WalkLists | Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers)
# | Dwelling Type |
Homeowner Probability Model |
Length of Residence |
Number of Persons in Unit |
Single Parent In Household |
Disabled In Household |
Christian Family |
Working Woman In Household |
African-American Professional In Household |
Home Office Indicator |
TV Sat Dish |
Home Swimming Pool |
Home Air Conditioning |
Home Heating |
Home Sewer |
Home Water |
Census Median Home Value |
Census Median Household Income |
Population Density |
Property Home Square Footage |
Property Land Square Footage |
Estimated Income |
Household Net Worth |
Presence of Credit Card |
Presence of Gold or Platinum Credit Card |
Presence of Upscale Retail Credit Card |
Presence of BankCard |
Gas Dept Retail Credit Card |
American Express Credit Card |
Bank Rating |
Household Number Lines of Credit |
Credit Range of New Credit |
Investments -- Estimated Real Estate Property Onwed |
Inferred Age Rank Within Household |
Number of Adults |
Generations in Household |
Males 18 to 24 |
Femals 18 to 24 |
Unknown Gender |
Males 25 To 34 |
Females 25 To 34 |
Unknown Gender 25 To 34 |
Males 35 To 44 |
Females 35 To 44 |
Unknown Gender 35 To 44 |
Males 45 To 54 |
Females 45 To 54 |
Unknown Gender |
Males 55 To 64 |
Females 55 To 64 |
Unknown Gender 55 To 64 |
Males 65 To 74 |
Females 65 To 74 |
Unknown Gender 65 To 74 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 |
2 | 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 | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx |
3 | 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 |
4 | 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 | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx |
5 | 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 |
6 | 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 |
7 | 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 |
8 | 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 |
9 | 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 |
10 | 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 |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
Dwelling Type
|
Multiple Family Dwelling Unit | ||
Homeowner Probability Model
|
Home Owner | ||
Length of Residence
|
01 Year | ||
Number of Persons in Unit
|
1 | ||
Single Parent In Household
|
Yes | ||
Disabled In Household
|
Yes | ||
Christian Family
|
Yes | ||
Working Woman In Household
|
yes | ||
African-American Professional In Household
|
Yes | ||
Home Office Indicator
|
Yes | ||
TV Sat Dish
|
Yes | ||
Home Swimming Pool
|
Pool Present | ||
Home Air Conditioning
|
Air Conditioning Package | ||
Home Heating
|
Electric Heating | ||
Home Sewer
|
Commercial Sewer | ||
Home Water
|
Private Water System | ||
Census Median Home Value
|
From To | ||
Census Median Household Income
|
From To | ||
Population Density
|
From To | ||
Property Home Square Footage
|
From To | ||
Property Land Square Footage
|
From To | ||
Estimated Income
|
50000 To 54999 | ||
Household Net Worth
|
250000 to 499999 | ||
Presence of Credit Card
|
Yes | ||
Presence of Gold or Platinum Credit Card
|
Yes | ||
Presence of Upscale Retail Credit Card
|
Yes | ||
Presence of BankCard
|
Yes | ||
Gas Dept Retail Credit Card
|
Yes | ||
American Express Credit Card
|
Yes | ||
Bank Rating
|
0 To 499 | ||
Household Number Lines of Credit
|
3 | ||
Credit Range of New Credit
|
5--1001 To 3000 | ||
Investments -- Estimated Real Estate Property Onwed
|
2 | ||
Inferred Age Rank Within Household
|
3rd | ||
Number of Adults
|
4 Adults | ||
Generations in Household
|
3 Generations - Adult/Child/Parent | ||
Males 18 to 24
|
Yes | ||
Femals 18 to 24
|
Yes | ||
Unknown Gender
|
Yes | ||
Males 25 To 34
|
Yes | ||
Females 25 To 34
|
Yes | ||
Unknown Gender 25 To 34
|
Yes | ||
Males 35 To 44
|
Yes | ||
Females 35 To 44
|
Yes | ||
Unknown Gender 35 To 44
|
Yes | ||
Males 45 To 54
|
Yes | ||
Females 45 To 54
|
Yes | ||
Unknown Gender
|
Yes | ||
Males 55 To 64
|
Yes | ||
Females 55 To 64
|
Yes | ||
Unknown Gender 55 To 64
|
Yes | ||
Males 65 To 74
|
Yes | ||
Females 65 To 74
|
Yes | ||
Unknown Gender 65 To 74
|
Yes |
Description
Country Coverage
History
Volume
240 million | records |
Pricing
License | Starts at |
---|---|
One-off purchase |
$300 / purchase |
Monthly License | Not available |
Yearly License |
$10,000 / year |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers)?
Access to a database of more than 240 million USA Individual consumers with information about their home life and household characteristics such as the Type of Dwelling, Length of Residence, Single Parent Household, Estimated Income Level, Children in Household, Adults in Household, and many more.
What is WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers) used for?
This product has 5 key use cases. ScaleCampaign recommends using the data for Advertising, Consumer Intelligence, automobile purchasing, household infomation, and housing. Global businesses and organizations buy Property Owner Data from ScaleCampaign to fuel their analytics and enrichment.
Who can use WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers)?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Property Owner Data. Get in touch with ScaleCampaign to see what their data can do for your business and find out which integrations they provide.
How far back does the data in WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers) go?
This product has 12 years of historical coverage. It can be delivered on a monthly, quarterly, yearly, and on-demand basis.
Which countries does WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers) cover?
This product includes data covering 1 country like USA. ScaleCampaign is headquartered in United States of America.
How much does WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers) cost?
Pricing for WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers) starts at USD300 per purchase. Connect with ScaleCampaign to get a quote and arrange custom pricing models based on your data requirements.
How can I get WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers)?
Businesses can buy Property Owner Data from ScaleCampaign and get the data via S3 Bucket, SFTP, and Email. Depending on your data requirements and subscription budget, ScaleCampaign can deliver this product in .csv and .xls format.
What is the data quality of WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers)?
ScaleCampaign has reported that this product has the following quality and accuracy assurances: 100% match rate. You can compare and assess the data quality of ScaleCampaign using Datarade’s data marketplace.
What are similar products to WalkLists Consumer Data Lists Household Residence and Resident Characteristics USA ( >240M Consumers)?
This product has 3 related products. These alternatives include Redmob: Identity Graph USA HEMs & MAIDs I Identity Data I Device Graph I 700M Users, Versium REACH - Consumer Household and Financial Demographic Append (Income, Car Ownership, Financial Data, etc), USA, CCPA Compliant, and Unacast Consumer Data Enrichment. You can compare the best Property Owner Data providers and products via Datarade’s data marketplace and get the right data for your use case.