Consumer Behavior Data | VisitIQ™ | US Online Consumer Behavior Database
# | firstName |
lastName |
linkedIn |
email |
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 |
maid |
maidOs |
zip4 |
dpbc |
dpv |
carrierRoute |
fipsStateCode |
fipsCountyCode |
countyName |
companyName |
companyRevenue |
seniorityLevel |
department |
jobTitle |
primaryIndustry |
companyCity |
companyState |
companyDomain |
companyEmployeeCount |
companySic |
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2 | 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 | 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 |
3 | 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 |
4 | 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 |
5 | 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 |
6 | 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 |
7 | 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 |
8 | 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 |
9 | 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 |
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Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
firstName
|
String | ||
lastName
|
String | ||
linkedIn
|
String | https://linkedin.com/in/John-Smith-55555555 | |
email
|
String | ||
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
|
|||
maid
|
|||
maidOs
|
|||
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 | Contact First Name | ||
String | Contact Last Name | ||
String | Contact Facebook URL | ||
String | Contact LinkedIn | ||
String | Contact LinkedIn | ||
String | Email Address | ||
optIn
|
Boolean | t | |
optInDate
|
DateTime | 2021-06-21T00:00:00+00:00 | |
PixelFirstHitDate
|
DateTime | 2021-06-21T00:00:00+00:00 | |
PixelLastHitDate
|
DateTime | 2021-06-21T00:00:00+00:00 | |
String | Phone Number | ||
dnc
|
|||
String | Contact Age | ||
String | Contact Gender | ||
maritalStatus
|
String | Single | |
String | Address | ||
city
|
String | Cocoa | |
String | FL | State Name | |
zip
|
Integer | 32926 | |
householdIncome
|
String | C. $20,000-$29,999 | |
netWorth
|
String | B. Less than $1 | |
incomeLevels
|
String | LT_30K | |
education
|
String | Some College | |
creditRange
|
String | i. Unknown | |
ethnicGroup
|
String | White | |
generation
|
String | 1. Millenials and Gen Z (1982 and after) | |
homeOwner
|
String | Home Owner | |
occupationDetail
|
String | Self Employed | |
politicalParty
|
String | NA/Unknown | |
religion
|
String | Portestant | |
premiumIncomeHousehold
|
String | AA. Unknown | |
String | MAID | ||
String | MAID |
Description
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Pricing
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Frequently asked questions
What is Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database?
Our Consumer Behavior Data database provides comprehensive insights into the current US online consumer-behavior trends. Packed with thousands of indexes of product consumption, lifestyle preferences, product ownership, and attitudes, it is the perfect dataset for studying consumer behaviors.
What is Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database used for?
This product has 5 key use cases. VisitIQ™ recommends using the data for Marketing, Online Advertising, Consumer Trend Analysis, Consumer Profiling, and Consumer Data Enrichment. Global businesses and organizations buy Consumer Behavior Data from VisitIQ™ to fuel their analytics and enrichment.
Who can use Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Consumer Behavior Data. Get in touch with VisitIQ™ to see what their data can do for your business and find out which integrations they provide.
Which countries does Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database cover?
This product includes data covering 1 country like USA. VisitIQ™ is headquartered in United States of America.
How much does Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database cost?
Pricing information for Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database 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 VisitIQ™ US Online Consumer Behavior Database?
Businesses can buy Consumer Behavior Data from VisitIQ™ and get the data via S3 Bucket, Email, and UI Export. Depending on your data requirements and subscription budget, VisitIQ™ can deliver this product in .csv, .xls, and .txt format.
What is the data quality of Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database?
You can compare and assess the data quality of VisitIQ™ using Datarade’s data marketplace. VisitIQ™ has received 3 reviews from clients. VisitIQ™ appears on selected Datarade top lists ranking the best data providers, including Best +8 License Plate Lookup APIs to use in 2023.
What are similar products to Consumer Behavior Data VisitIQ™ US Online Consumer Behavior Database?
This product has 3 related products. These alternatives include Consumer Review Data Consumer Behavior Reasons of the calls from consumers to companies, VisitIQ™ Psychographic Data: Consumer Insight into Behavioral Habits and Interests., and BIGDBM US Consumer Demographics 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.