Datastream Group Automotive Ownership Data USA with Consumer Demographics
# | Id |
Name_Suffix |
Zip |
Zip4 |
Dpbc |
Carrier_Route |
Walk_Sequence_Code |
Lot |
Fips_State_Code |
Fips_County_Code |
Address_Type |
Msa |
Cbsa |
Census_Tract |
Census_Block_Group |
Census_Block |
Census_Median_Home_Value |
Census_Median_Hh_Income |
Landline_Present_Flag |
Area_Code_And_Phone_Number |
Gender |
Homeowner |
Dob_Yr |
Dob_Mon |
Dob_Day |
Exact_Age |
Age_Range |
HH_Income |
Net_Worth |
Credit_Lines |
Credit_Range_New |
Education_Level |
Occupation |
Occ_Busn_Ownr |
Num_Kids |
Pres_Kids |
Kids_M_0_2 |
Kids_F_0_2 |
Kids_U_0_2 |
Kids_M_3_5 |
Kids_F_3_5 |
Kids_U_3_5 |
Kids_M_6_10 |
Kids_F_6_10 |
Kids_U_6_10 |
Kids_M_11_15 |
Kids_F_11_15 |
Kids_U_11_15 |
Kids_M_16_17 |
Kids_F_16_17 |
Kids_U_16_17 |
Hh_Marital_Status |
Length_Of_Residence |
Dwell_Type |
Num_Adults |
Hh_Size |
Home_Mkt_Value |
Generations |
Adults_M_18_24 |
Adults_F_18_24 |
Adults_U_18_24 |
Adults_M_25_34 |
Adults_F_25_34 |
Adults_U_25_34 |
Adults_M_35_44 |
Adults_F_35_44 |
Adults_U_35_44 |
Adults_M_45_54 |
Adults_F_45_54 |
Adults_U_45_54 |
Adults_M_55_64 |
Adults_F_55_64 |
Adults_U_55_64 |
Adults_M_65_74 |
Adults_F_65_74 |
Adults_U_65_74 |
Adults_M_75Plus |
Adults_F_75Plus |
Adults_U_75Plus |
Buy_Mo_Buyer |
Buy_Mo_Respdr |
Buy_Ol_Purch_Ind |
Buy_Mem_Clubs |
Buy_Value_Priced |
Buy_Wmns_Apparel |
Buy_Wmns_Petite_Apparel |
Buy_Wmns_Plus_Apparel |
Buy_Young_Wmns_Apparel |
Buy_Mns_Apparel |
Buy_Mns_Big_Apparel |
Buy_Young_Mns_Apparel |
Buy_Kids_Apparel |
Buy_Health_Beauty |
Buy_Cosmetics |
Buy_Jewelry |
Buy_Luggage |
Cc_Amex_Prem |
Cc_Amex_Reg |
Cc_Disc_Prem |
Cc_Disc_Reg |
Cc_Gas_Prem |
Cc_Gas_Reg |
Cc_Mc_Prem |
Cc_Mc_Reg |
Cc_Visa_Prem |
Cc_Visa_Reg |
Cc_Hldr_Bank |
Cc_Hldr_Gas |
Cc_Hldr_Te |
Cc_Hldr_Unk |
Cc_Hldr_Prem |
Cc_Hldr_Ups_Dept |
Cc_User |
Cc_New_Issue |
Cc_Bank_Cd_In_Hh |
Invest_Act |
Invest_Pers |
Invest_Rl_Est |
Invest_Stocks |
Invest_Read_Fin_News |
Invest_Money_Seekr |
Int_Grp_Invest |
Invest_Foreign |
Invest_Est_Prop_Own |
Int_Grp_Donor |
Donr_Mail_Ord |
Donr_Charitable |
Donr_Animal |
Donr_Arts |
Donr_Kids |
Donr_Wildlife |
Donr_Environ |
Donr_Health |
Donr_Intl_Aid |
Donr_Pol |
Donr_Pol_Cons |
Donr_Pol_Lib |
Donr_Relig |
Donr_Vets |
Donr_Oth |
Donr_Comm_Char |
Vet_In_Hh |
Int_Oth_Parenting |
Single_Parent |
Buy_Infant_Apparel |
Buy_Kids_Learn_Toys |
Buy_Kids_Baby_Care |
Buy_Kids_School |
Buy_Kids_Genl |
Young_Adult_In_Hh |
Sr_Adult_In_Hh |
Int_Oth_Kids_Ints |
Int_Oth_Grandkids |
Int_Oth_Christian_Fam |
Buy_Pets |
Int_Oth_Pets_Horse |
Int_Oth_Pets_Cat |
Int_Oth_Pets_Dog |
Int_Oth_Pets_Oth |
Int_Oth_Career_Imp |
Occ_Working_Wmn |
Occ_Afric_Amer_Prof |
Occ_Soho_Ind |
Int_Oth_Career |
Buy_Magazines |
Buy_Books |
Buy_Audio_Books |
Read_Avid |
Read_Relig |
Read_Scifi |
Read_Magazines |
Read_Audio_Books |
Int_Grp_Read |
Read_Hist_Mltry |
Read_Curr_Affairs |
Buy_Religious |
Read_Science_Space |
Mags |
Ent_Educ_Ol |
Ent_Gaming |
Occ_Comp_Genl |
Ent_Dvd_Videos |
Ent_Tv_Video_Movie |
Occ_Home_Off |
Ent_Hi_End_Appl |
Ent_Hdtv_Int |
Ent_Stereo |
Ent_Music_Playr |
Ent_Music_Coll |
Ent_Music_Avid |
Ent_Movie_Coll |
Ent_Cable_Tv |
Ent_Video_Gaming |
Ent_Sat_Dish |
Ent_Computers |
Ent_Pc_Gaming |
Ent_Cons_Elec |
Int_Grp_Movie_Music |
Int_Grp_Elec |
Int_Oth_Telcomm |
Buy_Antiques |
Buy_Art |
Ent_Theater |
Int_Oth_The_Arts |
Ent_Mus_Instr |
Int_Coll_Genl |
Int_Coll_Stamps |
Int_Coll_Coins |
Int_Coll_Arts |
Int_Coll_Antiques |
Int_Coll_Avid |
Int_Grp_Coll |
Int_Coll_Sports |
Int_Coll_Mil |
Buy_Collectibles |
Int_Hob_Diy |
Int_Auto_Wk |
Int_Hob_Sew |
Int_Hob_Woodwk |
Int_Hob_Photo |
Int_Aviation |
Int_Hob_House_Plant |
Int_Hob_Crafts |
Int_Hob_Gardening |
Buy_Gardening |
Buy_Home_Gard |
Int_Grp_Home_Imp |
Buy_Crafts |
Buy_Photo_Video |
Int_Oth_Smoking |
Int_Oth_Home_Dec |
Int_Hob_Home_Imp |
Int_Oth_Home_Imp_Int |
Int_Oth_Cook_Wine |
Int_Oth_Cook_Gnrl |
Int_Oth_Cook_Gourmet |
Int_Oth_Cook_Nat_Food |
Int_Grp_Cook |
Int_Hob_Games |
Int_Trav_Casino |
Int_Hob_Sweeps |
Int_Grp_Travel |
Int_Trav_Genl |
Int_Trav_Us |
Int_Trav_Intl |
Int_Trav_Cruise |
Life_Home |
Life_Diy |
Life_Sporty |
Life_Upscale |
Life_Culture |
Life_Highbrow |
Life_Ht |
Life_Common |
Life_Prof |
Life_Broader |
Int_Grp_Exer |
Int_Fit_Jog |
Int_Fit_Walk |
Int_Fit_Aerob |
Int_Sport_Spect_Auto |
Int_Sport_Spect_Tv_Sports |
Int_Sport_Spect_Foot |
Int_Sport_Spect_Base |
Int_Sport_Spect_Bskt |
Int_Sport_Spect_Hockey |
Int_Sport_Spect_Soccer |
Int_Sport_Tennis |
Int_Sport_Golf |
Int_Sport_Snow_Ski |
Int_Sport_Mtrcycl |
Int_Sport_Nascar |
Int_Sport_Boating |
Int_Sport_Scuba |
Buy_Sport_Leis |
Buy_Hunting |
Int_Sport_Fishing |
Int_Sport_Camp |
Int_Sport_Shoot |
Int_Grp_Sports |
Int_Grp_Outdoor |
Int_Fit_Health_Med |
Int_Fit_Diet |
Int_Fit_Self_Imp |
Buy_Auto_Parts |
Genl_Pp_Home_Value |
Genl_Purch_Dt |
Genl_Purch_Amt |
Genl_Sls_Trans |
Mr_Amt |
Mr2_Amt |
P1_Amt |
P2_Amt |
Mr_Dt |
Mr2_Dt |
P1_Dt |
Mr_Loan_Typ |
Mr2_Loan_Typ |
P1_Loan_Typ |
P2_Loan_Typ |
Mr_Lendr_Cd |
Mr2_Lendr_Cd |
P1_Lendr_Cd |
Mr_Lendr |
Mr2_Lendr |
P1_Lendr |
Mr_Rate_Typ |
Mr2_Rate_Typ |
P1_Rate_Typ |
P2_Rate_Typ |
Mr_Rate |
Mr2_Rate |
P1_Rate |
P2_Rate |
Prop_Bld_Yr |
Prop_Ac |
Prop_Pool |
Prop_Fuel |
Prop_Sewer |
Prop_Water |
Genl_Loan_To_Value |
Ethnic_Code |
Ethnic_Conf |
Ethnic_Grp |
Ethnic_Lang |
Ethnic_Relig |
Ethnic_Hisp_Cntry |
Ethnic_Assim |
Credit_Rating |
Dnc_Flag |
Perm_Id |
Addr_Primary |
Addr_Pre |
Addr_Street |
Addr_Post |
Addr_Suffix |
Addr_Abrev |
Addr_Secy |
Prop_Type |
Telephone_Landline_2 |
Cellphone_1 |
Cellphone_Carrier_1 |
Cellphone_Dnc_Flag_1 |
Telephone_Work_1 |
Url |
Ip |
Optin_Date |
Email_Verify_Flag |
Domain |
Cellphone_2 |
Providersms |
Cellphone_Carrier_2 |
Cell_Phone_Date |
Auto_Make |
Auto_Model_ |
Auto_Year_ |
Auto_Vin_ |
Auto_Tdate_ |
Auto_Trim |
Auto_Style |
Auto_Vehicle_Type |
Auto_Body_Type |
Auto_Msrp |
Auto_Fuel_Type |
Auto_Def_Engine_Cylinders |
Auto_Def_Trans_Type |
Auto_Max_Payload |
Auto_Mfg_Code |
Auto_Gvw_Range |
Number_of_vehicles_in_HH |
Party_Affiliation |
Driverslicensestate |
Driverslicenseeverrevoked |
AutoHasABS |
AutoHasAirbags |
AutoAlarmType |
Autoinscompany |
Autoinsuredsince |
Autoinsexpirydate |
Autoinscoveragetype |
Autoinsbodilyinjurycoverage |
Autoinspropertydamagecoverage |
Autoinscollisiondeductible |
Autoinscomprehensivedeductible |
AutoAnnualMiles |
AI_Autoyear |
AI_Automake |
AI_Automodel |
Autocommutedistance |
Autoinscoveragetyperequested |
Autoprimaryuse |
Auto_Insurance_Date |
Address_ID |
Household_ID |
CAPE: Inc: HH: Median Family Household Income |
CAPE: Age: Pop: Median Age |
CAPE: Age: Pop: % 0-17 |
CAPE: Age: Pop: % 18-99+ |
CAPE: Age: Pop: % 65-99+ |
CAPE: Ethnic: Pop: % White Only |
CAPE: Ethnic: Pop: % Black Only |
CAPE: Ethnic: Pop: % Asian Only |
CAPE: Ethnic: Pop: % Hispanic |
CAPE: Density: Persons Per HH for Pop in HH |
CAPE: HHSize: HH: Average Household Size |
CAPE: Typ: HH: % Married Couple Family |
CAPE: Child: HH: % with Persons LT18 |
CAPE: Child: HH: % Marr Couple FamW/ Persons LT18 |
CAPE: Child: HH: % Marr Couple FamW/O Persons LT18 |
CAPE: Lang: HH: % Spanish Speaking |
CAPE: Educ: Pop25+: Median Education Attained |
CAPE: HomVal: OOHU: Median Home Value |
CAPE: HUStr: HU: % Mobile Home |
CAPE: Built: HU: Median Housing Unit Age |
CAPE: Tenancy: OCCHU: % Owner Occupied |
CAPE: Tenancy: OCCHU: % Renter Occupied |
Auto In The Market: New |
Auto In The Market: Used |
Auto In The Market: Used 0-5 Vehicle |
Auto In The Market: Used 6-10 Vehicle |
Auto In The Market: Used 11+ Vehicle |
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Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
Id
|
Integer | 203829865 | |
String | Contact First Name | ||
String | Contact Last Name | ||
Name_Suffix
|
|||
String | Address | ||
String | Austin | City Name | |
String | TX | State Name | |
Zip
|
Integer | 78732 | |
Zip4
|
Integer | 2060 | |
Dpbc
|
Integer | 168 | |
Carrier_Route
|
String | R031 | |
Walk_Sequence_Code
|
|||
Lot
|
|||
Fips_State_Code
|
Integer | 48 | |
Fips_County_Code
|
Integer | 453 | |
String | Travis | County Name | |
Float | 30.36919 | Latitude | |
Float | -97.903707 | Longitude | |
Address_Type
|
String | S | |
Msa
|
Integer | 640 | |
Cbsa
|
Integer | 12420 | |
Census_Tract
|
Integer | 1760 | |
Census_Block_Group
|
Integer | 0 | |
Census_Block
|
Integer | 32 | |
Census_Median_Home_Value
|
|||
Census_Median_Hh_Income
|
|||
Landline_Present_Flag
|
Boolean | t | |
Area_Code_And_Phone_Number
|
Integer | 5122437446 | |
Gender
|
String | ||
Homeowner
|
String | H | |
Dob_Yr
|
Integer | 1973 | |
Dob_Mon
|
Integer | 11 | |
Dob_Day
|
Integer | 1 | |
Exact_Age
|
Integer | 44 | |
Age_Range
|
|||
HH_Income
|
String | S | |
Net_Worth
|
String | I | |
Credit_Lines
|
Integer | 0 | |
Credit_Range_New
|
Integer | 0 | |
Education_Level
|
String | A | |
Occupation
|
Integer | 0 | |
Occ_Busn_Ownr
|
|||
Num_Kids
|
Integer | 0 | |
Pres_Kids
|
|||
Kids_M_0_2
|
|||
Kids_F_0_2
|
|||
Kids_U_0_2
|
|||
Kids_M_3_5
|
|||
Kids_F_3_5
|
|||
Kids_U_3_5
|
|||
Kids_M_6_10
|
|||
Kids_F_6_10
|
|||
Kids_U_6_10
|
|||
Kids_M_11_15
|
|||
Kids_F_11_15
|
|||
Kids_U_11_15
|
|||
Kids_M_16_17
|
|||
Kids_F_16_17
|
|||
Kids_U_16_17
|
|||
Hh_Marital_Status
|
String | M | |
Length_Of_Residence
|
Integer | 6 | |
Dwell_Type
|
String | S | |
Num_Adults
|
Integer | 3 | |
Hh_Size
|
Integer | 2 | |
Home_Mkt_Value
|
String | Q | |
Generations
|
Integer | 1 | |
Adults_M_18_24
|
|||
Adults_F_18_24
|
|||
Adults_U_18_24
|
|||
Adults_M_25_34
|
|||
Adults_F_25_34
|
Boolean | t | |
Adults_U_25_34
|
|||
Adults_M_35_44
|
Boolean | t | |
Adults_F_35_44
|
Boolean | t | |
Adults_U_35_44
|
|||
Adults_M_45_54
|
Boolean | t | |
Adults_F_45_54
|
|||
Adults_U_45_54
|
|||
Adults_M_55_64
|
|||
Adults_F_55_64
|
|||
Adults_U_55_64
|
|||
Adults_M_65_74
|
|||
Adults_F_65_74
|
|||
Adults_U_65_74
|
|||
Adults_M_75Plus
|
|||
Adults_F_75Plus
|
|||
Adults_U_75Plus
|
|||
Buy_Mo_Buyer
|
|||
Buy_Mo_Respdr
|
|||
Buy_Ol_Purch_Ind
|
Boolean | t | |
Buy_Mem_Clubs
|
|||
Buy_Value_Priced
|
Integer | 4 | |
Buy_Wmns_Apparel
|
|||
Buy_Wmns_Petite_Apparel
|
|||
Buy_Wmns_Plus_Apparel
|
|||
Buy_Young_Wmns_Apparel
|
|||
Buy_Mns_Apparel
|
|||
Buy_Mns_Big_Apparel
|
|||
Buy_Young_Mns_Apparel
|
|||
Buy_Kids_Apparel
|
|||
Buy_Health_Beauty
|
|||
Buy_Cosmetics
|
|||
Buy_Jewelry
|
|||
Buy_Luggage
|
|||
Cc_Amex_Prem
|
|||
Cc_Amex_Reg
|
Boolean | t | |
Cc_Disc_Prem
|
|||
Cc_Disc_Reg
|
|||
Cc_Gas_Prem
|
|||
Cc_Gas_Reg
|
|||
Cc_Mc_Prem
|
|||
Cc_Mc_Reg
|
|||
Cc_Visa_Prem
|
|||
Cc_Visa_Reg
|
Boolean | t | |
Cc_Hldr_Bank
|
Boolean | t | |
Cc_Hldr_Gas
|
|||
Cc_Hldr_Te
|
|||
Cc_Hldr_Unk
|
Boolean | t | |
Cc_Hldr_Prem
|
|||
Cc_Hldr_Ups_Dept
|
|||
Cc_User
|
Boolean | t | |
Cc_New_Issue
|
|||
Cc_Bank_Cd_In_Hh
|
Boolean | t | |
Invest_Act
|
|||
Invest_Pers
|
|||
Invest_Rl_Est
|
|||
Invest_Stocks
|
|||
Invest_Read_Fin_News
|
|||
Invest_Money_Seekr
|
|||
Int_Grp_Invest
|
|||
Invest_Foreign
|
|||
Invest_Est_Prop_Own
|
Integer | 0 | |
Int_Grp_Donor
|
|||
Donr_Mail_Ord
|
|||
Donr_Charitable
|
|||
Donr_Animal
|
|||
Donr_Arts
|
|||
Donr_Kids
|
|||
Donr_Wildlife
|
|||
Donr_Environ
|
|||
Donr_Health
|
|||
Donr_Intl_Aid
|
|||
Donr_Pol
|
|||
Donr_Pol_Cons
|
|||
Donr_Pol_Lib
|
|||
Donr_Relig
|
|||
Donr_Vets
|
|||
Donr_Oth
|
|||
Donr_Comm_Char
|
|||
Vet_In_Hh
|
|||
Int_Oth_Parenting
|
|||
Single_Parent
|
|||
Buy_Infant_Apparel
|
|||
Buy_Kids_Learn_Toys
|
Boolean | t | |
Buy_Kids_Baby_Care
|
Boolean | t | |
Buy_Kids_School
|
|||
Buy_Kids_Genl
|
Boolean | t | |
Young_Adult_In_Hh
|
|||
Sr_Adult_In_Hh
|
|||
Int_Oth_Kids_Ints
|
Boolean | t | |
Int_Oth_Grandkids
|
|||
Int_Oth_Christian_Fam
|
|||
Buy_Pets
|
|||
Int_Oth_Pets_Horse
|
|||
Int_Oth_Pets_Cat
|
|||
Int_Oth_Pets_Dog
|
|||
Int_Oth_Pets_Oth
|
|||
Int_Oth_Career_Imp
|
|||
Occ_Working_Wmn
|
|||
Occ_Afric_Amer_Prof
|
|||
Occ_Soho_Ind
|
|||
Int_Oth_Career
|
|||
Buy_Magazines
|
Boolean | t | |
Buy_Books
|
Boolean | t | |
Buy_Audio_Books
|
|||
Read_Avid
|
Boolean | t | |
Read_Relig
|
|||
Read_Scifi
|
|||
Read_Magazines
|
Boolean | t | |
Read_Audio_Books
|
|||
Int_Grp_Read
|
Boolean | t | |
Read_Hist_Mltry
|
|||
Read_Curr_Affairs
|
|||
Buy_Religious
|
|||
Read_Science_Space
|
|||
Mags
|
Boolean | t | |
Ent_Educ_Ol
|
|||
Ent_Gaming
|
|||
Occ_Comp_Genl
|
|||
Ent_Dvd_Videos
|
|||
Ent_Tv_Video_Movie
|
|||
Occ_Home_Off
|
|||
Ent_Hi_End_Appl
|
|||
Ent_Hdtv_Int
|
|||
Ent_Stereo
|
|||
Ent_Music_Playr
|
|||
Ent_Music_Coll
|
|||
Ent_Music_Avid
|
|||
Ent_Movie_Coll
|
|||
Ent_Cable_Tv
|
|||
Ent_Video_Gaming
|
|||
Ent_Sat_Dish
|
|||
Ent_Computers
|
Boolean | t | |
Ent_Pc_Gaming
|
|||
Ent_Cons_Elec
|
|||
Int_Grp_Movie_Music
|
|||
Int_Grp_Elec
|
|||
Int_Oth_Telcomm
|
|||
Buy_Antiques
|
|||
Buy_Art
|
|||
Ent_Theater
|
|||
Int_Oth_The_Arts
|
|||
Ent_Mus_Instr
|
|||
Int_Coll_Genl
|
|||
Int_Coll_Stamps
|
|||
Int_Coll_Coins
|
|||
Int_Coll_Arts
|
|||
Int_Coll_Antiques
|
|||
Int_Coll_Avid
|
|||
Int_Grp_Coll
|
|||
Int_Coll_Sports
|
|||
Int_Coll_Mil
|
|||
Buy_Collectibles
|
|||
Int_Hob_Diy
|
|||
Int_Auto_Wk
|
|||
Int_Hob_Sew
|
|||
Int_Hob_Woodwk
|
|||
Int_Hob_Photo
|
|||
Int_Aviation
|
|||
Int_Hob_House_Plant
|
|||
Int_Hob_Crafts
|
Boolean | t | |
Int_Hob_Gardening
|
|||
Buy_Gardening
|
|||
Buy_Home_Gard
|
Boolean | t | |
Int_Grp_Home_Imp
|
Boolean | t | |
Buy_Crafts
|
|||
Buy_Photo_Video
|
|||
Int_Oth_Smoking
|
|||
Int_Oth_Home_Dec
|
Boolean | t | |
Int_Hob_Home_Imp
|
Boolean | t | |
Int_Oth_Home_Imp_Int
|
|||
Int_Oth_Cook_Wine
|
|||
Int_Oth_Cook_Gnrl
|
|||
Int_Oth_Cook_Gourmet
|
|||
Int_Oth_Cook_Nat_Food
|
|||
Int_Grp_Cook
|
|||
Int_Hob_Games
|
|||
Int_Trav_Casino
|
|||
Int_Hob_Sweeps
|
|||
Int_Grp_Travel
|
|||
Int_Trav_Genl
|
|||
Int_Trav_Us
|
|||
Int_Trav_Intl
|
|||
Int_Trav_Cruise
|
|||
Life_Home
|
|||
Life_Diy
|
|||
Life_Sporty
|
|||
Life_Upscale
|
|||
Life_Culture
|
|||
Life_Highbrow
|
|||
Life_Ht
|
|||
Life_Common
|
|||
Life_Prof
|
|||
Life_Broader
|
|||
Int_Grp_Exer
|
|||
Int_Fit_Jog
|
|||
Int_Fit_Walk
|
|||
Int_Fit_Aerob
|
|||
Int_Sport_Spect_Auto
|
|||
Int_Sport_Spect_Tv_Sports
|
|||
Int_Sport_Spect_Foot
|
|||
Int_Sport_Spect_Base
|
|||
Int_Sport_Spect_Bskt
|
|||
Int_Sport_Spect_Hockey
|
|||
Int_Sport_Spect_Soccer
|
|||
Int_Sport_Tennis
|
|||
Int_Sport_Golf
|
|||
Int_Sport_Snow_Ski
|
|||
Int_Sport_Mtrcycl
|
|||
Int_Sport_Nascar
|
|||
Int_Sport_Boating
|
|||
Int_Sport_Scuba
|
|||
Buy_Sport_Leis
|
|||
Buy_Hunting
|
|||
Int_Sport_Fishing
|
|||
Int_Sport_Camp
|
|||
Int_Sport_Shoot
|
|||
Int_Grp_Sports
|
Boolean | t | |
Int_Grp_Outdoor
|
Boolean | t | |
Int_Fit_Health_Med
|
|||
Int_Fit_Diet
|
|||
Int_Fit_Self_Imp
|
|||
Buy_Auto_Parts
|
|||
Genl_Pp_Home_Value
|
Integer | 6 | |
Genl_Purch_Dt
|
Integer | 0 | |
Genl_Purch_Amt
|
Integer | 0 | |
Genl_Sls_Trans
|
String | R | |
Mr_Amt
|
Integer | 0 | |
Mr2_Amt
|
Integer | 0 | |
P1_Amt
|
Integer | 0 | |
P2_Amt
|
Integer | 45200 | |
Mr_Dt
|
Integer | 0 | |
Mr2_Dt
|
Integer | 0 | |
P1_Dt
|
Integer | 20110830 | |
Mr_Loan_Typ
|
String | C | |
Mr2_Loan_Typ
|
|||
P1_Loan_Typ
|
|||
P2_Loan_Typ
|
|||
Mr_Lendr_Cd
|
|||
Mr2_Lendr_Cd
|
|||
P1_Lendr_Cd
|
Integer | 0 | |
Mr_Lendr
|
|||
Mr2_Lendr
|
|||
P1_Lendr
|
String | AMERIPRO F | |
Mr_Rate_Typ
|
|||
Mr2_Rate_Typ
|
|||
P1_Rate_Typ
|
|||
P2_Rate_Typ
|
Boolean | f | |
Mr_Rate
|
|||
Mr2_Rate
|
|||
P1_Rate
|
Integer | 0 | |
P2_Rate
|
|||
Prop_Bld_Yr
|
Integer | 2005 | |
Prop_Ac
|
String | A | |
Prop_Pool
|
Boolean | t | |
Prop_Fuel
|
|||
Prop_Sewer
|
Integer | 0 | |
Prop_Water
|
Integer | 0 | |
Genl_Loan_To_Value
|
Integer | 63 | |
Ethnic_Code
|
String | T3 | |
Ethnic_Conf
|
|||
Ethnic_Grp
|
String | W | |
Ethnic_Lang
|
String | E1 | |
Ethnic_Relig
|
String | P | |
Ethnic_Hisp_Cntry
|
Integer | 0 | |
Ethnic_Assim
|
|||
Credit_Rating
|
String | C | |
Dnc_Flag
|
Boolean | t | |
Perm_Id
|
Integer | 0 | |
Addr_Primary
|
String | 2516 Lipizzan Dr | |
Addr_Pre
|
|||
Addr_Street
|
String | Lipizzan | |
Addr_Post
|
|||
Addr_Suffix
|
String | Dr | |
Addr_Abrev
|
String | Austin | |
Addr_Secy
|
|||
Prop_Type
|
|||
String | Email Address | ||
Telephone_Landline_2
|
Integer | 0 | |
Cellphone_1
|
Integer | 5127516999 | |
Cellphone_Carrier_1
|
String | AT&T | |
Cellphone_Dnc_Flag_1
|
Boolean | t | |
Telephone_Work_1
|
Integer | 0 | |
Url
|
String | yourpaydaycashadvance.com | |
Ip
|
|||
Optin_Date
|
String | 7/31/2018 | |
Email_Verify_Flag
|
Boolean | t | |
Domain
|
String | gmail | |
Cellphone_2
|
Integer | 0 | |
Providersms
|
Integer | 0 | |
Cellphone_Carrier_2
|
|||
Cell_Phone_Date
|
|||
Auto_Make
|
String | GMC | |
Auto_Model_
|
String | Sierra 1500 | |
Auto_Year_
|
Integer | 2014 | |
Auto_Vin_
|
String | 3GTP1VEC2EG421703 | |
Auto_Tdate_
|
String | 1/1/1900 | |
Auto_Trim
|
String | SLT | |
Auto_Style
|
String | 4x2 SLT 4dr Crew Cab 5.8 ft. SB | |
Auto_Vehicle_Type
|
String | TRUCK | |
Auto_Body_Type
|
String | PICKUP | |
Auto_Msrp
|
Integer | 41860 | |
Auto_Fuel_Type
|
Boolean | f | |
Auto_Def_Engine_Cylinders
|
Integer | 8 | |
Auto_Def_Trans_Type
|
String | A | |
Auto_Max_Payload
|
Integer | 1933 | |
Auto_Mfg_Code
|
String | G | |
Auto_Gvw_Range
|
String | 6001-7000 | |
Number_of_vehicles_in_HH
|
Integer | 7 | |
Party_Affiliation
|
|||
Driverslicensestate
|
|||
Driverslicenseeverrevoked
|
|||
AutoHasABS
|
|||
AutoHasAirbags
|
|||
AutoAlarmType
|
|||
Autoinscompany
|
|||
Autoinsuredsince
|
|||
Autoinsexpirydate
|
|||
Autoinscoveragetype
|
|||
Autoinsbodilyinjurycoverage
|
|||
Autoinspropertydamagecoverage
|
|||
Autoinscollisiondeductible
|
|||
Autoinscomprehensivedeductible
|
|||
AutoAnnualMiles
|
|||
AI_Autoyear
|
Integer | 2014 | |
AI_Automake
|
String | GMC | |
AI_Automodel
|
String | Sierra 1500 | |
Autocommutedistance
|
|||
Autoinscoveragetyperequested
|
|||
Autoprimaryuse
|
|||
Auto_Insurance_Date
|
|||
Address_ID
|
Integer | 81283185 | |
Household_ID
|
Integer | 197073332 | |
CAPE: Inc: HH: Median Family Household Income
|
Integer | 145369 | |
CAPE: Age: Pop: Median Age
|
Integer | 4500 | |
CAPE: Age: Pop: % 0-17
|
Integer | 414 | |
CAPE: Age: Pop: % 18-99+
|
Integer | 765 | |
CAPE: Age: Pop: % 65-99+
|
Integer | 168 | |
CAPE: Ethnic: Pop: % White Only
|
Integer | 921 | |
CAPE: Ethnic: Pop: % Black Only
|
Integer | 27 | |
CAPE: Ethnic: Pop: % Asian Only
|
Integer | 142 | |
CAPE: Ethnic: Pop: % Hispanic
|
Integer | 87 | |
CAPE: Density: Persons Per HH for Pop in HH
|
Integer | 344 | |
CAPE: HHSize: HH: Average Household Size
|
Integer | 344 | |
CAPE: Typ: HH: % Married Couple Family
|
Integer | 847 | |
CAPE: Child: HH: % with Persons LT18
|
Integer | 681 | |
CAPE: Child: HH: % Marr Couple FamW/ Persons LT18
|
Integer | 633 | |
CAPE: Child: HH: % Marr Couple FamW/O Persons LT18
|
Integer | 427 | |
CAPE: Lang: HH: % Spanish Speaking
|
Integer | 77 | |
CAPE: Educ: Pop25+: Median Education Attained
|
Integer | 153 | |
CAPE: HomVal: OOHU: Median Home Value
|
Integer | 286 | |
CAPE: HUStr: HU: % Mobile Home
|
Integer | 418953 | |
CAPE: Built: HU: Median Housing Unit Age
|
Integer | 42 | |
CAPE: Tenancy: OCCHU: % Owner Occupied
|
Integer | 921 | |
CAPE: Tenancy: OCCHU: % Renter Occupied
|
Integer | 130 | |
Auto In The Market: New
|
Integer | 5 | |
Auto In The Market: Used
|
Integer | 9 | |
Auto In The Market: Used 0-5 Vehicle
|
Integer | 8 | |
Auto In The Market: Used 6-10 Vehicle
|
Integer | 9 | |
Auto In The Market: Used 11+ Vehicle
|
Integer | 9 |
Attribute | Type | Example | Mapping |
---|---|---|---|
name
|
Joe Smith | ||
String | Address | ||
String | Email Address | ||
String | Phone Number | ||
over 500 demographics
|
mechanic | ||
String | VIN | ||
String | MAID |
Description
Country Coverage
History
Volume
150 million | records |
Pricing
License | Starts at |
---|---|
One-off purchase | Not available |
Monthly License |
$8,000$7,600 / month |
Yearly License |
$96,000$91,200 / year |
Usage-based | Not available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Datastream Group Automotive Ownership Data USA with Consumer Demographics?
Automotive VIN Database of over 155 million car owners in the USA. Available for Licensing and Installs. Fully Enhanced and Technology Ready.
What is Datastream Group Automotive Ownership Data USA with Consumer Demographics used for?
This product has 5 key use cases. Datasys recommends using the data for Audience Targeting, Contact Validation, Identity-Based Targeting, Behavioral Targeting, and Consumer Intelligence. Global businesses and organizations buy Firmographic Data from Datasys to fuel their analytics and enrichment.
Who can use Datastream Group Automotive Ownership Data USA with Consumer Demographics?
This product is best suited if you’re a Enterprise or Medium-sized Business looking for Firmographic 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 Datastream Group Automotive Ownership Data USA with Consumer Demographics go?
This product has 24 months of historical coverage. It can be delivered on a monthly and on-demand basis.
Which countries does Datastream Group Automotive Ownership Data USA with Consumer Demographics cover?
This product includes data covering 1 country like USA. Datasys is headquartered in United States of America.
How much does Datastream Group Automotive Ownership Data USA with Consumer Demographics cost?
Pricing for Datastream Group Automotive Ownership Data USA with Consumer Demographics starts at USD8,000 per month. Datasys offers a 5% discount when you buy data from them through Datarade. Connect with Datasys to get a quote and arrange custom pricing models based on your data requirements.
How can I get Datastream Group Automotive Ownership Data USA with Consumer Demographics?
Businesses can buy Firmographic Data from Datasys and get the data via S3 Bucket, SFTP, REST API, and Feed API. Depending on your data requirements and subscription budget, Datasys can deliver this product in .csv and .txt format.
What is the data quality of Datastream Group Automotive Ownership Data USA with Consumer Demographics?
Datasys has reported that this product has the following quality and accuracy assurances: 60% match rate to Mobile Devices. 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 Datastream Group Automotive Ownership Data USA with Consumer Demographics?
This product has 3 related products. These alternatives include DrivenIQ’s Consumer Enrichment/Enhancement/Append 500+ fields ICP Look A Like Model USA 6 Billion records HEM MAID EMAIL First Party Opt-In, Alesco Consumer Database - Individual-Level Consumer Data - 264+ million US consumers with 220+ million opt-in emails - available for licensing!, and Factori People Data Global coverage with 900 Million+ device profiles. You can compare the best Firmographic Data providers and products via Datarade’s data marketplace and get the right data for your use case.