
Description
Geography
History
Volume
40 | million records |
Pricing
License | Starts at |
---|---|
One-off purchase |
$500 / purchase |
Monthly License | Not available |
Yearly License | Not available |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform?
The Datastream US Consumer Insurance file contains known instances of an insurance policy connected to individuals in our Consumer Database. Verticals include, Home, Health, Auto, and Life.
What is Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform used for?
This product has 3 key use cases. Datastream Group recommends using the data for Identity-Based Targeting, Cross Device Identity Management, and Insurance marketing. Global businesses and organizations buy Insurance Data from Datastream Group to fuel their analytics and enrichment.
Who can use Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Insurance Data. Get in touch with Datastream Group to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform go?
This Text Data has 3 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.
Which countries does Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform cover?
This product includes data covering 1 country like USA. Datastream Group is headquartered in United States of America.
How much does Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform cost?
Pricing for Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform starts at USD500 per purchase. Connect with Datastream Group to get a quote and arrange custom pricing models based on your data requirements.
How can I get Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform?
Businesses can buy Insurance Data from Datastream Group and get the data via SFTP and Email. Depending on your data requirements and subscription budget, Datastream Group can deliver this product in .csv and .txt format.
What is the data quality of Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform?
Datastream Group has reported that this product has the following quality and accuracy assurances: 80% match rate. You can compare and assess the data quality of Datastream Group using Datarade’s data marketplace. Datastream Group 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 Datastream Group Insurance Industry Data Leading Data-as-a-Service Platform?
This Text Data has 3 related products. These alternatives include Pixta AI Imagery Data Global 5,000 Stock Images Annotation and Labelling Services Provided Full-body human images for AI & ML, Healthcare Contact Data Hospital Industry Data Global Coverage Doctors, Nurses 200M+ Contacts (Verified E-mail, Direct Dails) , and Factori US Person Data APIs 240M+ profiles:40+ attributes . You can compare the best Insurance Data providers and products via Datarade’s data marketplace and get the right data for your use case.