Consumer Behavior Data | US | Online 670M People Profiles with Digital Identifiers
|
firstName
|
lastName
|
linkedIn
|
emailVerificationDate
|
businessEmail
|
phone
|
age
|
gender
|
maritalStatus
|
address
|
city
|
state
|
zip
|
isPrimaryResidence
|
householdIncome
|
netWorth
|
incomeLevels
|
peopleInHousehold
|
adultsInHousehold
|
childrenInHousehold
|
veteransInHousehold
|
education
|
creditRange
|
ethnicGroup
|
generation
|
homeOwner
|
occupationDetail
|
politicalParty
|
religion
|
childrenBetweenAges0_3
|
childrenBetweenAges4_6
|
childrenBetweenAges7_9
|
childrenBetweenAges10_12
|
childrenBetweenAges13_18
|
behaviors
|
childrenAgeRanges
|
interests
|
ownsAmexCard
|
ownsBankCard
|
dwellingType
|
homeHeatType
|
homePrice
|
homePurchasedYearsAgo
|
homeValue
|
householdNetWorth
|
language
|
mortgageAge
|
mortgageAmount
|
mortgageLoanType
|
mortgageRefinanceAge
|
mortgageRefinanceAmount
|
mortgageRefinanceType
|
isMultilingual
|
newCreditOfferedHousehold
|
numberOfVehiclesInHousehold
|
ownsInvestment
|
ownsPremiumAmexCard
|
ownsPremiumCard
|
ownsStocksAndBonds
|
personality
|
isPoliticalContributor
|
premiumIncomeHousehold
|
urbanicity
|
zip4
|
dpbc
|
dpv
|
carrierRoute
|
fipsStateCode
|
fipsCountyCode
|
countyName
|
companyName
|
companyRevenue
|
seniorityLevel
|
department
|
jobTitle
|
primaryIndustry
|
companyCity
|
companyState
|
companyDomain
|
companyEmployeeCount
|
companySic
|
|||
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| 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 | 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 | 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 | 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 | 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 | 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 | 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 | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxx |
| xxxxxxxxx | Xxxxx | xxxxx | xxxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | xxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx |
| Xxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxx | Xxxxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxx |
| xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx | xxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxx | xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxxx |
Data Dictionary
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
firstName
|
String | ||
|
lastName
|
String | ||
|
linkedIn
|
String | https://linkedin.com/in/John-Smith-55555555 | |
| String | Email Address | ||
|
emailVerificationDate
|
String | 11/15/2024 | |
|
businessEmail
|
String | Johnsmith@visitiq.io | |
|
phone
|
Integer | ||
|
age
|
|||
|
gender
|
String | ||
|
maritalStatus
|
String | Married | |
|
address
|
String | 1515 Broadway | |
|
city
|
String | Orlando | |
|
state
|
String | FL | |
|
zip
|
Integer | 32810 | |
|
isPrimaryResidence
|
|||
|
householdIncome
|
|||
|
netWorth
|
String | $2,500 to $24,999 | |
|
incomeLevels
|
|||
|
peopleInHousehold
|
|||
|
adultsInHousehold
|
|||
|
childrenInHousehold
|
|||
|
veteransInHousehold
|
|||
|
education
|
|||
|
creditRange
|
|||
|
ethnicGroup
|
|||
|
generation
|
|||
|
homeOwner
|
String | Home Owner | |
|
occupationDetail
|
|||
|
politicalParty
|
|||
|
religion
|
|||
|
childrenBetweenAges0_3
|
|||
|
childrenBetweenAges4_6
|
|||
|
childrenBetweenAges7_9
|
|||
|
childrenBetweenAges10_12
|
|||
|
childrenBetweenAges13_18
|
|||
|
behaviors
|
|||
|
childrenAgeRanges
|
|||
|
interests
|
|||
|
ownsAmexCard
|
|||
|
ownsBankCard
|
|||
|
dwellingType
|
|||
|
homeHeatType
|
|||
|
homePrice
|
|||
|
homePurchasedYearsAgo
|
|||
|
homeValue
|
|||
|
householdNetWorth
|
|||
|
language
|
|||
|
mortgageAge
|
|||
|
mortgageAmount
|
|||
|
mortgageLoanType
|
|||
|
mortgageRefinanceAge
|
|||
|
mortgageRefinanceAmount
|
|||
|
mortgageRefinanceType
|
|||
|
isMultilingual
|
|||
|
newCreditOfferedHousehold
|
|||
|
numberOfVehiclesInHousehold
|
|||
|
ownsInvestment
|
|||
|
ownsPremiumAmexCard
|
|||
|
ownsPremiumCard
|
|||
|
ownsStocksAndBonds
|
|||
|
personality
|
|||
|
isPoliticalContributor
|
|||
|
premiumIncomeHousehold
|
|||
|
urbanicity
|
|||
| String | MAID | ||
| String | MAID | ||
|
zip4
|
|||
|
dpbc
|
|||
|
dpv
|
|||
|
carrierRoute
|
|||
|
fipsStateCode
|
|||
|
fipsCountyCode
|
|||
|
countyName
|
|||
|
companyName
|
String | Express Floors | |
|
companyRevenue
|
String | Under 1 Million | |
|
seniorityLevel
|
String | Cxo | |
|
department
|
String | Executive | |
|
jobTitle
|
String | Owner | |
|
primaryIndustry
|
|||
|
companyCity
|
String | Orlando | |
|
companyState
|
String | FL | |
|
companyDomain
|
|||
|
companyEmployeeCount
|
String | 1 to 10 | |
|
companySic
|
| Attribute | Type | Example | Mapping |
|---|---|---|---|
| String | 9fbf6902-3259-43e0-b84d-c802b1940899 | POI ID | |
| String | Contact First Name | ||
| String | Contact Last Name | ||
| String | Address | ||
| String | Toledo | City Name | |
| String | OH | State Abbreviation | |
| Integer | 12345 | ZIP Code | |
| String | Polk | County Name | |
| String | Contact Email Address | ||
| String | Email Address | ||
| String | Phone Number |
Description
Country Coverage
History
Volume
| 670 million | People Profiles |
Pricing
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
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US Household-Level Consumer Data | US Online Consumer Behavior Database 98% Coverage
Identity Linkage Data | USA Coverage | Scale large quantities
Frequently asked questions
What is Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers?
Identity Graph Data available for U.S. based consumers, representative of 98% of consumer households and including 670 Million people profiles.
What is Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers used for?
This product has 4 key use cases. VisitIQ™ recommends using the data for Identity Resolution, 360-Degree Customer View, Identity-Based Targeting, and Identity Validation. Global businesses and organizations buy Identity Graph Data from VisitIQ™ to fuel their analytics and enrichment.
Who can use Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Identity Graph Data. Get in touch with VisitIQ™ to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers go?
This product has 30 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, and on-demand basis.
Which countries does Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers cover?
This product includes data covering 1 country like USA. VisitIQ™ is headquartered in United States of America.
How much does Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers cost?
Pricing information for Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers is available by getting in contact with VisitIQ™. Connect with VisitIQ™ to get a quote and arrange custom pricing models based on your data requirements.
How can I get Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers?
Businesses can buy Identity Graph Data from VisitIQ™ and get the data via SOAP API, S3 Bucket, SFTP, UI Export, and REST API. Depending on your data requirements and subscription budget, VisitIQ™ can deliver this product in .json, .csv, .xls, and .txt format.
What is the data quality of Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers?
VisitIQ™ has reported that this product has the following quality and accuracy assurances: 98% accuracy. You can compare and assess the data quality of VisitIQ™ using Datarade’s data marketplace. VisitIQ™ has received 3 reviews from clients.
What are similar products to Consumer Behavior Data US Online 670M People Profiles with Digital Identifiers?
This product has 3 related products. These alternatives include Identity Data Americas Hashed Email with MAIDs & Login Metadata, Consumer Marketing Data, Audience Targeting Data- B2C Consumer Audience Builder USA - Identity Graph Data, and US Household-Level Consumer Data US Online Consumer Behavior Database 98% Coverage. 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.
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